Objective:To achieve the conversion from dual-energy cone-beam CT (DECBCT) at the kilovolt (KV) level to projections at the megavolt (MV) level using an improved CycleGAN network, in order to provide a potential reference benchmark and real-time monitoring of in vivo doses delivered by exit beams for the safe implementation of advanced techniques such as online adaptive radiotherapy. Methods:Simulated patient data were generated using a 4D extended cardiac torso (XCAT) model, and projections were generated based on the geometric parameters of Varian′s onboard cone-beam CT. Furthermore, relative electron density (RED) images were derived from DECBCT images using an iterative dual-energy decomposition algorithm. The SE-CycleGAN and CycleGAN networks were trained to generate MV projection images using DECBCT projections and RED images, respectively. The performance of both methods was evaluated using metrics including structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and root mean square error (RMSE).Results:SE-CycleGAN significantly outperformed CycleGAN in all evaluation metrics ( Z = -23.92, -26.17, -25.54, -26.80, -11.54, -11.21, P<0.05), particularly in learning global information. Besides, although both methods generated satisfactory MV projections, training using DECBCT projections as input yielded better effects than training using RED images. For all the 3 636 sets of projections in the test set, the SE-CycleGAN and CycleGAN networks using DECBCT projections as input respectively yielded SSIMs of 0.997 7±0.000 7 and 0.997 1±0.001 6, PSNRs of 39.625 0±4.684 4 and 36.272 2±5.566 3, and RMSEs of 0.004 1±0.002 7 and 0.006 3±0.0043, respectively. In contrast, the SE-CycleGAN and CycleGAN networks using RED projections as input respectively yielded SSIMs of 0.996 8±0.001 0 and 0.996 2±0.001 5, PSNRs of 38.548 7±3.637 4 and 36.007 3±4.437 8, and RMSEs of 0.004 3±0.002 2 and 0.006 1±0.0037, respectively. Conclusions:This study proposed a new method to establish reference benchmarks for in vivo dose monitoring based on DECBCT and deep learning technologies. This method is accurate and effective according to the preliminary validation using virtual simulation experiments.

Objective:To apply statistical process control (SPC) techniques to the quality assurance of non-normal radiotherapy plans through Johnson transformation, establishing patient-specific tolerance and action limits based on treatment sites and dose/distance assessment criteria, thereby enhancing the intensity-modulated radiation therapy (IMRT) verification accuracy and dose delivery precision.Methods:In this study, 951 gamma analysis data of patient-specific quality assurance (PSQA) executed on the Halcyon accelerator platform were selected and categorized into six groups based on treatment sites, including brain (102 cases), head and neck (100 cases), breast (229 cases), lung (154 cases), esophagus (223 cases), and pelvic (143 cases) groups. The six groups of data were statistically analyzed through Anderson-Darling normality tests ( α = 0.05) using Minitab 21 software. Non-normal data were transformed into normal data through Johnson transformation and then were used to establish treatment site-specific tolerance and action limits, which were compared with the Shewhart control charts based on normal distributions. Results:The PSQA result of the six groups all exhibited non-normal distributions ( P < 0.05). Through Johnson transformation, the tolerance and action limits for the head and neck, breast, lung, esophagus, and pelvic areas under the 3%/2 mm criterion ranged from 95.13% to 96.16% and 94.19% to 95.91%, respectively. In contrast, the tolerance and action limits ranged from 91.15% to 94.86% and 89.94% to 94.78% under the 2%/2 mm criterion. Directly applying Shewhart control charts without normality assumptions yielded higher tolerance limits compared to the application of Johnson transformation, increasing the false positive rate in the non-normal PSQA process. Conclusions:Applying the SPC techniques directly to a non-normal process can lead to an increased false alarm rate and wrong process interpretation. The SPC techniques combined with Johnson transformation enable more effective monitoring of a non-normal PSQA process, facilitating timely identification of potential factors that may lead to an out-of-control process based on the treatment site-specific limits.

Objective:To achieve the conversion from dual-energy cone-beam CT (DECBCT) at the kilovolt (KV) level to projections at the megavolt (MV) level using an improved CycleGAN network, in order to provide a potential reference benchmark and real-time monitoring of in vivo doses delivered by exit beams for the safe implementation of advanced techniques such as online adaptive radiotherapy. Methods:Simulated patient data were generated using a 4D extended cardiac torso (XCAT) model, and projections were generated based on the geometric parameters of Varian′s onboard cone-beam CT. Furthermore, relative electron density (RED) images were derived from DECBCT images using an iterative dual-energy decomposition algorithm. The SE-CycleGAN and CycleGAN networks were trained to generate MV projection images using DECBCT projections and RED images, respectively. The performance of both methods was evaluated using metrics including structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and root mean square error (RMSE).Results:SE-CycleGAN significantly outperformed CycleGAN in all evaluation metrics ( Z = -23.92, -26.17, -25.54, -26.80, -11.54, -11.21, P<0.05), particularly in learning global information. Besides, although both methods generated satisfactory MV projections, training using DECBCT projections as input yielded better effects than training using RED images. For all the 3 636 sets of projections in the test set, the SE-CycleGAN and CycleGAN networks using DECBCT projections as input respectively yielded SSIMs of 0.997 7±0.000 7 and 0.997 1±0.001 6, PSNRs of 39.625 0±4.684 4 and 36.272 2±5.566 3, and RMSEs of 0.004 1±0.002 7 and 0.006 3±0.0043, respectively. In contrast, the SE-CycleGAN and CycleGAN networks using RED projections as input respectively yielded SSIMs of 0.996 8±0.001 0 and 0.996 2±0.001 5, PSNRs of 38.548 7±3.637 4 and 36.007 3±4.437 8, and RMSEs of 0.004 3±0.002 2 and 0.006 1±0.0037, respectively. Conclusions:This study proposed a new method to establish reference benchmarks for in vivo dose monitoring based on DECBCT and deep learning technologies. This method is accurate and effective according to the preliminary validation using virtual simulation experiments.

Objective:To apply statistical process control (SPC) techniques to the quality assurance of non-normal radiotherapy plans through Johnson transformation, establishing patient-specific tolerance and action limits based on treatment sites and dose/distance assessment criteria, thereby enhancing the intensity-modulated radiation therapy (IMRT) verification accuracy and dose delivery precision.Methods:In this study, 951 gamma analysis data of patient-specific quality assurance (PSQA) executed on the Halcyon accelerator platform were selected and categorized into six groups based on treatment sites, including brain (102 cases), head and neck (100 cases), breast (229 cases), lung (154 cases), esophagus (223 cases), and pelvic (143 cases) groups. The six groups of data were statistically analyzed through Anderson-Darling normality tests ( α = 0.05) using Minitab 21 software. Non-normal data were transformed into normal data through Johnson transformation and then were used to establish treatment site-specific tolerance and action limits, which were compared with the Shewhart control charts based on normal distributions. Results:The PSQA result of the six groups all exhibited non-normal distributions ( P < 0.05). Through Johnson transformation, the tolerance and action limits for the head and neck, breast, lung, esophagus, and pelvic areas under the 3%/2 mm criterion ranged from 95.13% to 96.16% and 94.19% to 95.91%, respectively. In contrast, the tolerance and action limits ranged from 91.15% to 94.86% and 89.94% to 94.78% under the 2%/2 mm criterion. Directly applying Shewhart control charts without normality assumptions yielded higher tolerance limits compared to the application of Johnson transformation, increasing the false positive rate in the non-normal PSQA process. Conclusions:Applying the SPC techniques directly to a non-normal process can lead to an increased false alarm rate and wrong process interpretation. The SPC techniques combined with Johnson transformation enable more effective monitoring of a non-normal PSQA process, facilitating timely identification of potential factors that may lead to an out-of-control process based on the treatment site-specific limits.

Objective:To investigate the effects of Juglone on the apoptosis of osteosarcoma(OS)cells(U2OS and MG63 cells)through the cysteinyl aspartate specific proteinase-3(Caspase-3)/gasdermin E(GSDME)-mediated pyroptosis pathway.Methods:The U2OS and MG63 cells were cultured in vitro and divided into control group,different concentrations(5,10 and 20 μmol·L-1)of Juglone groups and Caspase-3 inhibitor Z-DEVD-FMK group(10 μmol·L-1 Juglone+30 μmol·L-1 Z-DEVD-FMK).The survival rates of cells in various groups were assessed by cell counting kit-8(CCK-8)assay,and the apoptotic rates were detected by flow cytometry.Lactate dehydrogenase(LDH)release assay was used to measure the release rates of LDH from the cells.Western blotting method was used to detect the expression levels of apoptosis-related proteins including B-cell lymphoma-2(Bcl-2),Bcl-2-associated X protein(Bax),cleaved-Caspase-3 and poly(ADP-ribose)polymerase(PARP)and pyroptosis-related proteins including GSDME full form(GSDME-F)and GSDME N-terminal(GSDME-N).The levels of interleukin-1β(IL-1β)and interleukin-18(IL-18)in the cell supernataut in various groups were measured by enzyme-linked immunosorbent assay(ELISA)method.Results:Compared with control group,the survival rates of cells in 5,10,and 20 μmol·L-1Juglone groups were significantly decreased(P＜0.05 or P＜0.01),and the 50％inhibitory concentration(IC50)values of U2OS cells and MG63 cells were 8.4 and 10.2 μmol·L-1,respectively.Compared with control group,the apoptotic rates and LDH release rates of U2OS and MG63 cells in 5 and 10 μmol·L-1Juglone groups were significantly increased(P＜0.05 or P＜0.01).Compared with control group,the expression levels of Bax,cleaved-Caspase-3,and cleaved-PARP proteins in 5 and 10 μmol·L-1 Juglone groups were significantly increased(P＜0.01),while the expression levels of Bcl-2 protein were significantly decreased(P＜0.01).Compared with control group,the levels of IL-1β and IL-18 in cell supernatant in 5 and 10 μmol·L-1Juglone groups were increased(P＜0.01).Compared with control group,the expression levels of cleaved-Caspase-3 and GSDME-N proteins in 5 and 10 μmol·L-1 Juglone groups were significantly increased(P＜0.01),while there was no difference in the expression level of GSDME-F protein(P＞0.05).Compared with 10 μmol·L-1 Juglone group,the expression levels of cleaved-Caspase-3 and GSDME-N in Z-DEVD-FMK group were significantly decreased(P＜0.01),while there was no difference in the expression level of GSDME-F protein(P＞0.05).Conclusion:Juglone can induce the apoptosis of U2OS and MG63 cells and cause the Caspase-3/GSDME-mediated pyroptosis.

Objective To propose and validate a decomposition method based on half-projection reconstruction for dual-energy cone beam CT(DE CBCT),thereby providing a potentially feasible low-dose imaging solution for anatomical monitoring and dose reconstruction optimization in adaptive radiotherapy.Methods Dual-energy scans were performed on a Gammex phantom using the on-board kilovoltage CBCT system of a VitalBeam accelerator at acquisition frame rates of 15 and 7 frames per second(f/s).Images were reconstructed from the projection data,and dual-energy decomposition was applied to the 7 f/s dual-energy images to derive relative electron density(RED)and stopping power ratio(SPR)using weighted formulas and empirical functions,followed by accuracy evaluation.Additionally,the weighted CT dose index was calculated for different scanning parameters.Results Dual-energy decomposition effectively suppressed image artifacts,with RED and SPR errors remaining below 2.82%and 2.56%,respectively.Compared with the traditional dual-scan method which required high-and low-energy acquisitions,the weighted CT dose index of the half-projection DE CBCT was reduced by 11.60 mGy(a 52.90%reduction).Furthermore,it was 2.58 mGy lower than the dose of the full-projection high-energy CBCT alone(a 19.98%reduction)and only 1.31 mGy higher than that of the low-energy CBCT(a 14.52%increase).Conclusion The proposed method effectively suppresses image artifacts while maintaining high accuracy in RED and SPR under low radiation dose conditions,demonstrating its potential value for scenarios requiring frequent image guidance,such as adaptive radiotherapy.

Background: Curcumin, the main yellow pigment in turmeric, is a potent anticancer agent. However, its effect on the viability of human prostate cancer (PCa) cells and underlying mechanisms remain unclear. This study aimed to determine the effects of curcumin on the proliferation and glucose metabolism of PCa cells. Methods: Cell viability was measured by MTS assay, and apoptosis was measured by flow cytometry. Glucose metabolism was assessed by measuring glucose intake, lactate production, and adenosine triphosphate content. Western blotting was performed to detect the expression of apoptosis-related proteins. Results: Curcumin treatment significantly reduced the viability of two types of PCa cells. We also found that curcumin increased apoptosis and glycolysis by inhibiting the activities of phosphatidylinositol 3-kinase/protein kinase B and hypoxia-inducible factor-1α. Furthermore, curcumin reduced the expression of ETS-related gene (ERG). However, after the ERG was knocked out, the effects of curcumin treatment were attenuated. Conclusion This study investigated the effects of curcumin on the proliferation and apoptosis of PCa cells, which may be related to the inhibition of glycolysis, and further explored the pathway involved. The subsequent effect on ERG expression indicated that these effects may be related to this oncogene.

Objective To propose and validate a decomposition method based on half-projection reconstruction for dual-energy cone beam CT(DE CBCT),thereby providing a potentially feasible low-dose imaging solution for anatomical monitoring and dose reconstruction optimization in adaptive radiotherapy.Methods Dual-energy scans were performed on a Gammex phantom using the on-board kilovoltage CBCT system of a VitalBeam accelerator at acquisition frame rates of 15 and 7 frames per second(f/s).Images were reconstructed from the projection data,and dual-energy decomposition was applied to the 7 f/s dual-energy images to derive relative electron density(RED)and stopping power ratio(SPR)using weighted formulas and empirical functions,followed by accuracy evaluation.Additionally,the weighted CT dose index was calculated for different scanning parameters.Results Dual-energy decomposition effectively suppressed image artifacts,with RED and SPR errors remaining below 2.82%and 2.56%,respectively.Compared with the traditional dual-scan method which required high-and low-energy acquisitions,the weighted CT dose index of the half-projection DE CBCT was reduced by 11.60 mGy(a 52.90%reduction).Furthermore,it was 2.58 mGy lower than the dose of the full-projection high-energy CBCT alone(a 19.98%reduction)and only 1.31 mGy higher than that of the low-energy CBCT(a 14.52%increase).Conclusion The proposed method effectively suppresses image artifacts while maintaining high accuracy in RED and SPR under low radiation dose conditions,demonstrating its potential value for scenarios requiring frequent image guidance,such as adaptive radiotherapy.

Objective To investigate the therapeutic effects of bone marrow mesenchymal stem cells (BMSCs) for radiation-induced lung injury (RILI) and the underlying mechanism. Methods Forty-five healthy adult male C57BL/6 mice were randomly divided into control, model, and BMSCs groups. The model and BMSCs groups received a single irradiation dose of 20 Gy to the chest, while the control group did not receive X-ray irradiation. For the BMSCs group, an injection of 1 × 10⁶ BMSCs cells was administered via the tail vein within 6 h after irradiation. In the 5th week, the lung tissue was taken to observe pathological changes with HE staining; examine the expression of the inflammatory factors interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) with immunohistochemical staining; observe the polarization of macrophages with immunofluorescence staining; and measure the expression of the epithelial-mesenchymal transition markers E-cadherin, N-cadherin, and vimentin proteins by Western blot. Results After radiation, the model group developed pulmonary vasodilation and congestion with septal thickening and inflammatory cell infiltration, and these changes were markedly reduced in the BMSCs group. The model group showed significantly down-regulated expression of IL-6 and TNF-α compared with significantly increased levels in the model group (P < 0.01, P < 0.05). Treatment with BMSCs significantly increased the polarization of lung macrophages towards the M2 type, while significantly decreasing the abnormally increased N-cadherin and vimentin levels in RILI mice (P < 0.05, P < 0.01). Conclusion BMSCs have therapeutic effects for RILI mice, which may be through promoting macrophage polarization from M1 to M2.