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Background: The distribution of radiation exposure on the body surface of interventional echocardiographers during structural heart disease (SHD) procedures is unclear. Objectives: This study estimated and visualized radiation exposure on the body surface of interventional echocardiographers performing transesophageal echocardiography by computer simulations and real-life measurements of radiation exposure during SHD procedures. Methods: A Monte Carlo simulation was performed to clarify the absorbed dose distribution of radiation on the body surface of interventional echocardiographers. The real-life radiation exposure was measured during 79 consecutive procedures (44 transcatheter edge-to-edge repairs of the mitral valve and 35 transcatheter aortic valve replacements [TAVRs]). Results: The simulation demonstrated high-dose exposure areas (>20 µGy/h) in the right half of the body, especially the waist and lower body, in all fluoroscopic directions caused by scattered radiation from the bottom edge of the patient bed. High-dose exposure occurred when obtaining posterior-anterior and cusp-overlap views. The real-life exposure measurements were consistent with the simulation estimates: interventional echocardiographers were more exposed to radiation at their waist in transcatheter edge-to-edge repair than in TAVR procedures (median 0.334 µSv/mGy vs 0.053 µSv/mGy; P < 0.001) and in TAVR with self-expanding valves than in those with balloon-expandable valves (median 0.067 µSv/mGy vs 0.039 µSv/mGy; P < 0.01) when the posterior-anterior or the right anterior oblique angle fluoroscopic directions were used. Conclusions: During SHD procedures, the right waist and lower body of interventional echocardiographers were exposed to high radiation doses. Exposure dose varied between different C-arm projections. Interventional echocardiographers, especially young women, should be educated regarding radiation exposure during these procedures. (The development of radiation protection shield for catheter-based treatment of structural heart disease [for echocardiologists and anesthesiologists]; UMIN000046478).

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Resuscitative endovascular balloon occlusion of the aorta (REBOA) is an endovascular procedure for hemorrhage control. In REBOA, the balloon must be placed in the precise place, but it may be performed without X-ray fluoroscopy. This study aimed to estimate the REBOA zones from the body surface using deep learning for safe balloon placement. A total of 198 abdominal computed tomography (CT) datasets containing the regions of the REBOA zones were collected from open data libraries. Then, depth images of the body surface generated from the CT datasets and the images corresponding to the zones were labeled for deep learning training and validation. DeepLabV3+, a deep learning semantic segmentation model, was employed to estimate the zones. We used 176 depth images as training data and 22 images as validation data. A nine-fold cross-validation was performed to generalize the performance of the network. The median Dice coefficients for Zones 1-3 were 0.94 (inter-quarter range: 0.90-0.96), 0.77 (0.60-0.86), and 0.83 (0.74-0.89), respectively. The median displacements of the zone boundaries were 11.34 mm (5.90-19.45), 11.40 mm (4.88-20.23), and 14.17 mm (6.89-23.70) for the boundary between Zones 1 and 2, between Zones 2 and 3, and between Zone 3 and out of zone, respectively. This study examined the feasibility of REBOA zone estimation from the body surface only using deep learning-based segmentation without aortography.

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Catheterization for structural heart disease (SHD) requires fluoroscopic guidance, which exposes health care professionals to radiation exposure risk. Nevertheless, existing freestanding radiation shields for anesthesiologists are typically simple, uncomfortable rectangles. Therefore, we devised a new perforated radiation shield that allows anesthesiologists and echocardiographers to access a patient through its apertures during SHD catheterization. No report of the relevant literature has described the degree to which the anesthesiologist's radiation dose can be reduced by installing radiation shields. For estimating whole-body doses to anesthesiologists and air dose distributions in the operating room, we used a Monte Carlo system for a rapid dose-estimation system used with interventional radiology. The simulations were performed under four conditions: no radiation shield, large apertures, small apertures and without apertures. With small apertures, the doses to the lens, waist and neck surfaces were found to be comparable to those of a protective plate without an aperture, indicating that our new radiation shield copes with radiation protection and work efficiency. To simulate the air-absorbed dose distribution, results indicated that a fan-shaped area of the dose rate decrease was generated in the area behind the shield, as seen from the tube sphere. For the aperture, radiation was found to wrap around the backside of the shield, even at a height that did not match the aperture height. The data presented herein are expected to be of interest to all anesthesiologists who might be involved in SHD catheterization. The data are also expected to enhance their understanding of radiation exposure protection.

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For interventional radiology, dose management has persisted as a crucially important issue to reduce radiation exposure to patients and medical staff. This study designed a real-time dose visualization system for interventional radiology designed with mixed reality technology and Monte Carlo simulation. An earlier report described a Monte-Carlo-based estimation system, which simulates a patient's skin dose and air dose distributions, adopted for our system. We also developed a system of acquiring fluoroscopic conditions to input them into the Monte Carlo system. Then we combined the Monte Carlo system with a wearable device for three-dimensional holographic visualization. The estimated doses were transferred sequentially to the device. The patient's dose distribution was then projected on the patient body. The visualization system also has a mechanism to detect one's position in a room to estimate the user's exposure dose to detect and display the exposure level. Qualitative tests were conducted to evaluate the workload and usability of our mixed reality system. An end-to-end system test was performed using a human phantom. The acquisition system accurately recognized conditions that were necessary for real-time dose estimation. The dose hologram represents the patient dose. The user dose was changed correctly, depending on conditions and positions. The perceived overall workload score (33.50) was lower than the scores reported in the literature for medical tasks (50.60) for computer activities (54.00). Mixed reality dose visualization is expected to improve exposure dose management for patients and health professionals by exhibiting the invisible radiation exposure in real space.

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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.

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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.

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For interventional radiology (IR), understanding the precise dose distribution is crucial to reduce the risks of radiation dermatitis to patients and staff. Visualization of dose distribution is expected to support radiation safety efforts immensely. This report presents techniques for perceiving the dose distribution using virtual reality (VR) technology and for estimating the air dose distribution accurately using Monte Carlo simulation for VR dose visualization. We adopted an earlier reported Monte-Carlo-based estimation system for IR and simulated the dose in a geometrical area resembling an IR room with fluoroscopic conditions. Users of our VR system experienced a simulated air dose distribution in the IR room while the irradiation angle, irradiation timing, and lead shielding were controlled. The estimated air dose was evaluated through comparison with measurements taken using a radiophotoluminescence glass dosimeter. Our dose estimation results were consistent with dosimeter readings, showing a 13.5% average mutual difference. The estimated air dose was visualized in VR: users could view a virtual IR room and walk around in it. Using our VR system, users experienced dose distribution changes dynamically with C-arm rotation. Qualitative tests were conducted to evaluate the workload and usability of our VR system. The perceived overall workload score (18.00) was lower than the scores reported in the literature for medical tasks (50.60) and computer activities (54.00). This VR visualization is expected to open new horizons for understanding dose distributions intuitively, thereby aiding the avoidance of radiation injury.

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This study was conducted to improve cone-beam computed tomography (CBCT) image quality using the super-resolution technique, a method of inferring a high-resolution image from a low-resolution image. This technique is used with two matrices, so-called dictionaries, constructed respectively from high-resolution and low-resolution image bases. For this study, a CBCT image, as a low-resolution image, is represented as a linear combination of atoms, the image bases in the low-resolution dictionary. The corresponding super-resolution image was inferred by multiplying the coefficients and the high-resolution dictionary atoms extracted from planning CT images. To evaluate the proposed method, we computed the root mean square error (RMSE) and structural similarity (SSIM). The resulting RMSE and SSIM between the super-resolution images and the planning CT images were, respectively, as much as 0.81 and 1.29 times better than those obtained without using the super-resolution technique. We used super-resolution technique to improve the CBCT image quality.

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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.

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A novel cyclohexane/water/ionic-liquid (1-butyl-3-methylimidazolium hexafluorophosphate, [bmim][PF6]) triphasic extraction system was studied for a possible fractional extraction of divalent metal cations with co-using 8-quinolinol (HQ) and tri-n-octylphosphine oxide (TOPO) as competitive extractants. In this system, Ni2+ was extracted into the [bmim][PF6] phase as a Q(-)-complex, whereas each of Mn2+, Zn2+, Cd2+ and Pb2+ was extracted into the cyclohexane phase as an ion-pair of a cationic TOPO-complex and PF6-. A suitable selection of extractants and ionic liquid can result in developing a powerful triphasic fractional extraction system.