A dose reconstruction algorithm for electrionic portal imaging device(EPID)based on calibration and calculation is developed.The raw data of EPID in continuous acquisition mode are corrected for dark field and gain,and the gray level features of bright field are used to determine the field boundary.Subsequently,MU calibration,off-axis calibration and field size calibration are performed on the EPID data,and dose reconstruction is carried out based on the calibrated superimposed flux and the Monte Carlo model of the linac head.Nine cases of IMRT plans are selected for verification and measurement using EPID and MapCheck separately,and the passing rates between the two tools are compared under different gamma criteria(3%/3 mm and 2%/2 mm).For a planned case,the average passing rates of multiple cases verified by MapCheck under the two criteria were 99.02%±1.28%and 90.84%±4.49%,and the average passing rates of the EPID reconstruction models were 98.86%±1.19%and 91.39%±4.80%.Compared with MapCheck,the EPID reconstruction algorithm based on calibration and calculation has no significant difference in the passing rate of IMRT plan verification(P＞0.05),which meets the clinical requirements of dose verification.

Objective A quality control(QC)system based on the electronic portal imaging device(EPID)system was used to realize the Multi-Leaf Collimator(MLC)position verification and dose verification functions on Primus and VenusX accelerators.Methods The MLC positions were calculated by the maximum gradient method of gray values to evaluate the deviation.The dose of images acquired by EPID were reconstructed using the algorithm combining dose calibration and dose calculation.The dose data obtained by EPID and two-dimensional matrix(MapCheck/PTW)were compared with the dose calculated by Pinnacle/TiGRT TPS for γ passing rate analysis.Results The position error of VenusX MLC was less than 1 mm.The position error of Primus MLC was significantly reduced after being recalibrated under the instructions of EPID.For the dose reconstructed by EPID,the average γ passing rates of Primus were 98.86%and 91.39%under the criteria of 3%/3 mm,10%threshold and 2%/2 mm,10%threshold,respectively.The average γ passing rates of VenusX were 98.49%and 91.11%,respectively.Conclusion The EPID-based accelerator quality control system can improve the efficiency of accelerator quality control and reduce the workload of physicists.

Objective:To develop the real-time radiotherapy monitoring system of three-dimensional (3D) point cloud by using depth camera and verify its feasibility.Methods:Taking the depth camera coordinate system as the world coordinate system, the conversion relationship between the simulation CT coordinate system and the world coordinate system was obtained from the calibration module. The patient's simulation CT point cloud was transformed into the world coordinate system through the above relationship, and registered with the patient's surface point cloud obtained in real-time manner by the depth camera to calculate the six-dimensional (6D) error, and complete the positioning verification and fractional internal position error monitoring in radiotherapy. Mean and standard deviation of 6D calculation error, Hausdorff distance of point cloud after registration and the running time of each part of the program were calculated to verify the feasibility of the system. Fifteen real patients were selected to calculate the 6D error between the system and cone beam CT (CBCT).Results:In the phantom experiment, the errors of the system in the x, y and z axes were (1.292±0.880)mm, (1.963±1.115)mm, (1.496±1.045)mm, respectively, and the errors in the rotation, pitch and roll directions were 0.201°±0.181°, 0.286°±0.326°, 0.181°±0.192°, respectively. For real patients, the translational error of the system was within 2.6 mm, the rotational error was approximately 1°, and the program run at 1-2 frames/s. The precision and speed met the radiotherapy requirement. Conclusion:The 3D point cloud radiotherapy real-time monitoring system based on depth camera can automatically complete the positioning verification before radiotherapy, real-time monitoring of body position during radiotherapy, and provide error visual feedback, which has potential clinical application value.

Objective:To construct a cycle dual-task network based on cycleGAN to implement 3D CT synthesis from single-view projection for adaptive radiotherapy of thoracic tumor and then evaluate image quality and dose accuracy.Methods:A total of 45 thoracic tumor patients admitted to the Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University were collected, and 991 cases were also selected from public dataset as pretrained dataset. Multi-view projections were acquired by ASTRA algorithm. The public dataset was divided into a training set of 800 cases, a validation set of 160 cases and a test set of 31 cases. The dataset obtained from patients in our hospital was divided into a training set of 40 cases and a test set of 5 cases. The network included synthetic CT model and multi-view projection prediction model and achieved the dual-task training. The final test only used the synthetic CT model to acquire the predicted CT images and deliver image quality [mean absolute error (MAE), peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM)] and dose evaluation.Results:Image quality evaluation metrics for synthetic CT showed high image synthesis accuracy with MAE of 0.05±0.01, PSNR of 19.08±1.69, SSIM of 0.75±0.04, respectively. The dose distribution calculated on synthetic CT was also close to the actual dose distribution. The mean 3%/3 mm γ pass rate for synthetic CT was 93.1%.Conclusions:A dual-task cycle network modified on cycleGAN has been implemented to rapidly and accurately predict 3D CT from single-view projection, which can be applied to the workflow of adaptive radiotherapy for thoracic cancer. Both image generation quality and dosimetric evaluation demonstrate that synthetic CT can meet the clinical requirements for radiotherapy.

Objective To investigate the dosimetric effect of truncated regions in computed tomography (CT) images on the targets and organs at risk in volumetric modulated arc therapy (VMAT) for middle thoracic esophageal cancer. Methods CT images of 15 patients with middle thoracic esophageal cancer were selected. Circle masks were used to make the volume of the truncated region account for 10%, 20%, 30%, and 40% of the arm volume, and the corresponding truncated CT images were obtained. The real CT was denoted as CT0. Two radiotherapy plans were made on CT0. One plan was VMAT_1F with full arcs, and the other one was VMAT_3F with arm avoidance. The plans were transplanted to four truncated CT, respectively, and the dosimetric differences between different plans were compared using Wilcoxon signed-rank test. Results Compared with VMAT_1F in CT0, D_mean and V₅ of the lung decreased in VMAT_3F, but D_max of the spinal cord, D_mean of the heart, and V₂₀ of the lung increased. In VMAT_3F, there was no statistically significant difference between the dosimetric parameters in the four truncated CT and those in CT0 (all P > 0.05). In VMAT_1F, except for homogeneity index and D_max of the spinal cord, the dosimetric parameters in four truncated CT were significantly different from those in CT0 (P < 0.05). The dosimetric difference increased with the increase in truncated region-to-volume ratio. Conclusion Complete CT data should be collected in clinical practice, and the radiation field avoiding the truncated regionshould be set if necessary to reduce the influence of the truncated region on dosimetry.

Objective:To develop a 3D visualization technology-assisted patient positioning system for radiotherapy and compare it with traditional patient positioning method for breast and pelvic radiotherapy.Methods:A total of 40 patients receiving radiotherapy in Changzhou No.2 People′s Hospital from June 2020 to April 2021 were selected for this study, including 20 patients with breast cancer and 20 patients with pelvic cancer.3D visualization reconstruction was carried out using the CT data of the patients for positioning. Then the 3D visualization models were integrated with the real treatment environment and were then shifted to the isocentral positions of accelerators through interactive operations. Based on this, the patients were actually positioned. Every week, all of the patients were firstly treated with traditional positioning, followed by 3D visualization-guided positioning. As a result, 240 times of positioning data of all patients were collected in three weeks. They were compared with the data of cone-beam CT(CBCT)-guided positioning, which served as the gold standard.Results:The absolute positioning errors of 3D visualization-guided positioning along x, y and z axes were (1.92±1.23), (2.04±1.16), and (1.77±1.37)mm, respectively for patients with breast cancer and were (2.07±1.08), (1.33±0.88), and (1.99±1.25)mm, respectively for patients with pelvic cancer. Compared with traditional positioning method , the accuracy of 3D visualization-guided positioning along x、 y, and z axes was increased by 38.83%, 52.40% and 33%, respectively for patients with breast cancer and was improved by 36.84%, 54.04% and 52.58% for patients with pelvic cancer, with all differences being statistically significant along y and z axes ( t=2.956-5.734, P< 0.05). Meanwhile, the error distribution of the two positioning method was statistically significant along in y axis for patients with breast cancer( χ2=7.481, P<0.05) and was statistically significant along each axis for patients with pelvic cancer( χ2=5.900, 6.415, 7.200, P<0.05). Conclusions:The positioning method guided by 3D visualization technology can effectively improve the positioning accuracy of patients with breast cancer and patients with pelvic cancer and is of value in potential clinical application.

Objective:To explore the volume resolution of prostate motion target by four-dimensional (4D) ultrasound.Methods:The prostate ultrasound model was selected, and the group comparison study was conducted using 4D ultrasound to outline the prostate target under different motion amplitudes (A) and motion period (T). The simulated A value was set as 0.5 mm, 1 mm, 2 mm, 3 mm, 4 mm, and 5 mm, respectively. The T value was set as 1 s, 2 s, 3 s, and 4 s, respectively. The volume of the target of the model prostate was calculated, and the static ultrasound image of the target was used as the control group to analyze the difference between two groups.Results:When the model was still, the size of the target of ultrasound was consistent with that of CT scan ( P>0.05). When the A values were 0.5 mm and 1 mm, there was no statistical difference between the volume in period 1-4 s and the volume in the target at rest (all P>0.05). When the A values were 2 mm and 3 mm, and the T values were 1 s, 2 s and 3 s there was statistical difference between the volume of target and that of of static ultrasonic target (all P<0.05). When the A value was 2 mm and the T value was 4 s, there was no statistical difference between the target volume and the static target volume ( P=0.710). The range within the group was 6.7 cm 3, and the standard deviation was 1.15 cm 3. When the A value was 3 mm and the T value was 4 s, the volume repeatability of the target was poor, and the range within the group was 14.4 cm 3; when the A values were 4 mm and 5 mm, and the T values were 1-4 s, the range within the group was 3.27-17.63 cm 3 and 6.51-21.02 cm 3, respectively. The volume repeatability of the target under each period was extremely poor, which could not meet the clinical requirements. Conclusion:4D ultrasound can provide reliable reference data for patients′ target delineation within 1-4 s of motion cycle and within 1 mm of motion amplitude, which exerts on effect upon the original position of probe.

Medical images can provide clinicans with accurate and comprehensive patients’ information. Morphological or functional abnormalities caused by various diseases can be manifested in many aspects. Although MR images and CT images can highlight the medical image data of different tissue structures of patients, single MR images or CT images cannot fully reflect the complexity of diseases. Using MR image to predict CT image is one of the cross-modal prediction of medical images. In this paper, the methods of MR image prediction for CTmage are classified into four categoriesincluding registration based on atlas, based on image segmentationmethod, based on learning method and based on deep learning method. In our research, we concluded that the method based on deep learning should bemore promoted in the future by compering the existing problems and future development of MR image predicting CT image method.

Objective:To observe the effect and underlying mechanism of down-regulation of VEGFA on the radiosensitivity of esophageal cancer ECA-109 cells.Methods:Esophageal cancer cells were divided into four groups: sh-VEGFA group, vector control group, X-ray plussh-VEGFA group and X-ray plus vector group. The expressions of VEGFA gene and protein were detected by qPCR and Western blot, respectively. Cell proliferation and survival was measured by CCK8 assay and cloning formation, respectively. Cell apoptosis was detected by flow cytometry, and γ-H2AX foci were detected by immune-fluorescence assay.Results:Compared with the vector group, the expression of VEGFA gene was decreased in sh-VEGFA group ( t=11.98, P<0.05), and the expression of VEGFA protein was also reduced( t=12.38, P<0.05). After VEGFA being down-regulated, the cell proliferation( A450)was obviously inhibited( t=2.78, 7.25, 21.93, 13.21, P<0.05), and the cell clone formation of the sh-VEGFA group was significantly decreased so that D0, Dqand SF2 of sh-VEGFA group were decreased( t=5.83, 8.56, 7.68, P<0.05), and SERD0and SERDqwere increased. Compared with the vector group, the apoptosis rate in the sh-VEGFA group and the X-ray group was significantly increased and further increased in the sh-VEGFA plus X-ray group( t=17.63, 22.48, 33.87, P<0.05), and the number of γ-H2AX foci in both sh-VEGFA and vector groups were significantly increased within 2 h after X-ray irradiation. At 24 h after irradiation, the number of γ-H2AX foci returned to normal level in the vector group but remained at a higher level in the sh-VEGFA group ( t=7.00, P<0.05). Conclusions:Down-regulation of VEGFA inhibits the proliferation and colony formation, promotes apoptosis and hence increases the radiosensitivity of esophageal carcinoma cells via a pathway related to DNA damage repair.

Objective An improved method for obtaining pseudo-computed tomography (CT ps) based on ultrasound deformation field.Methods The three-dimensional image data of computed tomography and ultrasound for three postoperative cervical cancer patients were selected,including the CT (CTsim) and ultrasound (USsim) images obtained during the simulated positioning stage,and the cone beam CT (CBCT) and ultrasound images obtained during the positioning verification stage of the treatment one week later.Binary masks of the OROI and OROW were created and applied in ultrasound image registration;thus,the deformation field was obtained.The deformation field was applied to CTsim images and different pseudo-CT images were obtained.Similarities between these pseudo-CT images and those of CBCT were compared,and registration accuracies between pseudo-CT images under different binary masks and CTsim were discussed.Results The averages of the correlation coefficient between pseudo-CT based on OROI,OROW,no binary mask and CBCT were 0.95,0.82 and 0.64 respectively.The average of the normalized mean square Error were 0.12,0.42 and 0.57 respectively.Conclusion The pseudo-CT based on OROI binary mask matches the best with CTsim and achieves the highest similarity with CBCT.