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Purpose: Patients with head and neck cancer (HNC) who undergo dental procedures during radiotherapy (RT) face an increased risk of developing osteoradionecrosis (ORN). Accordingly, new tools must be developed to extract critical information regarding the dose delivered to the teeth and mandible. This article proposes a novel approach for visualizing 3-dimensional planned dose distributions on panoramic reconstruction computed tomography (pCT) images. Materials and Methods: Four patients with HNC who underwent volumetric modulated arc therapy were included. One patient experienced ORN and required the extraction of teeth after RT. In the study approach, the dental arch curve (DAC) was defined using an open-source platform. Subsequently, pCT images and dose distributions were generated based on the new coordinate system. All teeth and mandibles were delineated on both the original CT and pCT images. To evaluate the consistency of dose metrics, the Mann-Whitney U test and Student t-test were employed. Results: A total of 61 teeth and 4 mandibles were evaluated. The correlation coefficient between the 2 methods was 0.999, and no statistically significant difference was observed (P>0.05). This method facilitated a straightforward and intuitive understanding of the delivered dose. In 1 patient, ORN corresponded to the region of the root and the gum receiving a high dosage (approximately 70 Gy). Conclusion: The proposed method particularly benefits dentists involved in the management of patients with HNC. It enables the visualization of a 3-dimensional dose distribution in the teeth and mandible on pCT, enhancing the understanding of the dose delivered during RT.
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PURPOSE: This study aimed to clarify the dosimetric impact of the respiratory motion of the liver on stereotactic body radiation therapy (SBRT) for spine metastasis and examine the utility of introducing beam avoidance (beam-off at specific gantry angles). METHODS: A total of 112 consecutive patients who underwent SBRT for spine metastasis between 2018 and 2024 were examined. Overall, 15 patients who had lesions near the liver dome were included in this study. Retrospective treatment plans were generated using computed tomography (CT) images acquired during inhalation and exhalation to evaluate the dosimetric impact of respiratory motion of the liver. The dose difference (DD) and relative value (DD%) were evaluated using the dose-volume histogram (DVH) metrics, planning target volume Dmax, D95%, spinal cord D0.035 cc, and esophagus D2.5 cc. The magnitude of the liver movements was evaluated based on differences of liver size Lave at the isocentric axial plane between the inspiratory and expiratory CT images. RESULTS: The DD in almost all DVH metrics tended to increase when the liver moved away from the target during inhalation: For example, Mean ± $ \pm $ a standard deviation (SD) DD in PTV D95% for the treatment plan incorporating beam avoidance and those without beam avoidance was 0.5 ± $\pm$ 0.3 and 0.9 ± $ \pm $ 0.6 Gy, respectively. The spinal cord D0.035 cc for those shows 0.4 ± $ \pm $ 0.2 and 0.7 ± $ \pm $ 0.7 Gy, respectively. The treatment plans without beam avoidance also showed moderate or strong correlations between Lave and DD for almost all DVH metrics. No correlation was seen in the beam avoidance plan. The spinal cord D0.035 cc revealed approximately 1 Gy or +4% in DD when Lave was < -4 cm. CONCLUSIONS: Respiratory motion of the liver dome can cause substantial dosimetric discrepancies in the dose delivered to the spinal cord, although the extent depends on patient variables. Dose assessment should be performed for determining the appropriate means of respiratory management, such as breath-hold. Alternatively, beam avoidance effectively mitigates the impact.
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BACKGROUND: Boron Neutron Capture Therapy (BNCT) has recently been used in clinical oncology thanks to recent developments of accelerator-based BNCT systems. Although there are some specific processes for BNCT, they have not yet been discussed in detail. PURPOSE: The aim of this study is to provide comprehensive data on the risk of accelerator-based BNCT system to institutions planning to implement an accelerator-based BNCT system. METHODS: In this study, failure mode and effects analysis (FMEA) was performed based on a treatment process map prepared for the accelerator-based BNCT system. A multidisciplinary team consisting of a medical doctor (MD), a registered nurse (RN), two medical physicists (MP), and three radiologic technologists (RT) identified the failure modes (FMs). Occurrence (O), severity (S), and detectability (D) were scored on a scale of 10, respectively. For each failure mode (FM), risk priority number (RPN) was calculated by multiplying the values of O, S, and D, and it was then categorized as high risk, very high risk, and other. Additionally, FMs were statistically compared in terms of countermeasures, associated occupations, and whether or not they were the patient-derived. RESULTS: The identified FMs for BNCT were 165 in which 30 and 17 FMs were classified as high risk and very high risk, respectively. Additionally, 71 FMs were accelerator-based BNCT-specific FMs in which 18 and 5 FMs were classified as high risk and very high risk, respectively. The FMs for which countermeasures were "Education" or "Confirmation" were statistically significantly higher for S than the others (p = 0.019). As the number of BNCT facilities is expected to increase, staff education is even more important. Comparing patient-derived and other FMs, O tended to be higher in patient-derived FMs. This could be because the non-patient-derived FMs included events that could be controlled by software, whereas the patient-derived FMs were impossible to prevent and might also depend on the patient's condition. Alternatively, there were non-patient-derived FMs with higher D, which were difficult to detect mechanically and were classified as more than high risk. In O, significantly higher values (p = 0.096) were found for FMs from MD and RN associated with much patient intervention compared to FMs from MP and RT less patient intervention. Comparing conventional radiotherapy and accelerator-based BNCT, although there were events with comparable risk in same FMs, there were also events with different risk in same FMs. They could be related to differences in the physical characteristics of the two modalities. CONCLUSIONS: This study is the first report for conducting a risk analysis for BNCT using FMEA. Thus, this study provides comprehensive data needed for quality assurance/quality control (QA/QC) in the treatment process for facilities considering the implementation of accelerator-based BNCT in the future. Because many BNCT-specific risks were discussed, it is important to understand the characteristics of BNCT and to take adequate measures in advance. If the effects of all FMs and countermeasures are discussed by multidisciplinary team, it will be possible to take countermeasures against individual FMs from many perspectives and provide BNCT more safely and effectively.
