Purpose: Radiation dermatitis is one of the most common adverse events in patients undergoing radiotherapy. However, the objective evaluation of this condition is difficult to provide because the clinical evaluation of radiation dermatitis is made by visual assessment based on Common Terminology Criteria for Adverse Events (CTCAE). Therefore, we created a radiation dermatitis grading support system (RDGS) using a deep convolutional neural network (DCNN) and then evaluated the effectiveness of the RDGS. Methods: The DCNN was trained with a dataset that comprised 647 clinical skin images graded with radiation dermatitis (Grades 1–4) at our center from April 2011 to May 2019. We created the datasets by mixing data augmentation images generated by image conversion and images generated by Poisson image editing using the hybrid generation method (Hyb) against lowvolume severe dermatitis (Grade 4). We then evaluated the classification accuracy of RDGS based on the hybrid generation method (Hyb-RDGS). Results: The overall accuracy of the Hyb-RDGS was 85.1%, which was higher than that of the data augmentation method generally used for image generation. Conclusion: Effectiveness of the Hyb-RDGS using Poisson image editing was suggested. This result shows a possible supporting system for objective evaluation in grading radiation dermatitis.

Purpose: The purpose was to study comparative evaluation of calculated dose distribution by X-ray Voxel Monte Carlo (XVMC) for dose calculation in Acuros XB (AXB). The dose commissioning and head and neck volumetric modulated arc therapy (VMAT) clinical cases were compared for AXB in Eclipse and XVMC in Monaco. Methods: For TrueBeam at 6 MV, we compared the dose commissioning for simple rectangle, heterogeneity correction, and multileaf collimator (MLC) characteristics. 15 clinical cases were compared for computation times, calculation accuracy, dose-volume histogram (DVH), and 3D-γ analysis (γ 3%/2 mm). Results: There was no difference between the calculated values of jaw field, the measurement errors of both were within± 1%, and the dose profiles of water, bone, and lung equivalent slab phantoms were in good agreement. There was no difference in transmission, tongue and groove effect, and there was a difference of less than 10% in leaf-end transmission. In clinical cases, the computation time of XVMC was a half time that of AXB, the average values of the dose difference between the two dose calculations were –1.17±2.14%, and there was no difference in measurement error (AXB: –0.73±0.79%, XVMC: –0.07±1.21%). In DVH, max doses of XVMC were about 3% higher in planning target volume (PTV) and gross tumor volume (GTV), but the pass rate of 3D-γ analysis was overall 95.11±2.59%, which was in good agreement. Conclusions: Both dose calculation algorithms were equivalent, suggesting that Monaco XVMC is a verification method with a high accuracy for comparative evaluation of calculated dose distribution.

Purpose: The International Commission on Radiological Protection recommends adaptation of the diagnostic reference levels (DRLs). Japan DRLs 2020 apply the entrance surface dose (ESD) in radiography. However, it is difficult to measure ESD in the clinical setting. A dose area product meter has been proposed for use as a dose index in interventional radiology. We investigated the basic characteristic of a dose area product meter and the relationship of ESD and dose area product meter values in radiography. Method: We measured calibration factors from phantom studies and estimated ESD from the dose area product meter. Subject thickness was measured from the chest clinical images for calculation of ESD. Estimated ESD from the dose area product meter was compared with that calculated from program software (Surface Dose Evaluation Code, Sdec). Result: Relative dose (dose area product meter/ionization chamber) decreased when tube voltage was lower (60 kV) or higher (130 kV). A positive correlation was found between the estimated and calculated ESD. Conclusion: Dose area product meter can be used for patient’s dose control in radiography.

Purpose: In our proton beam therapy center, we use imaging plates (IP) for dose verification of field matching in irradiation (called patch-field technique). In this study, a polymer gel dosimeter, which can perform three- dimensional dose distribution measurement, was used as a new tool for the verification of the patch field irradiation method corresponding to the rectangular irradiation. Method: The results of measurements of the PAGAT gel dosimeter to irradiate to two rectangular fields called as patch irradiation fields, which were created using the treatment planning system, were evaluated and compared to the results of IP and plan in profiles near the boundary of two fields. Result: In the case of no gap between the two fields, the relative dose using the gel dosimeter was 10.1% higher compared to that measured with the IP in the midpoint of two fields. In case of overlap (called hot region), the result of gels was 6.3% higher than that of IP. In the case of space (called cold region), the result of gels was 14.9% higher than that of IP. The results of the difference between gel and plan in the midpoint of two fields were 14.2% (no gap), −5.0% (hot), and 10.5% (cold). Conclusion: We found that the gel dosimeter was a 3-D dosimetric tool and possibility method for dose verification of patch fields. In this study, the results were preliminary and included several error factors. In the future, it is necessary to develop a dosimeter with improved and more precise measurements.

Purpose: Foreign bodies such as a surgical gauze can be retained in the body after surgery and in some cases cannot be detected by postoperative radiography. The aim of this study was to develop an object detection model capable of postsurgical detection of retained gauze in the body. The object detection model used deep learning using abdominal radiographs, and a phantom study was performed to evaluate the ability of the model to automatically detect retained surgical gauze. Materials and Methods: The object detection model was constructed using a Single Shot MultiBox Detector (SSD) 300. In total, 268 abdominal phantom images were used: 180 gauze images were used as training data, 20 gauze images were used as validation data, and an additional 34 gauze images and 34 nongauze images were used as test data. To evaluate the performance of the object detection model, a confusion matrix was created and the accuracy and sensitivity were calculated. Result: True-positive (TP) rate, true-negative (TN) rate, false-positive (FP) rate, and false-negative (FN) rate were 0.92, 1.00, 0.00, and 0.08, respectively. Accuracy was 0.96, and sensitivity was 0.92. Conclusion: The object detection model could detect surgical gauze on abdominal phantom images with a high accuracy and sensitivity.

Purpose: The method using a numerical slit (slit method) is used commonly to obtain the one-dimensional (1D) noise power spectrum (NPS) in computed tomography. However, the relationship between the 1D-NPS obtained by the slit method and the original two-dimensional (2D) NPS derived by the 2D Fourier transformation has not been elucidated clearly. The purpose of this study was to clarify their relationship based on the well-known central slice theorem (projection slice theorem) and validate it using computer simulation analysis. Methods: With the application of the central slice theorem, we described that the 1D-NPS obtained by the slit method was equal to the central slice (profile) in the 2D-NPS when we set the slit length to the maximum (i.e. the matrix size of the noise image). To verify this, we generated computer-simulated noise images with the known 2D-NPS (true 2D-NPS). From those images, we obtained the 1D-NPS that was obtained by the slit method and compared it with the central slice in the true 2D-NPS. Results: When we set the slit length to the maximum, the 1D-NPS obtained by the slit method showed good agreement with the central slice in the true 2D-NPS. Conclusion: We clarified the relationship between the 1D-NPS obtained by the slit method and the 2D-NPS using a theoretical approach and the computer simulation. We had to maximize the slit length to achieve the accurate measurement of the 1D-NPS using the slit method.