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Purpose To share the experience of an iridium-192 (192Ir) source stuck event during high-dose-rate (HDR) brachytherapy for cervical cancer. Material and methods In 2014, we experienced the first source stuck event in Japan when treating cervical cancer with HDR brachytherapy. The cause of the event was a loose screw in the treatment device that interfered with the gear reeling the source. This event had minimal clinical effects on the patient and staff; however, after the event, we created a normal treatment process and an emergency process. In the emergency processes, each staff member is given an appropriate role. The dose rate distribution calculated by the new Monte Carlo simulation system was used as a reference to create the process. Results According to the calculated dose rate distribution, the dose rates inside the maze, near the treatment room door, and near the console room were ≅ 10-2 [cGy · h-1], 10-3 [cGy · h-1], and << 10-3 [cGy · h-1], respectively. Based on these findings, in the emergency process, the recorder was evacuated to the console room, and the rescuer waited inside the maze until the radiation source was recovered. This emergency response manual is currently a critical workflow once a year with vendors. Conclusions We reported our experience of the source stuck event. Details of the event and proposed emergency process will be helpful in managing a patient safety program for other HDR brachytherapy users.

Out‐of‐field organs are not commonly designated as dose calculation targets during radiation therapy treatment planning, but they might entail risks of second cancer. Risk components include specific internal body scatter, which is a dominant source of out‐of‐field doses, and head leakage, which can be reduced by external shielding. Our simulation study quantifies out‐of‐field organ doses and estimates second cancer risks attributable to internal body scatter in whole‐breast radiotherapy (WBRT) with or without additional regional nodal radiotherapy (RNRT), respectively, for right and left breast cancer using Monte Carlo code PHITS. Simulations were conducted using a complete whole‐body female model. Second cancer risk was estimated using the calculated doses with a concept of excess absolute risk. Simulation results revealed marked differences between WBRT alone and WBRT plus RNRT in out‐of‐field organ doses. The ratios of mean doses between them were as large as 3.5–8.0 for the head and neck region and about 1.5–6.6 for the lower abdominal region. Potentially, most out‐of‐field organs had excess absolute risks of less than 1 per 10,000 persons‐year. Our study surveyed the respective contributions of internal body scatter to out‐of‐field organ doses and second cancer risks in breast radiotherapy on this intact female model.

To minimise the radiation dermatitis related to interventional radiology (IR), rapid and accurate dose estimation has been sought for all procedures. We propose a technique for estimating the patient skin dose rapidly and accurately using Monte Carlo (MC) simulation with a graphical processing unit (GPU, GTX 1080; Nvidia Corp.). The skin dose distribution is simulated based on an individual patient’s computed tomography (CT) dataset for fluoroscopic conditions after the CT dataset has been segmented into air, water and bone based on pixel values. The skin is assumed to be one layer at the outer surface of the body. Fluoroscopic conditions are obtained from a log file of a fluoroscopic examination. Estimating the absorbed skin dose distribution requires calibration of the dose simulated by our system. For this purpose, a linear function was used to approximate the relation between the simulated dose and the measured dose using radiophotoluminescence (RPL) glass dosimeters in a water-equivalent phantom. Differences of maximum skin dose between our system and the Particle and Heavy Ion Transport code System (PHITS) were as high as 6.1%. The relative statistical error (2 σ) for the simulated dose obtained using our system was ≤3.5%. Using a GPU, the simulation on the chest CT dataset aiming at the heart was within 3.49 s on average: the GPU is 122 times faster than a CPU (Core i7–7700K; Intel Corp.). Our system (using the GPU, the log file, and the CT dataset) estimated the skin dose more rapidly and more accurately than conventional methods.