Objective To establish a quantitative evaluation of quality control image for the onboard imaging system of medical linear accelerator.Methods An MV planar image of electronic portal imaging device (EPID) is acquired by both Elekta iViewGT and Varian aS1000,and a kV planar image and cone-beam computed tomography (CBCT) images of CBCT are acquired by both Elekta X-ray volume imaging (XVI) and Varian On-board Imager (OBI).Phantoms used here included Las Vegas,TOR18FG,and Catphan504.A series of image quality indicators were evaluated by analyzing the images mentioned above using a quantitative method.Results A quantitative value was calculated to represent the contrast resolution of EPID.A modulation transfer function (MTF) to describe spatial resolution and a quantitative value representing contrast resolution were calculated for the kV planar image.As for the CBCT system,a series of quantitative results of noise,uniformity,CT value accuracy,and contrast resolution and a MTF were calculated to represent the performance of CBCT system.Conclusions Based on common phantoms,a complete set of quantitative methods to evaluate the image quality of EPID and CBCT has been developed,which could provide a very good reference for the establishment of quality control system for image-guided radiotherapy.

Objective To establish a fast and accurate method for measurement of leaf position accuracy of dynamic multi-leaf collimator (MLC) using electronic portal imaging device (EPID) and EBT3 film dosimeter.Methods A Varian 6 MV accelerator was used with the gantry angle and the collimator angle fixed at zero degree.A total of 11 sliding window MLC fields were designed.Each field contained a group of strip fields with the same width.The width of a strip field ranged from 1 mm to 10 mm and the distance between two adjacent strip fields was 20 mm.The relationship between the width of the strip field (band width) and the full width at half maximum (FWHM) was calibrated using EPID and EBT3 as measurement tools.A field with a band width of 5 mm was designed in the same way and several MLC leaf deviations were made in different positions.EPID and EBT3 film dosimeter were used to analyze the leaf position accuracy.Results A good linear relationship between band width and FWHM was achieved when the band width was larger than 4 mm.The accuracy of band width,distance between peaks,and MLC leaf position were determined as ±0.2 mm,±0.1 mm,and ±0.1 mm by EPID and ±0.3 mm,±0.2 mm,and ± 0.2 mm by EBT3 film dosimeter,respectively.Conclusions This study provides a fast and accurate method for the measurement of MLC leaf position accuracy using EPID or EBT3 film dosimeter,which is helpful for quality assurance of MLC.

Objective:To evaluate the practicability of dose volume histogram (DVH) prediction model for organ at risk (OAR) of radiotherapy plan by minimizing the cost function based on equivalent uniform dose (EUD).Methods:A total of 66 nasopharyngeal carcinoma (NPC) patients received volume rotational intensity modulated arc therapy (VMAT) at Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences from 2020 to 2021 were retrospectively selected for this study. Among them, 50 patients were used to train the recurrent neutral network (RNN) model and the remaining 16 cases were used to test the model. DVH prediction model was constructed based on RNN. A three-dimensional equal-weighted 9-field conformal plan was designed for each patient. For each OAR, the DVHs of individual fields were acquired as the model input, and the DVH of VMAT plan was regarded as the expected output. The prediction error obtained by minimizing EUD-based cost function was employed to train the model. The prediction accuracy was characterized by the mean and standard deviation between predicted and true values. The plan was re-optimized for the test cases based on the DVH prediction results, and the consistency and variability of the EUD and DVH parameters of interest (e.g., maximum dose for serial organs such as the spinal cord) were compared between the re-optimized plan and the original plan of OAR by the Wilcoxon paired test and box line plots.Results:The neural network obtained by training the cost function based on EUD was able to obtain better DVH prediction results. The new plan guided by the predicted DVH was in good agreement with the original plan: in most cases, the D 98% in the planning target volume (PTV) was greater than 95% of the prescribed dose for both plans, and there was no significant difference in the maximum dose and EUD in the brainstem, spinal cord and lens (all P>0.05). Compared with the original plan, the average reduction of optic chiasm, optic nerves and eyes in the new plans reached more than 1.56 Gy for the maximum doses and more than 1.22 Gy for EUD, and the average increment of temporal lobes reached 0.60 Gy for the maximum dose and 0.30 Gy for EUD. Conclusion:The EUD-based loss function improves the accuracy of DVH prediction, ensuring appropriate dose targets for treatment plan optimization and better consistency in the plan quality.

[Abstract] Objective: To explore the expression of PSME3 (proteasome activator complex subunit 3) in gastric cancer (GC) tissues and its correlation with the prognosis of GC patients, and to further analyze its effect and mechanism in the occurrence and development of GC. Methods: The expression level of PSME3 gene in GC tissues was analyzed with TCGA and UALCAN database. qPCR was used to verify the expression of PSME3 in GC tissues and corresponding adjacent normal tissues that resected from 40 GC patients who were surgically treated in the Fourth Hospital of Hebei Medical University from January 2017 to December 2018. ROC curve and KaplanMeier plotter method were used to analyze the value of PSME3 mainly in diagnosing and predicting the prognosis of GC patients. The biological processes and pathways that PSME3 involved in were further analyzed. Results: The expression level of PSME3 in GC tissues was significantly higher than that in normal tissues, and it’s high expression was significantly correlated with the tumor stage, pathological subtype, status of lymph node metastasis and Helicobacter pylori infection in GC patients (all P<0.01). PSME3 was also highly expressed in GC tissue samples collected by the qPCR confirmatory detection group (P<0.01). PSME3 could distinguish gastric cancer patients from normal people with an AUC value of 0.808. The overall survival time, the first progression survival time and post progression survival time of the GC patients with low PSME3 expression were longer than those in the patients with high PSME3 expression (all P<0.01). Mechanism research found that PSME3 mainly played an oncogenic role of the development of GC by regulating cell cycle, mTORC1 signaling pathway, PI3K/AKT/mTOR signaling pathway and TGF- β signaling pathway etc. Conclusion: PSME3 is highly expressed in GC tissues, and it is significantly related to the poor prognosis of GC patients. It plays an oncogenic role in the occurrence and development of GC.