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Objective:To study the influence of environmental radiation of radiotherapy workplace on the stereotactic radiation therapy(SRT) plan absolute dose verification with plastic scintillator detector Exradin W1.Methods:The computed tomography (CT) image of the stereotactic dose verification phantom (SDVP) was scanned and imported into the treatment planning system. Three schemes, including 3 cm × 3 cm to 20 cm × 20 cm square gradient field irradiation, virtual planning target volume(PTV) non-coplanar arcs irradiation and 10 cases of volumetric modulated arc radiotherapy SRT (VMAT SRT) clinical plan verification, were measured with or without a home-made shield over the photodiode. Measurements were recorded to analyze the impact of environmental radiation on dose measurement under different conditions.Results:The noise effect of the photodiode increased with the the lager open field size, and decreased with the reduced distance between the photodiode and isocenter. The contribution of photodiode noise effect increase with the lager non-coplanar arc field size, with the largest up to 4.16%. As for the clinical SRT plan verification measurement, the relative difference between the SRT plan measurements and treatment planning system(TPS) before and after shielding were (1.39±1.05)% and (0.59±1.03)%, respectively ( t=-5.343, P < 0.05). and for W1 vs. A16 microchamber was (1.22±1.56)% and (0.42±1.42)%, respectively ( t=-5.414, P < 0.05). Conclusions:The measurements of Exradin W1 are in good agreement with the TPS result and the ionization chamber measurements, but its accuracy is easily affected by the environmental radiation of radiotherapy workplace. To measure non-coplanar radiation, the photodiode should be placed as far away as possible from the isocenter and be properly shielded, which can effectively improve the accuracy and stability of the measurement and provide a strong guarantee for clinical precision radiotherapy.
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Objective:To develop a deep learning-based approach for predicting the dose distribution of intensity-modulated radiotherapy (IMRT) for breast cancer patients, and evaluate the feasibility of applying the predicted dose distribution in the automatic treatment planning.Methods:A total of 240 patients with left breast cancer admitted to Fudan University Shanghai Cancer Center were enrolled in this study: 200 cases in the training dataset, 20 cases in the validation dataset and 20 cases in the testing dataset. A modified deep residual neural network was trained to establish the relationship between CT image, the contouring images of target area and organs at risk (OARs) and the dose distribution, aiming to predict the dose distribution. The predicted dose distribution was utilized as the optimization objective function to optimize and generate a high-quality plan.Results:Compared with the dose distribution of clinical treatment plan, the predicted dose distribution for target areas and OARs showed no statistical significance except for a simultaneous boost target PTV 48Gy. And the treatment plan generated based on the predicted dose distribution was basically consistent with the predicted outcomes. Conclusion:Our results demonstrate that the deep learning-based approach for predicting the dose distribution of IMRT for breast cancer contributes to further achieving the goal of automatic treatment planning.
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Objective:To realize automatic delineation of rectal cancer target volume and normal tissues and improve clinical work efficiency.Methods:The deep learning method based on convolutional neural network was adopted to construct neural network, learn and realize automatic delineation, and compare the differences between automatic delineation and manual delineation.Results:Two hundred and ten cases with rectal cancer were randomly assigned to a training set of 190 and a validation set of 20. The complete delineation of a single case took about 10s; the average Dice of CTV was 0.87±0.04; the average Dice of other normal tissues was bigger than 0.8; the Hausdorff distance (HD) index of CTV was 25.33±16.05; the mean distance to agreement (MDA) index was 3.07±1.49, and the Jaccard similarity coefficient (JSC) index was 0.77±0.07.Conclusion:The deep learning method based on full convolutional neural network can realize the automatic delineation of rectal cancer target volume and improve work efficiency.
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Objective Multiple software applications and systems and complex hardware are utilized in the process of radiotherapy. In this paper,Xenapp-based visualized system was adopted to integrate each system during the radiotherapy procedures. Methods Windows2008r2 operating system,Citrix Xenapp 6. 5 sp1 enterprise edition,sqlserverr2008 express database were utilized. The Xenapp server was installed and the commonly used software applications were installed and published on this server. CitrixReceiver was installed on the computers in the local network in Department of Radiotherapy. A web browser was utilized to log in the Xenapp server to access all the applications published on the server. Results The application of Citrix Xenapp-based virtualized system significantly reduced the cost of computer hardware by more than 50％,decreased the maintenance cost of technical personnel. Besides,it made the process of Department of Radiation Oncology seamless and improved the efficiency of the staff in the Department of Radiation Oncology. Conclusions The Xenapp-based virtualized system can save cost and improve efficiency in the process of radiotherapy,which is worthy of widespread application in clinical practice.
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The theory and application of small animal radiotherapy models is critical for the research and development of radiobiology and clinical radiotherapy.Considering universality and cost effects,mouse models are widely used to explore the radiobiological mechanisms of cancerous and normal tissues.In recent years,there has been tremendous progress in image-guided stereotactic radiotherapy equipment for small animals,which could simulate the human radiotherapy process.This article introduces stereotactic radiotherapy systems for small animals guided by different imaging modalities,such as cone-beam computed tomography and magnetic resonance imaging,and then reviews small animal fluorescence imaging technology and summarizes the application of different bioluminescence and fluorescence imaging equipment in small animal imaging systems.Finally,we put forward the prospect of optimization direction of radiotherapy equipment for small animals in future.
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Objective To develop an automatic algorithm to predict the dose-volume histogram (DVH) and implement it in clinical practice.Methods Based on the prior information in the existing plan,such as dosimetric results of organs at risk (OARs) and OAR-target spatial relationship,a two-dimensional kernel density estimation was implemented to predict the DVH of OARs.The predicted DVH curves were converted into objective functions that would be implemented in the Pinnacle treatment planning system.Comparisons between predicted and actual values and between Auto-plan and manual planning were made by paired t test.Results We applied this algorithm to 10 rectal cancer patients,10 breast cancer patients,and 10 nasopharyngeal carcinoma patients.The predicted DVH of OARs showed that the deviation between the actual and predicted values at important clinical dose points were within 5%(P>0.05).The re-planning for the 10 breast cancer patients using Auto-plan showed that the heart dose was significantly reduced and the target coverage was increased,which was consistent with the predicted results.Conclusions The method proposed in this study allows for accurat DVH prediction,and,combined with Auto-plan,can be used to generate clinically accepted treatment plans.
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Objective To retrospectively review the history and development of radiotherapy quality assurance ( QA) in the Affiliated Cancer Hospital of Fudan University, and to report the primary experience and evolvement of an entire QA workflow management. Methods The multidisciplinary QA team has implemented an entire QA workflow management process in the Radiotherapy Center using the failure modes and effects analysis ( FMEA) and plan?do?check?act ( PDCA) tool since April 2015. Treatment data of approximately 6000 patients before and after implementation were compared. Results The error rate was reduced from 17% to 09% after using the entire QA workflow management. Conclusions Entire QA workflow management effectively improves the accuracy and safety of radiotherapy.
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Background and purpose:Radiomics is an emerging field that generates large amounts of valuable clinical information through extracting quantitative imaging features. The purpose of this study was to use the radiomics approach to assess the value of features captured from PET and CT in predicting the therapeutic effect in stageⅠ non-small cell lung cancer (NSCLC) after stereotactic ablative radiotherapy (SABR).Methods:Patients with stageⅠ NSCLC conifrmed by pathology and treated with SABR were included retrospectively. The gross tumor volume (GTV) was deifned by two radiologists. PET and CT scan images were collected, and radiomic features were further extracted and analyzed. Non-negative matrix factorization was used to distinguish patients with or without local control.Results:Sixteen patients were eligible for analysis. This study identiifed two PET features (LL_GLCM_Maximal_Correlation_Coeffcient and HL_GLRMS_LRE) captured from PET/CT as having signiifcance in classifying patients with or without disease development. This study not ifnd similar results in CT scans.Conclusion:It seems feasible to use radiomics information effects from PET/CT to predict therapeutic effects of SABR in stageⅠ NSCLC. Further investigation is needed.
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Radiomics is a new area of research, which converts imaging data into high?resolution quantitative imaging features by applying the automatic high?throughput imaging?feature?extraction algorithm. With the development of data science, more and more attention has been paid to the non?invasive and quantitative method in precision radiotherapy all over the world. This paper will briefly introduce the concept of radiomics and its application in precision radiotherapy.
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Objective To determine whether Auto-Planning-based volumetric modulated radiotherapy(Auto-VMAT)planning can improve planning efficiency without compromising plan quality compared with current manual trial-and-error-based volumetric modulated arc therapy(Manual-VMAT) planning for patients with rectal cancer. Methods Ten patients with stage Ⅱ-Ⅲ rectal cancer who underwent Dixon surgery were enrolled as subjects. The Pinnacle 9.10 planning system was used to design Manual-VMAT and Auto-VMAT plans. Dose distribution,homogeneity index(HI),conformity index(CI), D meanvalues of different organs at risk or dose-volume histogram of regions of interest,total planning time, and manual planning time were compared between the two plans. The differences were analyzed by paired t test. Results Dosimetric prescriptions were achieved in both plans. There were no significant differences in HI or CI between the Auto-VMAT plans and the Manual-VMAT plans(0.058 vs. 0.058, P=0.972;0.921 vs. 0.940,P=0.115). Compared with the Manual-VMAT plans,the V 40,D mean,and D 50%of the bladder were significantly reduced by 25.6%, 11.5%, and 8.9%, respectively, in the Auto-VMAT plans(P=0.004,0.016,0.001);the V 40,D mean,and D 50%of the small intestine were also significantly reduced by 12.1%,5.4%,and 6.8%,respectively,in the Auto-VMAT plans(P=0.023,0.001,0.001);the V 30, D mean,and D 50%of the left and right femoral heads were slightly reduced in the Auto-VMAT plans. The Auto-VMAT plans had significantly longer total planning time but significantly shorter manual planning time than the Manual-VMAT plans(50.38 vs. 36.81 min, P= 0.000;4.47 vs. 16.94 min, P= 0.000). Conclusions Compared with the Manual-VMAT plans, the Auto-VMAT plans have substantially shorter manual planning time and improved planning efficiency.
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Background and purpose:The radiation should move at the same direction in accordance with the position of the couch during radiotherapy due to the different location of gross target volume. However, under the condition of the long distance movement of the couch, collisions between the gantry and the couch (or the patients) may happen. To avoid the collisions between the gantry and the couch, the motion area conlfiction between the gantry and the couch was analyzed.Methods:The distance from isocenter to the surface center of linear accelerator head, and the width and the thickness of treatment bed were measured when the treatment bed was empty, and gantry and collimator were at zero position. Forty sets of bed movement data were collected. The sum of squares ofX-andY-coordinates of reference point was calculated and compared with squares of rotation radius. Then, it was anticipated whether the linear accelerator head will collide with treatment bed. Finally, practical veriifcation was made.Results:Whether linear accelerator head collides with treatment bed depends on the difference between the sum of squares ofX-andY-coordinates and the squares of rotation radius. No collisions will happen when the sum of squares ofX-andY-coordinates is less than that of the squares of rotation radius.Conclusion:It is feasible to avoid collisions of linear accelerator head with treatment bed by comparing the sum of squares ofX-andY-coordinates of reference point with squares of rotation radius.
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Background and purpose:Radiomics refers to the comprehensive quantification of human tissues through assessing a large number of quantitative image features. Radiomics approach is used to decode tumor phenotypes and predict treatment outcomes. Here we present a study investigating radiomic analysis to assess normal liver features and predict chemotherapy-associated liver injury.Methods:Gastric cancer patients treated with surgery and adjuvant chemotherapy were enrolled in this study retrospectively. CT images were obtained before chemotherapy. The whole liver organ was delineated by radiation oncologists. Images were extracted and filtered by radiomic approach to extract radiomic features. Clustering was performed to reveal clusters of patients with similar radiomic expression patterns. Chi-squared tests were used to assess the association of radiomic data with clinical data and chemotherapy-related liver injury.Results:Radiomic features of 73 patients were clustered into two clusters. A significant association with gender (P=0.004, chi-squared test) was observed, where in male showed a higher presence in cluster Ⅰ. Incidence of abnormal liver function after chemotherapy was 48.7% in cluster I and 67.6% in cluster Ⅱ, respectively (Δ=18.9%). Clinical data including age, gender, chemotherapy modality, number of chemotherapy cycles, HBV infection history, HBs-antigen presence were not associated with liver function abnormalities after chemotherapy. Accuracy of radiomic analysis to predict liver injury is 0.59.Conclusion:Radiomic approach revealed different imaging features of liver between men and women. It could help to predict chemotherapy-associated liver injury. It is feasible to use radiomics approach to decode normal liver features and predict treatment-associated liver injury.
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Background and purpose:Radiotherapy has been the preferred method for the treatment of naso-pharyngeal carcinoma (NPC). The aim of this paper was to compare the dosimetric differences in target volume and organ at risk between simpliifed intensity-modulated radiation therapy (sIMRT) and intensity-modulated radiation therapy (IMRT) in nasopharyngeal carcinoma.Methods:Treatment plans for ten NPC cases were designed with the same dose prescription and objective by means of IMRT and sIMRT respectively. Compare:(1) Plan dosimetric dis-tribution, conformity index (CI) and homogeneity index (HI) of the targets, the dosimetric parameters of organ at risk (OAR); (2)The total monitor units (MU) and the total segments.Results:The CI and HI of the planning gross tumor volume(PGTV) were 0.647 and 0.057 (IMRT), 0.633 and 0.071 (sIMRT), respectively (t=2.14,P=0.062;t=-6.21, P=0.000). Compared to IMRT, sIMRT had less inferior target homogeneity. However both treatment plans could achieve the clinical dosimetric demands. There was no signiifcant difference between IMRT and sIMRT in protecting OAR (t=-0.51-2.22,P=0.053-0.621). The sIMRT plan was better than IMRT plan in total MU and total segments. Conclusion:sIMRT is slightly inferior to IMRT in terms of target homogeneity, with similar target conformity and OAR dosimetric parameters. The sIMRT plan can reduce total monitor units and total segments. Thus it provides a clinical solution with high effciency for radiotherapy center with a large number of patients.
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Objective To establish a rat model of radiation-induced optic neuropathy ( RION) by delivering a single radiation dose to the optic chiasm. The aim of our study was to analysis the feasibility and effectiveness of manganese-enhanced magnetic resonance imaging ( MEMRI) in RION. Methods 34 Wistar rats were randomized to the control group(4 rats), the 2-month group(5 rats),the 4-month group(4 rats) and the 6-month group(11 rats) according to the different feeding period after irradiation. MEMRI scan were performed when the respective feeding periods of all groups expired. The rats were then killed for histological studies with hematoxylin and eosin stain, Luxol Fast Blue stain, and electron microscopy analysis. Results The ratio of RION in the four groups were 0/3, 1/5, 2/4 and 11/11, respectively (χ2 =15?443, P<0?05). There was an inverse correlation between the relative optical density value in the LFB stain and the interval between irradiation and pathological examination(R= -0?643,P<0?05). The number of glial cells in the HE stain in the four groups were 194 ± 65, 234 ± 19, 124 ± 11 and 345 ± 98, respectively(R=0?590,P<0?05). When compared MEMRI scan with the corresponding histological examination, we found that there was loss of signals of optic nerve on MEMRI imaging in one of 5 rats in the 2-month group, while no significant histological difference was found between this rat and the others. Conclusions RION can be non-invasively detected and semi-quantitative analysed by MEMRI scan. Moreover, RION can be early diagnosed by MEMRI scan which is capable to show physiological change in advance of pathological change.
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Objective To compare the difference region of interest volume (ROI) calculation method between Pinnacle and Eclipse treatment planning system. Methods To acquire CT image with 3 of slice thickness (1 mm, 3 mm, and 5 mm). Delineate 1, 2 and 5 slices square and circle contours in Pinnacle treatment planning system. Meanwhile 15 cases that include 5 cases with head neck tumor, 5 with thorax tumor and 5 with abdomen tumor were selected. Those image and ROI were transfer to Eclipse treatment plan system by DICOM RT protocol . The ROI volume was compared between two TPS . Results For ROI with small volume, the volume difference between TPS was obvious (for small volume ROI have 12 times difference, for big volume ROI almost same). The volume difference between TPS was influenced by many factors. The number of ROI slice and the magnitude of ROI was related with the difference between TPS (R2 = 1. 000, P = 0. 000). The CT thickness (R2 = 0. 200, P = 0. 972 ) and the shape of ROI ( R2 =0. 200, P = 0. 089) were not significant factors. The center of ROI on different axis was not affect the volume calculation in Pinnacle, which cause 3% different in Eclipse. The CT thickness was proportional to the ROI volume ( Pinnacle R2 = 0. 548, P = 0. 011; Eclipse R2 = 0. 502, P = 0. 027 ). In clinical case, optic chiasm and Len averagely have more than 35% volume difference between those two TPS. Conclusions We should pay more attention about the difference volume calculation algorithm between Pinnacle and Eclipse,especially when transfer small volume ROI to another TPS, which may have significant difference.