Objective:To explore the dosimetry optimization strategy based on filter thickness and shape selection for the bulb superficial X-ray radiotherapy unit.Methods:Monte Carlo code TOPAS was used to model tubular equipment, and the dose distribution from six X-ray energies (50-150 kV) and five conventional aluminum filters (0.5-3.0 mm) with different thickness were simulated in the water model. The percentage depth dose (PDD) curve along the central axis, the center-axis profile dose at different depths, and the lateral dose distribution were analyzed. The dose distribution of three different designs of aluminum filters (conventional cylindrical, conical and oblique cylindrical filters) was compared to evaluate the effect of dosimetric optimization of different filter shapes.Results:Under the same energy, increasing the thickness of the filter can optimize the superficial skin dose, and the optimization effect of depth dose uniformity can be increased by 26% at a depth of 5.5 mm at 70 kV energy. The raised, flat and inclined dose distribution modes can be achieved by using conventional cylindrical, conical and inclined aluminum filters.Conclusions:By selecting the appropriate X-ray energy and filter thickness, an ideal dose distribution matching the tumor depth can be achieved. The application of personalized filters is also of great significance for diverse target areas.

Objective To develop a deep learning-based denoising model for accelerating Monte Carlo(MC)simulation of electronic portal imaging device(EPID)transit dose images.Methods A total of 500 EPID fields were collected from 100 lung cancer patients undergoing 5-field intensity-modulated radiotherapy,with 400 fields randomly selected as training set,50 fields as validation set,and 50 fields as test set.EPID transit dose image datasets with low particle counts(1×107)and high particle counts(1×109)were simulated using the GPU-accelerated MC dose calculation engine ARCHER.A denoising network model named SUNet was constructed based on Swin Transformer and U-Net,and trained using low-particle-count images as input and high-particle-count images as output.Following training,SUNet model was used to denoise low-particle-count EPID images in the test set.Denoising performance was evaluated using structural similarity index(SSIM),peak signal-to-noise ratio(PSNR),and Gamma passing rates(3%/2 mm),and the computational efficiency of MC simulation combined with SUNet model was analyzed.Results Compared with the original low-particle-count images,the SUNet-denoised images showed significantly improved quality,reduced noise points,and smoother dose distribution.When benchmarked against high-particle-count images,the SUNet-denoised images achieved an average SSIM greater than 0.9,an average PSNR higher than 32 dB,and an average gamma passing rate exceeding 90%.The MC simulation combined with SUNet model required only 1.88 s to simulate a single EPID transit dose image,representing an approximate 40-fold improvement in computational efficiency as compared with high-particle-count MC simulation.Conclusion The deep learning-based denoising model substantially accelerates MC simulation of EPID transit dose images while preserving both image quality and dose accuracy,which provides possibilities for EPID-basedin vivodose verification.

Objective:To explore the dosimetry optimization strategy based on filter thickness and shape selection for the bulb superficial X-ray radiotherapy unit.Methods:Monte Carlo code TOPAS was used to model tubular equipment, and the dose distribution from six X-ray energies (50-150 kV) and five conventional aluminum filters (0.5-3.0 mm) with different thickness were simulated in the water model. The percentage depth dose (PDD) curve along the central axis, the center-axis profile dose at different depths, and the lateral dose distribution were analyzed. The dose distribution of three different designs of aluminum filters (conventional cylindrical, conical and oblique cylindrical filters) was compared to evaluate the effect of dosimetric optimization of different filter shapes.Results:Under the same energy, increasing the thickness of the filter can optimize the superficial skin dose, and the optimization effect of depth dose uniformity can be increased by 26% at a depth of 5.5 mm at 70 kV energy. The raised, flat and inclined dose distribution modes can be achieved by using conventional cylindrical, conical and inclined aluminum filters.Conclusions:By selecting the appropriate X-ray energy and filter thickness, an ideal dose distribution matching the tumor depth can be achieved. The application of personalized filters is also of great significance for diverse target areas.

Objective To develop a deep learning-based denoising model for accelerating Monte Carlo(MC)simulation of electronic portal imaging device(EPID)transit dose images.Methods A total of 500 EPID fields were collected from 100 lung cancer patients undergoing 5-field intensity-modulated radiotherapy,with 400 fields randomly selected as training set,50 fields as validation set,and 50 fields as test set.EPID transit dose image datasets with low particle counts(1×107)and high particle counts(1×109)were simulated using the GPU-accelerated MC dose calculation engine ARCHER.A denoising network model named SUNet was constructed based on Swin Transformer and U-Net,and trained using low-particle-count images as input and high-particle-count images as output.Following training,SUNet model was used to denoise low-particle-count EPID images in the test set.Denoising performance was evaluated using structural similarity index(SSIM),peak signal-to-noise ratio(PSNR),and Gamma passing rates(3%/2 mm),and the computational efficiency of MC simulation combined with SUNet model was analyzed.Results Compared with the original low-particle-count images,the SUNet-denoised images showed significantly improved quality,reduced noise points,and smoother dose distribution.When benchmarked against high-particle-count images,the SUNet-denoised images achieved an average SSIM greater than 0.9,an average PSNR higher than 32 dB,and an average gamma passing rate exceeding 90%.The MC simulation combined with SUNet model required only 1.88 s to simulate a single EPID transit dose image,representing an approximate 40-fold improvement in computational efficiency as compared with high-particle-count MC simulation.Conclusion The deep learning-based denoising model substantially accelerates MC simulation of EPID transit dose images while preserving both image quality and dose accuracy,which provides possibilities for EPID-basedin vivodose verification.

Objective To investigate the therapeutic effect of transcutaneous auricular vagus nerve stimulation(taVNS)on overweight/obesity patients,and to explore its central mechanism.Methods Twenty-six overweight/obesity patients were randomly divided into two groups,12 cases in the taVNS test group(shortened as the taVNS group)and 14 cases in the lifestyle intervention control group(shortened as the control group).The patients in the control group were treated with online lifestyle intervention of calorie-restricted diet(CRD),and the patients in the taVNS group were treated with taVNS on the basis of the intervention for the control group.The taVNS was performed on unilateral acupoints of spleen and endocrine,twice(in the morning and at evening)per day,for five days a week.The treatment for the two groups covered four weeks.The obesity indicators such as body weight,body mass index(BMI)and waist circumference of the patients in the two groups were observed before and after treatment.Moreover,the resting-state cerebral functional magnetic resonance imaging(fMRI)data of the patients were collected after treatment,and then the regulatory effect of taVNS on the regional homogeneity(ReHo)of local cerebral area of the patients was observed.Results(1)During the trial,one case in each group dropped off,and a total of 24 patients(including 13 cases in the control group and 11 cases in the taVNS group)were finally included in the statistical analysis of the observation indicators.(2)After treatment,the body weight,BMI and waist circumference of patients in the taVNS group were decreased compared with those before treatment(P＜0.05),while the obesity indicators in the control group only showed a downward trend compared with those before treatment,the differences being not statistically significant(P＞0.05).The improvement of the obesity indicators of body weight,BMI,and waist circumference in the taVNS group was significantly superior to that in the control group,and there were statistically significant differences in the post-treatment indicators and in the pre-and post-treatment difference values of the indicators between the two groups(P＜0.05 or P＜0.01).(3)After treatment,the taVNS group had greater ReHo values in the left prefrontal lobe and medial frontal gyrus than the control group,and the control group had greater ReHo value in the right parietal lobe than the taVNS group,which indicated that compared with the control group,the ReHo of the left prefrontal lobe and medial frontal gyrus in the taVNS group was increased and the ReHo of the right parietal lobe was decreased(Pvoxel＜0.001,Pcluster＜0.05,corrected by FWE level).Conclusion As a non-invasive treatment method,taVNS exerts certain efficacy for the treatment of overweight/obesity patients.The central response mechanism for treatment of obesity is probably related with the modulation of taVNS on the functional areas of left prefrontal lobe,medial frontal gyrus,and right parietal lobe of the patients.

Objective To investigate the effects of DNA demethylation drugs combined with histone deacetylase in-hibitors on fragile X mental retardation 1 neighbor protein (FMR1NB) expression and its promoter methylation in human oral cancer cells and try to find a strategy of weakening the heterogeneity of FMR1NB expression.Methods Human oral cancer cell lines Cal27 and SCC-9 were treated with decitabine (DAC) , an inhibitor of DNA meth-yltransferase, combined with trichostatin A (TSA) and valproic acid (VPA), inhibitors of histone deacetylase.Then reverse transcription-polymerase chain reaction (RT-PCR) , quantitative real-time PCR (qRT-PCR) and Western blot were used to detect the expression of FMR1 NB and pyrosequencing was used to detect the methylation of FMR1NB promoter.Results Compared with the blank control group, DAC and its combination with TSA and VPA significantly induced the expression of FMR1NB mRNA and protein in Cal27 and SCC-9 cells.Compared with DAC alone group, FMR1NB mRNA expression of each DAC-combined drug groups significantly increased, but FMR1NB protein did not significantly change in Cal27 cells; for SCC-9 cells, except for DAC+TSA group, the mRNA and protein levels of FMR1NB significantly increased in all other groups.In addition, there was no signifi-cant difference in the expression of FMR1 NB mRNA and protein between the three-combined drugs group and two-combined drugs groups.Further methylation assay showed that the methylation level of the overall FMR1NB promot-er and its each CpG site measured were reduced to varying degrees in all treatment groups except for three-combina-tion drug group of SCC-9.Conclusion DAC and its combination with TSA and VPA can enhance the expression of FMR1NB by mediating the demethylation of FMR1NB promoter, wherein the enhanced expression effect of the com-bination of the two drugs is stronger, suggesting that they have the potential to weaken the heterogeneity of FMR1NB expression and improve the immunotherapy effect of oral cancer.

Objective To compare the biomechanical stability of three cross-bridge headless compression screws and lock-ing plates in the fixation of Mason type Ⅲ radial head fractures by finite element method.Methods Using reverse modeling technology,the radial CT data and internal fixation data of a healthy 25-year-old male were imported into the relevant software.Three-dimensional finite element model of 3 cross-bridge headless compression screws and locking plates for Mason Ⅲ radial head fractures were established,and the radial head was loaded with 100 N axial loading.The maximum displacement,maxi-mum Von Mises stress and stress distribution of the two groups were compared.Results The maximum displacements of the three cross-bridge screws group and locking plate group were 0.069 mm and 0.087 mm respectively,and the Von Mises stress peaks were 18.59 MPa and 31.85 MPa respectively.The stress distribution of the three screws group was more uniform.Con-clusion Both internal fixation methods can provide good fixation effect.CoMPared with the locking plate fixation method,the 3 cross-bridge headless compression screws fixation is more stable and the stress distribution is more uniform.

Objective:To evaluate the efficacy and safety of antaitasvir phosphate 100 mg or 200 mg combined with yiqibuvir for 12 weeks in patients with various genotypes of chronic hepatitis C, without cirrhosis or compensated stage cirrhosis.Methods:Patients with chronic hepatitis C (without cirrhosis or compensated stage cirrhosis) were randomly assigned to the antaitasvir phosphate 100 mg+yiqibuvir 600 mg group (100 mg group) or the antaitasvir phosphate 200 mg+yiqibuvir 600 mg group (200 mg group) in a 1∶1 ratio. The drugs were continuously administered once a day for 12 weeks and observed for 24 weeks after drug withdrawal. The drug safety profile was assessed concurrently with the observation of the sustained virological response (SVR12) in the two patient groups 12 weeks following the drug cessation. The intention-to-treat concept was used to define as closely as possible a full analysis set, including all randomized cases who received the experimental drug at least once. The safety set was collected from all subjects who received the experimental drug at least once (regardless of whether they participated in the randomization group) in this study. All efficacy endpoints and safety profile data were summarized using descriptive statistics. The primary efficacy endpoint was SVR12. The primary analysis was performed on a full analysis set. The frequency and proportion of cases were calculated in the experimental drug group (antaitasvir phosphate capsules combined with yiqibuvir tablets) that achieved "HCV RNA

Objective To develop a GPU-based Monte Carlo dose calculation module for helical tomotherapy(TOMO),and integrate it into the commercial software ArcherQA to achieve fast and accurate dose verification in clinic.Methods The TOMO treatment head was modeled using TOPAS to obtain phase space files,and a fast weight tuning algorithm was used to simulate particle transport in multi-leaf collimator for improving computational efficiency,and finally,GPU-based Monte Carlo algorithms in ArcherQA were used to simulate particle transport in patients.To verify the model accuracy,the ArcherQA calculated results in water tank were compared with measured data for different open fields.In addition,multiple comparisons among ArcherQA results,TPS results and ArcCHECK results were conducted on 15 clinical cases(5 cases in the head and neck,5 cases in the chest and abdomen,and 5 cases in the whole body).Results In the water tank tests for 40 cm×5.0 cm,40 cm×2.5 cm and 40 cm× 1.0 cm radiation fields,the average global relative errors of the percentage depth dose,transverse dose distribution,and longitudinal dose distribution calculated by ArcherQA with the corresponding measured values were 0.72％,0.66％,and 0.54％,respectively.Over 98％of the voxels had a global relative error of less than 1％.As for 15 clinical cases,in 2％/2 mm criteria,the mean Gamma passing rate was 98.1％between ArcherQA and TPS,99.1％between TPS and ArcCHECK,and 99.4％between ArcherQA and ArcCHECK.The uncertainty of the simulation maintained less than 1％,and the average time taken for calculation based on patient CT vs ArcCHECK phantom was 87 s vs 64 s.Conclusion ArcherQA can be used for independent dose validation for TOMO plans for it can provide fast and accurate dose calculations.

Objective: To examine the safety and effectiveness of inflatable video-assisted mediastinoscopic transhiatal esophagectomy (IVMTE). Methods: Totally 269 patients admitted to the Anhui Provincial Hospital of Anhui Medical University who underwent IVMTE (IVMTE group, n=47) or thoracoscopy combined with minimally invasive Mckeown esophageal cancer resection (MIME group, n=222) from September 2017 to December 2021 were analyzed retrospectively. There were 31 males and 16 females in IVMTE group, aged (68.6±7.5) years (range: 54 to 87 years). There were 159 males and 63 females in MIME group, aged (66.8±8.8) years (range: 42 to 93 years). A 1∶1 match was performed on both groups by propensity score matching, with 38 cases in each group. The intraoperative conditions and postoperative complication rates of the two groups were compared by t test, Wilcoxon rank, χ² test, or Fisher exact probability method. Results: Patients in IVMTE group had less intraoperative bleeding ((96.0±39.2) ml vs. (123.8±49.3) ml, t=-2.627, P=0.011), shorter operation time ((239.1±47.3) minutes vs. (264.2±57.2) minutes, t=-2.086, P=0.040), and less drainage 3 days after surgery (85(89) ml vs. 675(573) ml, Z=-7.575, P<0.01) compared with that of MIME group. There were no statistically significant differences between the two groups in terms of drainage tube-belt time, postoperative hospital stay, and lymph node dissection stations and numbers (all P>0.05). The incidence of Clavien-Dindo grade 1 to 2 pulmonary infection (7.9%(3/38) vs. 31.6%(12/38), χ²=6.728, P=0.009), total complications (21.1%(8/38) vs. 47.4%(18/38), χ²=5.846, P=0.016) and total lung complications (13.2%(5/38) vs. 42.1%(16/38), χ²=7.962, P=0.005) in the IVMTE group were significantly lower. Conclusion: Inflatable video-assisted mediastinoscopic transhiatal esophagectomy combined with laparoscopic esophagectomy is safe and feasible, which can reach the same range of oncology as thoracoscopic surgery.
Male ; Female ; Humans ; Retrospective Studies ; Esophagectomy/methods* ; Treatment Outcome ; Laparoscopy ; Thoracoscopy ; Lymph Node Excision/methods* ; Esophageal Neoplasms/surgery* ; Postoperative Complications