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Recently, ultra-high dose rate (> 40 Gy/s, uHDR; FLASH) radiation therapy (RT) has attracted interest, because the FLASH effect that is, while a cell-killing effect on cancer cells remains, the damage to normal tissue could be spared has been reported. This study aimed to compare the immune-related protein expression on cancer cells after γ-ray, conventionally used dose rate (Conv) carbon ion (C-ion), and uHDR C-ion. B16F10 murine melanoma and Pan02 murine pancreas cancer were irradiated with γ-ray at Osaka University and with C-ion at Osaka HIMAK. The dose rates at 1.16 Gy/s for Conv and 380 Gy/s for uHDR irradiation. The expressed calreticulin (CRT), major histocompatibility complex class (MHC)-I, and programmed cell death 1 ligand (PD-L1) were evaluated by flow cytometry. Western blotting and PCR were utilized to evaluate endoplasmic reticulum (ER) stress, DNA damage, and its repair pathway. CRT, MHC-I on B16F10 was also increased by irradiation, while only C-ion increased MHC-I on Pan02. Notably, PD-L1 on B16F10 was increased after irradiation with both γ-ray and C-ion, while uHDR C-ion suppressed the expression of PD-L1 on Pan02. The present study indicated that uHDR C-ion has a different impact on the repair pathway of DNA damage and ER than the Conv C-ion. This is the first study to show the immune-related protein expressions on cancer cells after uHDR C-ion irradiation.

High dose rate (HDR) intracavitary brachytherapy (ICBT) with a remote afterloading system plays a vital role in the treatment of cervical cancer. We aimed to develop a new verification system for ICBT for cervical cancer and evaluate the feasibility for clinical plans (PlanClin) generated for different remote afterloaders, applicators and treatment techniques. In total, 517 PlansClin of patients were treated with Elekta 192Ir microSelectron HDR v2r. Reference plans (PlanRef) were generated for the ICBT applicators. An equation to predict total dwell time (Tdwell) of PlanClin was generated by evaluating the relationship between the volume receiving 100% of the prescribed dose (V100%) and the Tdwell. We also developed software to detect human errors in PlanClin by comparing parameters, including applicator and reference point geometries, dwell position and weight patterns and reference point dose, with those of PlanRef. Feasibility was evaluated for 83 PlanClin cases treated with the Elekta Flexitron remote afterloader and six ICBT plans with extra catheters (hybrid BT). The linear fitting function showed good agreement with the correlation between V100% and Tdwell. The developed equation accurately estimated the Tdwell of the PlanClin treated with the Flexitron with an accuracy of 0.26 ± 0.49%. Our system successfully detected intentional human errors including incorrect channel mapping, applicator tip offset, incorrect plan templates, an applicator digitization model and incorrect reference points. A verification system based on PlanRef and a statistical approach is feasible for the new remote afterloaders, applicators and hybrid BT techniques. This system contributes to the implementation of safe treatments.

No classification methods to predict prognosis after carbon‐ion radiotherapy for hepatocellular carcinoma have yet been reported. This study aimed to develop risk classification for cancer‐specific survival (CSS) after carbon‐ion radiotherapy for hepatocellular carcinoma using decision tree analysis as a data‐mining method. In this single‐center, retrospective study, we analyzed 90 consecutive patients with hepatocellular carcinoma treated with carbon‐ion radiotherapy between 2018 and 2022. Liver tumors were irradiated at 60 Gy (relative biological effectiveness [RBE]) in four fractions. If the tumor was close to the gastrointestinal tract, it was irradiated at 60 Gy [RBE] in 12 fractions. Univariate and multivariate analyses of progression‐free survival (PFS) and CSS were performed to assess patients' background and treatment‐related factors. Decision tree analysis (DTA) was performed to assess prognostic factors for CSS that were significantly different in the multivariate analysis. The median follow‐up period was 32.8 months for all patients and 35.6 months for survivors. Multivariate analysis identified dose fractionation and pretreatment alpha‐fetoprotein values as significant prognostic factors for PFS and CSS. Moreover, clinical stage and pretreatment protein induced by vitamin K absence or antagonist ΙΙ values were significant prognostic factors for CSS. DTA revealed that the patients could be divided into three groups according to prognosis: low‐risk, high‐risk, and intermediate‐risk. Consequently, the 3‐year CSS rates for the low‐, intermediate‐, and high‐risk groups were 100%, 73.3%, and 44.4%, respectively. DTA represents a new method for risk classification for CSS after carbon‐ion radiotherapy for hepatocellular carcinoma based on tumor markers and clinical stage. First study to use decision tree analysis for predicting cancer‐specific survival after carbon‐ion radiotherapy for hepatocellular carcinoma. Decision tree model offers clear, patient‐friendly prognosis visualization.

The current monochromatic beam mode (i.e., uHDR irradiation mode) of the scanned carbon-ion beam lacks a dedicated dose monitor, making the beam control challenging. We developed and characterized a dedicated dose monitor for uHDR-scanned carbon-ion beams. Furthermore, a simple measurable dose rate (dose rate per spot (DR spot )) was suggested by using the developed dose monitor and experimentally validating quantities relevant to the uHDR scanned carbon-ion beam. A large plane-parallel ionization chamber (IC) with a smaller electrode spacing was used to reduce uHDR recombination effects, and a dedicated operational amplifier was manufactured for the uHDR-scanned carbon-ion beam. The dose linearity of the IC was within ± 1% in the range of 1.8–12.3 Gy. The spatial inhomogeneity of the dose response of the IC was ± 0.38% inside the ± 40-mm detector area, and a systematic deviation of approximately 2% was measured at the edge of the detector. uHDR irradiation with beam scanning was tested and verified for different doses at the corresponding dose rates (in terms of both the average dose rate and DR spot ). We confirmed that the dose monitor can highlight the characteristics (i.e., dose, dose rate, and dose profile) of uHDR-scanned carbon-ion beams at several dose levels in the monochromatic beam mode.

A proton beam therapy (PBT) system has been designed which dedicates to spot-scanning and has a gating function employing the fluoroscopy-based real-time-imaging of internal fiducial markers near tumors. The dose distribution and treatment time of the newly designed real-time-image gated, spot-scanning proton beam therapy (RGPT) were compared with free-breathing spot-scanning proton beam therapy (FBPT) in a simulation. In-house simulation tools and treatment planning system VQA (Hitachi, Ltd., Japan) were used for estimating the dose distribution and treatment time. Simulations were performed for 48 motion parameters (including 8 respiratory patterns and 6 initial breathing timings) on CT data from two patients, A and B, with hepatocellular carcinoma and with clinical target volumes 14.6 cc and 63.1 cc. The respiratory patterns were derived from the actual trajectory of internal fiducial markers taken in X-ray real-time tumor-tracking radiotherapy (RTRT). With FBPT, 9/48 motion parameters achieved the criteria of successful delivery for patient A and 0/48 for B. With RGPT 48/48 and 42/48 achieved the criteria. Compared with FBPT, the mean liver dose was smaller with RGPT with statistical significance (p<0.001); it decreased from 27% to 13% and 28% to 23% of the prescribed doses for patients A and B, respectively. The relative lengthening of treatment time to administer 3 Gy (RBE) was estimated to be 1.22 (RGPT/FBPT: 138 s/113 s) and 1.72 (207 s/120 s) for patients A and B, respectively. This simulation study demonstrated that the RGPT was able to improve the dose distribution markedly for moving tumors without very large treatment time extension. The proton beam therapy system dedicated to spot-scanning with a gating function for real-time imaging increases accuracy with moving tumors and reduces the physical size, and subsequently the cost of the equipment as well as of the building housing the equipment.

Compared to conventional X-ray therapy, proton beam therapy (PBT) has more clinical and physical advantages such as irradiation dose reduction to normal tissues for pediatric medulloblastoma. However, PBT is expensive. We aimed to compare the cost-effectiveness of PBT for pediatric medulloblastoma with that of conventional X-ray therapy, while focusing on radiation-induced secondary cancers, which are rare, serious and negatively affect a patient’s quality of life (QOL). Based on a systematic review, a decision tree model was used for the cost-effectiveness analysis. This analysis was performed from the perspective of health care payers; the cost was estimated from medical fees. The target population was pediatric patients with medulloblastoma below 14 years old. The time horizon was set at 7.7 years after medulloblastoma treatment. The primary outcome was the incremental cost-effectiveness ratio (ICER), which was defined as the ratio of the difference in cost and lifetime attributable risk (LAR) between conventional X-ray therapy and PBT. The discount rate was set at 2% annually. Sensitivity analyses were performed to model uncertainty. Cost and LAR in conventional X-ray therapy and PBT were Japanese yen (JPY) 1 067 608 and JPY 2436061 and 42% and 7%, respectively. The ICER was JPY 3856398/LAR. In conclusion, PBT is more cost-effective than conventional X-ray therapy in reducing the risk of radiation-induced secondary cancers in pediatric medulloblastoma. Thus, our constructed ICER using LAR is one of the valid indicators for cost-effectiveness analysis in radiation-induced secondary cancer.

Currently, treatment planning systems (TPSs) that can compute the intensities of intensity-modulated carbon-ion therapy (IMCT) using scanned carbon-ion beams are limited. In the present study, the computational efficacy of the newly designed IMCT algorithms was analyzed for the first time based on the mixed beam model with respect to the physical and biological doses; moreover, the validity and effectiveness of the robust radiobiological optimization were verified. A dose calculation engine was independently generated to validate a clinical dose determined in the TPS. A biological assay was performed using the HSGc-C5 cell line to validate the calculated surviving fraction (SF). Both spot control (SC) and voxel-wise worst-case scenario (WC) algorithms were employed for robust radiobiological optimization followed by their application in a Radiation Therapy Oncology Group benchmark phantom under homogeneous and heterogeneous conditions and a clinical case for range and position errors. Importantly, for the first time, both SC and WC algorithms were implemented in the integrated TPS platform that can compute the intensities of IMCT using scanned carbon-ion beams for robust radiobiological optimization. For assessing the robustness, the difference between the maximum and minimum values of a dose–volume histogram index in the examined error scenarios was considered as a robustness index. The relative biological effectiveness (RBE) determined by the independent dose calculation engine exhibited a −0.6% difference compared with the RBE defined by the TPS at the isocenter, whereas the measured and the calculated SF were similar. Regardless of the objects, compared with the conventional IMCT, the robust radiobiological optimization enhanced the sensitivity of the examined error scenarios by up to 19% for the robustness index. The computational efficacy of the novel IMCT algorithms was verified according to the mixed beam model with respect to the physical and biological doses. The robust radiobiological optimizations lowered the impact of range and position uncertainties considerably in the examined scenarios. The robustness of the WC algorithm was more enhanced compared with that of the SC algorithm. Nevertheless, the SC algorithm can be used as an alternative to the WC IMCT algorithm with respect to the computational cost.

Few reports have documented how the accuracy of stopping power ratio (SPR) prediction for porous bone tissue affects the dose distribution of scanned carbon-ion beam therapy. The estimated SPR based on single-energy computed tomography (SECT) and dual-energy CT (DECT) were compared for the femur of a Rando phantom which simulates the porosity of human bone, NEOBONE which is the hydroxyapatite synthetic bone substitute, and soft tissue samples. Dose differences between SECT and DECT were evaluated for a scanned carbon-ion therapy treatment plan for the Rando phantom. The difference in the water equivalent length was measured to extract the SPR of the examined samples. The differences for SPR estimated from the DECT-SPR conversion were small with − 1.8% and − 3.3% for the Rando phantom femur and NEOBONE, respectively, whereas the differences for SECT-SPR were between 7.6 and 70.7%, illustrating a 1.5-mm shift of the range and a dose difference of 13.3% at maximum point in the evaluation of the dose distribution. This study demonstrated that the DECT-SPR conversion method better estimated the SPR of the porosity of bone tissues than SECT-SPR followed by the accurate range of the carbon-ion beams on carbon-ion dose calculations.

In urethra-sparing radiation therapy, prostatic urinary tract visualization is important in decreasing the urinary side effect. A methodology has been developed to visualize the prostatic urinary tract using post-urination magnetic resonance imaging (PU-MRI) without a urethral catheter. This study investigated whether the combination of PU-MRI and super-resolution (SR) deep learning models improves the visibility of the prostatic urinary tract. We enrolled 30 patients who had previously undergone real-time-image-gated spot scanning proton therapy by insertion of fiducial markers. PU-MRI was performed using a non-contrast high-resolution two-dimensional T2-weighted turbo spin-echo imaging sequence. Four different SR deep learning models were used: the enhanced deep SR network (EDSR), widely activated SR network (WDSR), SR generative adversarial network (SRGAN), and residual dense network (RDN). The complex wavelet structural similarity index measure (CW-SSIM) was used to quantitatively assess the performance of the proposed SR images compared to PU-MRI. Two radiation oncologists used a 1-to-5 scale to subjectively evaluate the visibility of the prostatic urinary tract. Cohen’s weighted kappa (k) was used as a measure of agreement of inter-operator reliability. The mean CW-SSIM in EDSR, WDSR, SRGAN, and RDN was 99.86%, 99.89%, 99.30%, and 99.67%, respectively. The mean prostatic urinary tract visibility scores of the radiation oncologists were 3.70 and 3.53 for PU-MRI (k = 0.93), 3.67 and 2.70 for EDSR (k = 0.89), 3.70 and 2.73 for WDSR (k = 0.88), 3.67 and 2.73 for SRGAN (k = 0.88), and 4.37 and 3.73 for RDN (k = 0.93), respectively. The results suggest that SR images using RDN are similar to the original images, and the SR deep learning models subjectively improve the visibility of the prostatic urinary tract.

Intensity-modulated radiation therapy (IMRT) uses intensity-modulated photon beams from multiple directions to achieve conformal dose delivery to a target with a complex shape while reducing the dose to organs at risk. We analyzed the trends in IMRT utilization rates across Japanese prefectures from 2015 to 2019 and investigated their relationship with medical resources. Data from the National Database of Health Insurance Claims and the Japanese Society for Radiation Oncology Structure Survey were analyzed. IMRT utilization rates and medical resources (radiation oncologists, medical physicists, radiation technologists, and IMRT-capable linear accelerators) were assessed for all 47 prefectures. A mixed-model analysis was employed to examine the relationship between IMRT utilization rates and medical resources. IMRT utilization increased from 16.4% in 2015 to 22.0% in 2019, with significant regional disparities (range, <10% to >30%). Mixed-model analysis revealed that the number of IMRT-capable linear accelerators (estimate = 0.073, P < 0.01) and radiation oncologists (estimate = 0.032, P = 0.04) was significantly associated with higher IMRT utilization rates. Medical physicists and radiation technologists showed no significant association with IMRT utilization rates. Although the use of IMRT has increased in Japan, substantial regional disparities persist. Increasing the number of IMRT-capable linear accelerators and radiation oncologists may be the most effective strategy to improve equitable access to IMRT in Japan.