Journal of Radiation Research最新文献

Non-small cell lung cancer (NSCLC) constitutes 80-85% of lung cancers, with advanced cases showing a 20-30% 5-year survival rate. Radiation resistance limits radiotherapy efficacy, and the function of NOP58 in this process is unknown. This study investigated the mechanisms of NOP58 in NSCLC radioresistance. A radiation-resistant NSCLC cell line (H1299R) was established. Bioinformatic analysis of the Cancer Genome Atlas Program data revealed that high NOP58 expression correlates with poor patient prognosis. The expression levels of NOP58 and DDX18 expression were quantified via quantitative real-time polymerase chain reaction and Western blot. Radiosensitivity of H1299R cells and parental H1299 cells was assessed under irradiation (0, 2, 4, 6 and 8 Gy). Cell viability was assessed using cell counting kit-8 and colony formation assays. Apoptosis was detected by flow cytometry with Annexin V/PI staining. DNA damage was analyzed via γ-H2AX immunofluorescence and comet assays. NOP58 knockdown and DDX18 overexpression were performed for rescue experiments, and protein interaction was validated by pull-down assays. NOP58 and DDX18 were significantly upregulated in H1299R cells. H1299R cells exhibited higher cell viability, stronger colony-forming capacity, reduced apoptosis and less DNA damage under irradiation treatment. The depletion of NOP58 in H1299 and H1299R cells exacerbated radiation-induced DNA damage, reduced cell viability and promoted apoptosis, reversing radioresistance. Direct interaction between NOP58 and DDX18 was confirmed by pull-down assay. DDX18 overexpression reversed the radiosensitizing effects of NOP58 knockdown, including attenuated DNA damage and restored cell survival. Overexpression NOP58 converted radiosensitive cells to a resistant phenotype. NOP58 promotes NSCLC radioresistance by interacting with DDX18, regulating its expression and thereby suppressing radiation-induced DNA damage. The NOP58-DDX18 axis could be a promising therapeutic target for improving radiotherapy efficacy in NSCLC.

Boron neutron capture therapy (BNCT) utilizes high linear energy transfer (LET) α-particles and 7Li ions generated through the 10B(n, α)7Li reaction. Precise dosimetry is essential for maximizing therapeutic efficacy while minimizing normal tissue adverse events, considering the microscopic distribution of 10B and cellular structures. Recently, the photon isoeffective dose (DisoE) has been proposed as a more appropriate metric for BNCT treatment planning and can be evaluated using the stochastic microdosimetric kinetic (SMK) model. However, clinical implementation of the SMK model remains challenging due to the difficulty of evaluating its input parameters, which requires computationally intensive radiation transport simulations at the cellular scale. To address this issue, we developed LISMEC (Linear Interpolation System for Stochastic Microdosimetric Kinetic model parameters Evaluated from Cellular-scale simulation), a rapid estimation framework based on precomputed cellular-scale PHITS (Particle and Heavy Ion Transport code System) simulations covering various cell geometries and boron distributions. By applying a linear interpolation algorithm, LISMEC enables the retrieval of SMK model parameters without the need for computationally intensive cellular-scale simulations. The utility of LISMEC, in conjunction with PHITS, was demonstrated through simulations of various irradiation scenarios in reactor-based BNCT. The results showed that DisoE values ranged from 7.4 to 32.7 Gy, even under a fixed macroscopic 10B concentration of 60 ppm. These findings emphasize the importance of incorporating a microscopic distribution of 10B and cellular structures into BNCT treatment planning.

Proton beam therapy (PBT) provides sharper dose gradients than conventional photon radiotherapy, potentially reducing radiation exposure to normal tissues. However, acute genitourinary adverse events (GU AEs) remain a clinical concern. This study aimed to evaluate the incidence and predictors of grade ≥ 2 acute GU AEs in patients with localized prostate cancer treated with real-time image-gated, spot-scanning PBT (RGPT). We analyzed the prospective study data of 326 patients who received RGPT at a dose of 63 Gy (relative biological effectiveness [RBE]) in 21 fractions between 2019 and 2021. Acute GU AEs were graded according to the Common Terminology Criteria for Adverse Events (version 5.0). Multivariable logistic regression was used to analyze potential predictive factors, including baseline International Prostate Symptom Score (IPSS), age, comorbidities, hydrogel spacer placement, use of anticoagulants or urinary symptom medications, clinical stage, National Comprehensive Cancer Network (NCCN) risk classification, prostate volume, and dose-volume histogram parameters. Grade 2 acute GU AEs occurred in 127 patients (39.0%), whereas no grade ≥ 3 events were observed. Moderate (odds ratio [OR] = 1.71; 95% confidence interval [CI]: 1.03-2.82) and severe (OR = 3.75; 95% CI: 1.49-9.46) baseline IPSS, as well as age ≥ 75 years (OR = 1.80; 95% CI: 1.10-2.95), were significant independent predictors of grade ≥ 2 GU AEs. No dose-volume histogram parameters were significantly associated with grade ≥ 2 GU AEs. Baseline urinary symptoms and older age were independent predictors of grade ≥ 2 GU AEs, emphasizing the importance of pretreatment evaluation in optimizing patient selection and management.

This study evaluated the feasibility of pencil beam scanning (PBS) proton therapy for stereotactic body radiotherapy using an isodose prescription in patients with isolated early-stage lung cancer, comparing dose-volume metrics with those of volumetric modulated arc therapy (VMAT). Treatment plans were generated for 10 patients with tumors located at least 2 cm from the trachea. Each plan prescribed 48 Gy(RBE) in four fractions with a 60% isodose prescription. Both multi-field optimized and single-field optimized PBS plans used four fields, while VMAT plans used two coplanar arcs. Plan robustness was assessed by simulating setup errors of ±5.0 mm and density uncertainties of ±3.5%, with worst-case target coverage also analyzed. Comparisons among the three planning strategies employed Bonferroni-adjusted multiple comparisons for target coverage, robustness, and organ-at-risk doses. PBS achieved target coverage comparable to VMAT, with similar D98% (63.2 ± 1.3 GyRBE vs. 64.0 ± 1.6 Gy; P = 0.12), mean doses (73.2 ± 0.8 GyRBE vs. 73.7 ± 1.2 Gy; P = 0.21), and robustness (D98%: 50.2 ± 0.9 GyRBE vs. 50.3 ± 1.1 Gy; P = 0.77). For the normal lung, PBS significantly reduced low-dose exposure up to V10Gy, whereas VMAT was more effective in reducing doses from V20Gy to the prescription level. All evaluated organ-at-risks received significantly lower mean doses with PBS than with VMAT (P < 0.05). Under a 60% isodose prescription for lung stereotactic body radiotherapy, multi-field optimized-based PBS proton therapy provides target coverage and robustness comparable to VMAT while offering superior normal tissue sparing.

Following the Fukushima Daiichi Nuclear Power Plant accident, Japan enhanced its nuclear disaster preparedness framework. However, personnel shortages stemming from fear and anxiety persist as a critical issue during such disasters. This study investigated the willingness of medical professionals at four university hospitals in Kyushu to participate in nuclear disaster response activities and explored factors influencing this willingness. A cross-sectional web-based survey was conducted among staff at Nagasaki, Kyushu, Saga and Kagoshima University Hospitals. Participants answered 19 questions assessing their willingness to participate in nuclear or radiological emergency response and associated psychosocial and occupational factors. Multiple regression analysis was used to identify predictors of willingness (Q1). A total of 378 valid responses were analyzed. Demographic variables, including age, sex, occupation and disaster experience, did not significantly influence willingness. However, interest in nuclear or radiological emergencies (β =0.383, P < 0.05), Incentives (β =0.249), Family understanding (β =0.116) and Occupational norms (β =0.114) were positively associated with willingness. Conversely, Anxiety (β = -0.151), Expectation of routine training (β = -0.138) and Perceived frequency of nuclear disasters (β = -0.104) were negatively associated with willingness. Medical staff's willingness to respond to nuclear or radiological emergencies is influenced more by psychological and occupational perceptions than by demographic factors. Interventions such as incentive programs, family support initiatives, targeted training and anxiety-reduction strategies may enhance preparedness for and participation in future nuclear or radiological emergencies.

Daily attendance requirements for radiotherapy (RT) make geographic accessibility a critical determinant of treatment adherence and completion. Although facility surveys indicate that advanced modalities such as intensity-modulated radiotherapy (IMRT) and brachytherapy are concentrated in urban centers, precise nationwide quantification of the resulting patient travel burden remains lacking. This study provides the first nationwide, modality-stratified assessment of geographic access to RT in Japan. Using the Open Source Routing Machine and a high-resolution dataset of 176 964 household-weighted 1-km mesh centroids, we calculated driving times to the nearest external-beam radiotherapy (EBRT), IMRT and brachytherapy facilities. Beyond standard distribution metrics, we generated high-resolution 'penalty maps' to quantify the incremental time tax imposed by advanced modality requirements. Although EBRT access was uniformly short nationwide, with a median travel time of 6.48 min, this increased to 8.26 min for IMRT and 14.06 min for brachytherapy. Crucially, the proportion of the population facing poor access (≥120 min) doubled from 0.24% for EBRT to 0.48% for brachytherapy. The spatial analysis identified specific 'newly poor-access' areas-regions that are accessible for EBRT but become remote when advanced care is needed-forming coherent geographic clusters in mountainous and island zones. These findings demonstrate that modality requirements introduce meaningful inequities despite strong national EBRT infrastructure. These indicators provide a vital evidence base for spatially optimizing resources to mitigate travel burdens for Japan's aging, mobility-limited population.

During the coronavirus disease 2019 (COVID-19) pandemic, a short-term decline in radiotherapy use was reported. In this study, we investigated long-term changes in the use of radiotherapy and hypofractionated radiotherapy before and after the COVID-19 pandemic period in Japan and assessed whether the pandemic influenced the adoption of hypofractionation. We obtained data for analysis from the National Database Open Data for fiscal years (FYs) 2014 to 2023. For the 5 years from FY2019 to FY2023, with detailed monthly data available, we used interrupted time series (ITS) analysis to examine changes in the level and slope of claims at the boundaries of the baseline, pandemic and post-pandemic periods. During the 10-year study period, the number of radiotherapy claims increased by an average of 1.6% per year. In FY2020, the peak of the COVID-19 pandemic, the number of radiotherapy claims decreased by 2.0% compared to the previous year. The number of claims for extra fees for hypofractionated radiotherapy for breast and prostate cancer showed a steady increase, except for a temporary decline around the April 2022 policy change in payment requirements for prostate cancer. In the ITS analysis, there were no significant changes in the level and slope of claims for radiotherapy and extra fees for hypofractionated radiotherapy at the onset of the pandemic. In conclusion, the impact of the COVID-19 pandemic on the utilization of radiotherapy in Japan was minimal, and the use of hypofractionated radiotherapy showed a steady increase throughout this period.

The role of the Certified Nurse in Radiation Oncology nursing (CN-RO) has expanded to include support for ensuring treatment reproducibility and minimizing medical radiation exposure through radiation protection measures. In hypofractionated radiotherapy for prostate cancer, in which consistent pretreatment bladder volume is more critical than in conventional fractionation, whether CN-RO intervention contributes to bladder volume reproducibility and reduction of cone-beam computed tomography (CBCT) frequency, lowering radiation exposure, was investigated. Sixty prostate cancer patients undergoing hypofractionated radiotherapy (51.6 Gy in 12 fractions) were retrospectively analyzed. Twenty patients received CN-RO intervention (Current Intervention (CI) group), which involved dehydration risk assessment and bladder volume guidance using a handheld bladder ultrasound scanner from the first session. Forty patients received no such intervention (Previous Intervention (PI) group). Bladder volume reproducibility, calculated as treatment bladder volume divided by planning bladder volume, and the number of CBCT scans were compared between the groups. The target was to achieve ≥70% reproducibility and to initiate treatment with the first CBCT scan in all sessions. There was no significant difference in bladder volume at treatment planning between the groups (P = 0.851). Mean bladder volume reproducibility was significantly higher in the CI group (96.5 ± 12.0%) than in the PI group (86.9 ± 14.2%, P = 0.022). Treatment was initiated after the first CBCT scan in 95.4% of sessions in the CI group (229/240), compared with 80.0% in the PI group (384/480, P < 0.001). These results suggest that CN-RO intervention enhances bladder volume reproducibility and contributes to reduced radiation exposure through fewer CBCT scans.

The purpose of this study was to design a radiogenomics machine learning-DeepSurv model for biochemical recurrence-free (BCR-free) survival and treatment response (TR) prediction for radiotherapy (RT) of prostate cancer (PCa). In this study, radiomic features were extracted from pre and post treatment multiparametric MRI (mpMRI), including T2-weighted (T2W), diffusion-weighted MR imaging (DWI) and apparent diffusion coefficient (ADC). Also, genomic biomarkers such as Ki-67 (a cell proliferation marker reflecting tumor growth activity and also prognostic information in cancer progression), PTEN (tumor suppressor gene regulating cell growth and survival, have a prominent role for TR and cancer progression) and Decipher (a genomic signature predicting cancer recurrence risk and TR based on gene expression patterns) were collected. Radiomics feature selection and dimensionality reduction methods were employed, followed by training machine learning (ML) models. Moreover, time to event data and survival models including Random Survival Forest (RSF) and DeepSurv neural networks were used. For model performance, the concordance index (C-index) and integrated Brier score (IBS), and for improving interpretability, the SHapley Additive exPlanations (SHAP) were applied. Radiomic feature of MRI including Kurtosis demonstrated a near-perfect positive correlation with Ki-67 expression (r = 0.64), however skewness showed a strong negative correlation with PTEN status (r = -0.88). Entropy and kurtosis of MRI were also highly correlated with the Decipher genomic risk score (r = 0.90 and r = -0.96, respectively). The integrated ML-DeepSurve model performance overall F1-score was 0.93 for TR. The model also offered robust stratification for patients based on BCR-free survival probability. Our findings underscore the potential of radiogenomic signatures as non-invasive biomarkers to personalized PCa RT decisions and provide a novel clinically explainable predictive model based on radiomic and molecular biomarkers for BCR-free survival and TR of mentioned cancer.