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Objective:To study the improvement of normal tissue region of interest (ROI) segmentation based on clustering-based multi-Atlas segmentation method, thereby achieving better delineation of organs at risk.Methods:CT images of 100 patients with cervical cancer who had completed treatment in Zhejiang Cancer Hospital during 2019-2020 were selected as the Atlas database. According to the volume characteristic parameters of the organs at risk (bladder, rectum and outer contour), the Atlas database was divided into several subsets by k-means clustering algorithm. The image to be segmented was matched to the corresponding Atlas library for multi-Atlas segmentation. The dice similarity coefficient (DSC) was used to evaluate the segmentation results.Results:Using 30 patients as the test set, the sub-Atlas generated by different clustering methods were compared for the improvement of image segmentation results. Compared with general multi-Atlas segmentation methods, clustering-based multi-Atlas segmentation method significantly improve the segmentation accuracy for the bladder (DSC=0.83±0.09 vs. 0.69±0.15, P<0.001) and the rectum (0.7±0.07 vs. 0.56±0.16, P<0.001), but no statistical significance was observed for left and right femoral head (0.92±0.04, 0.91±0.02) and bone marrow (0.91±0.06). The average segmentation time of clustering-based multi-Atlas segmentation method was shorter than that of the general multi-Atlas segmentation method (2.7 min vs. 6.3 min). Conclusion:The clustering-based multi-Atlas segmentation method can not only reduce the number of Atlas images registered with the image to be segmented, but also can be expected to improve the segmentation effect and obtain higher accuracy.
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Medical physicists play an important role in the delivery of radiotherapy. Compared with China′s mainland, Hong Kong has established a more mature training mode and a more complete management system for medical physics talents. In this article, the authors introduced the current state of medical physics talent training, as well as the recruitment, certification and promotion of medical physicist in Hong Kong by querying the official websites of medical physics organizations, reviewing related literature and interviewing senior medical physicists in Hong Kong. The authors also analyzed the shortcomings in the construction of medical physics talent system in China′s mainland and made valuable suggestions.
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Objective:Topredict the three-dimensional dose distribution of regions of interest (ROI) with brachytherapy for cervical cancer based on U-Net fully convolutional network, and evaluate the accuracy of prediction model.Methods:First, 100 cases of cervical cancer intracavity combined with interstitial implantation were selected as the entire research data set, and divided into the training set ( n=72), validation set ( n=8), and test set ( n=20). Then the U-Net was used to construct two models based on whether the uterine tandem and the implantation needles were included as the distinguishing factors. Finally, dose distribution of 20 cases in the test set were predicted using the trained model, and comparative analysis was performed. The performance of the model was jointly evaluated by , and the mean absolute deviation (MAD). Results:Compared with the model without the uterine tandem and the implantation needles, the of the rectum was increased by (16.83±1.82) cGy ( P<0.05), and the or of the other ROI were not different significantly (all P>0.05). The MAD of the high-risk clinical target volume, rectum, sigmoid, small bowel, and bladder was increased by (11.96±3.78) cGy, (11.43±0.54) cGy, (24.08±1.65) cGy, (17.04±7.17) cGy and (9.52±4.35) cGy, respectively (all P<0.05). The MAD of the intermediate-risk clinical target volume was decreased by (120.85±29.78) cGy ( P<0.05). The mean value of MAD for all ROI was decreased by (7.8±53) cGy ( P<0.05), which was closer to the actual plan. Conclusions:U-Net fully convolutional network can be used to predict three-dimensional dose distribution of patients with cervical cancer undergoing brachytherapy. Combining the uterine tube with the implantation needles as the input parameters yields more accurate predictions than a single use of the ROI structure as the input.
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Objective@#To investigate the willingness to receive measles-containing vaccine (MCV) and its influencing factors among healthcare workers in the Yangtze River Delta region, so as to provide the evidence for improving the measles-containing vaccination rate@*Methods@#Healthcare workers were sampled from 19 medical institutions in each of Shanghai Municipality, Jiangsu Province, Zhejiang Province and Anhui Province for questionnaire surveys using a multi-stage stratified convenience sampling methods from July 2020 to March 2021. Participants' gender, age, educational level, professional title, measles-containing vaccination, awareness of MCV and willingness to receive MCV were collected, and the factors affecting the willingness to receive MCV were identified among healthcare workers using a multivariable logistic regression model. @*Results@#Totally 1 403 questionnaires were allocated, and 1 394 valid questionnaires were recovered, with an effective recovery rate of 99.36%. The respondents included 327 men and 1 067 women, with a male to female ratio of 1∶3.26, and 64.35% (897) were at ages of 31 to 50 years. There were 1 005 respondents with a bachelor degree (72.09%), 765 with middle and senior professional titles (54.88%), 676 with a history of measles-containing vaccination (48.49%), 1 176 with willingness to receive MCV (84.36%) and 218 without willingness to receive MCV due to convenience of vaccination (30.73%) and cost (19.27%). Multivariable logistic regression analysis showed that region (Zhejiang, OR=1.613, 95%CI: 1.054-2.470; Anhui, OR=2.058, 95%CI: 1.259-3.363), and no history of measles (OR=2.219, 95%CI: 1.302-3.781) were factors improving the willingness to receive MCV among healthcare workers, and hospital level (secondary, OR=0.483, 95%CI: 0.306-0.763; tertiary, OR=0.251, 95%CI: 0.160-0.394), history of measles-containing vaccination (no, OR=0.262, 95%CI: 0.172-0.399; unknown, OR=0.386, 95%CI: 0.266-0.559), and unawareness of MCV knowledge (OR=0.208, 95%CI: 0.081-0.536) were factors inhibiting the willingness to receive MCV among healthcare workers.@*Conclusions@#The willingness to receive MCV correlates with region, history of measles, hospital level, history of measles-containing vaccination and awareness of MCV knowledge among healthcare workers in the Yangtze River Delta region.
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Objective@#To study a lung dose prediction method for the early stage non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy based on machine learning algorithm, and to evaluate the feasibility of application in planning quality assurance.@*Methods@#A machine learning algorithm was utilized to achieve DVH prediction. First, an expert plan dataset with 125 cases was built, and the geometric features of ROI, beam angle and dose-volume histogram(DVH) parameters in the dataset were extracted. Following a correlation model was established between the features and DVHs. Second, the geometric and beam features from 10 cases outside the training pool were extracted, and the model was adopted to predict the achievable DVHs values of the lung. The predicted DVHs values were compared with the actual planned results.@*Results@#The mean squared errors of external validation for the 10 cases in mean lung dose (MLD)MLD and V20 of the lung were 91.95 cGy and 3.12%, respectively. Two cases whose lung doses were higher than the predicted values were re-planned, and the results showed that the the lung doses were reduced.@*Conclusion@#It is feasible to utilize the anatomy and beam angle features to predict the lung DVH parameters for plan evaluation and quality assurance in early stage NSCLC patients treated with stereotactic body radiotherapy
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Objective:To explore a three-dimensional dose distribution prediction method for the left breast cancer radiotherapy planning based on full convolution network (FCN), and to evaluate the accuracy of the prediction model.Methods:FCN was utilized to achieve three-dimensional dose distribution prediction. First, a volumetric modulated arc therapy (VMAT) plan dataset with 60 cases of left breast cancer was built. Ten cases were randomly chosen from the dataset as the test set, and the remaining 50 cases were used as the training set. Then, a U-Net model was built with the organ structure matrix as inputs and dose distribution matrix as outputs. Finally, the model was adopted to predict the dose distribution of the cases in the test set, and the predicted 3D doses were compared with actual planned results.Results:The mean absolute differences of PTV, ipsilateral lung, heart, whole lung and spinal cord for 10 cases were (119.95±9.04) cGy, (214.02±9.04) cGy, (116.23±30.96) cGy, (127.67±69.19) cGy, and (37.28±18.66) cGy, respectively. The Dice similarity coefficient (DSC) of the prediction dose and the planned dose in the 80% and 100% prescription dose range were 0.92±0.01 and 0.92±0.01. The γ rate of 3 mm/3% in the area of 80% and 10% prescription dose range were 0.85±0.03 and 0.84±0.02. Conclusion:FCN can be used to predict the three-dimensional dose distribution of left breast cancer patients undergoing VMAT.
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Objective:To introduce the workflow of individualized 3D-printed intracavitary/interstitial vaginal template design. Dosimetric parameters and operation safety were investigated to evaluate the performance of 3D-printed template and freehand implantation.Methods:Forty patients previously treated with intracavitary/interstitial Ir-192 HDR brachytherapy were enrolled in this study. All patients were randomly divided into the treatment ( n=20) and control groups ( n=20). In the treatment group, twenty patients were treated with individualized 3D-printed template. CT-based preplan was carried out to determine the needle implantation cannels. Template with customized shape and implantation cannels was then produced by a 3D printer. Finally, the template was inserted under CT guidance. In the control group, twenty patients received freehand implantation. Needle insertion was decided empirically without the preplan process. Results:The difference of D 90 for high risk CTV was found to be minor, while the D 2cm 3 in the rectum, bladder and sigmoid was significantly improved in the treatment group. Meanwhile, the high dose region and conformal index were also improved in the treatment group. A total of 273 needles were inserted and one (0.3%) not-used needle was found. No normal tissues were penetrated during needle insertion in the treatment group. In the control group, a total of 203 needles were inserted and 4(2.0%) not-used needles were observed, and normal tissue penetration occurred in 3(1.5%) needle insertion. Conclusions:The individualized 3D-printed template implantation approach has advantages in terms of dosimetry and safety compared with freehand implantation. The actual treatment can achieve the dosimetric design requirements of the preplan.
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Objective To compare the dosimetric differences between free-hand method and virtually optimized method for implanting needles in intracavitary and interstitial combined brachytherapy (IC/IS BT) of cervical cancer,and to explore the improvement space of the existing interstitial brahcytherapy plan.Methods High-dose-rate cervical cancer IC/IS BT plans (short for Treatment-Plan) of 18 cases were retrospectively analyzed.For each treatment plan,Nucletron Oncentra 3D brachytherapy planning system was utilized to redesign the virtually optimized insertion method IC/IS BT plan (short for Optimized-Plan).Dose volume histogram was adopted to evaluate the dose distribution in high-risk clinical target areas and exposure dose to organ at risk (OAR).The plan execution efficiency between two plans was also assessed.Results Comparing these two plans,the differences in conformity and uniformity of dose distribution of the target area were statistically significant (P=0.000,0.008).The differences of D0.01 cm3,D1 cm3,D2 cm3 and D5 cm3 in bladder,rectum,sigmoid and small bowel were all statistically significant (all P＜0.05).Optimized-Plan could reduce the D2 cm3 of bladder,rectum,sigmoid and small bowel by 60.41,36.43,27.53 and 12.43 cGy,respectively.The execution time for the Treatment-Plan and Optimized-Plan were (857.92±243.39) s and (804.53±239.13) s with statistical significance (P＜0.001).Conclusions Compared with the free-hand method,virtually optimized method yields more conformable coverage of the target area and more uniform dose distribution.At the same time,the doses of each OAR are reduced to different degrees and the execution time of the plan is also shortened.
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Objective To study a lung dose prediction method for the early stage non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy based on machine learning algorithm,and to evaluate the feasibility of application in planning quality assurance.Methods A machine learning algorithm was utilized to achieve DVH prediction.First,an expert plan dataset with 125 cases was built,and the geometric features of ROI,beam angle and dose-volume histogram(DVH) parameters in the dataset were extracted.Following a correlation model was established between the features and DVHs.Second,the geometric and beam features from 10 cases outside the training pool were extracted,and the model was adopted to predict the achievable DVHs values of the lung.The predicted DVHs values were compared with the actual planned results.Results The mean squared errors of external validation for the 10 cases in mean lung dose (MLD) MLD and V20 of the lung were 91.95 cGy and 3.12％,respectively.Two cases whose lung doses were higher than the predicted values were re-planned,and the results showed that the the lung doses were reduced.Conclusion It is feasible to utilize the anatomy and beam angle features to predict the lung DVH parameters for plan evaluation and quality assurance in early stage NSCLC patients treated with stereotactic body radiotherapy
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Objective To evaluate the effect of different methods of deformable image registration on the dose evaluation in adaptive radiotherapy for lung cancer. Methods By using Raystation Ver4. 5 treatment planning system platform, two algorithms ( Hybrid-and Biomechanics-based deformable image registration) and two orders (CT images before and during radiotherapy as reference images) were adopted. Four deformable image registration methods were utilized to calculate the accumulative dose. Eleven patients of lung cancer received adaptive radiotherapy for 35. 0-61. 6 Gy were recruited. The mean doses of lung,heart and GTV and the D98 and D2 of GTV were statistically compared using four methods. Results With the four deformable image registration methods, the standard deviation of the mean lung dose of 11 lung cancer patients was ranged from 0. 07 to 0. 70 Gy,0. 01 to 0. 79 Gy for the mean heart dose,0. 01 to 2. 23 Gy for the mean GTV dose,0. 02 to 6. 51 Gy for the D98 of GTV and 0. 01 to 0. 97 Gy for the D2 of GTV,respectively. Conclusion The selection of deformable image registration method causes uncertainty to the calculation of accumulative dose during adaptive radiotherapy for lung cancer.
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Objective:The purpose of this paper is to introduce a method of using compensate angles to eliminate rotation set-up errors without six-degree of freedom couch. Methods: To detect six-degree of freedom set-up errors, cone-beam computed tomography (CBCT) scans were acquired. These set-up errors were defined as a matrix to transform from accelerator coordinate system to patient coordinate system. Two independent vectors were defined to describe angles of gantry, collimator and couch in accelerator machine. Transformation of vectors were determined by transformation matrix and re-calculated back to the machine angles. Results:It was found that compensate angles can fully corrected the rotation angles in set-up with limited time consuming. It is feasible to implement compensate angles in routinely radiation procedure. Conclusion:With this method, it is possible to implement the complete corrections of set-up errors in radiotherapy without six-degree of freedom couch and it is convenient in operation as well.
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Objective To explore the set-up errors of position fixation with simple perforated foam pad in colorectal cancer radiotherapy and their causes as well as the improvement measures.Methods Sixty cases of color-ectal cancer patients undergoing radiotherapy were collected.Prone position was adopted with the position fixed by perforated foam pad and membrane.CBCT imaging was taken weekly before treatment,setup errors were corrected if necessary.Errors throughout the course of treatment for each patient were recorded and compared between patients, followed by analyzing the reasons of errors.Results Before calibration,the maximum errors on the direction of left and right (X-axis),front and back (Z),upside and downside (Y)in these 60 patients were 0.5cm,0.9cm and 0.7cm respectively with the average errors of (0.22 ±0.03)cm,(0.38 ±0.03)cm and (0.27 ±0.04)cm respec-tively.Conclusion The method of applying perforated foam pad and thermoplastic mask in colorectal cancer radio-therapy is currently the most commonly used in the clinical position fixation techniques,by which the small intestine, bladder and other pelvic tissues can be well protected.Due to poor comfort prone position,it is necessary to further improve perforated foam pad through improving the quality of the foam pad,thus improving patients comfort and posi-tioning repeatability and reducing position fixation errors.
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Objective To develop a brachtherapy (BT) dose calculation program based on AAPM TG-43UI formula.With this program we can combine the dose result of external beam radiotherapy (EBRT) and BT together which is calculated by the different treatment planning TPS.Methods BT treatment data, such as source parameter, dwelling position and dwelling time, are retrieved from Nucletron Plato planning system and converted to ADAC planning system coordinate.The BT 3D dose distribution is re-calculated as well.Then the 3D dose distribution is exported to ADAC planning system.In that way, ADAC planning system can display either the EBRT dose or the BT dose and the combined dose can be calculated, displayed and evaluated as well.Results BT dose calculation result of our program which based on AAPM TG-43UI formula is identical with which of Plato (<0.1%).Furthermore, the BT dose can be transfer to the ADAC easily and the dose distributions of combined therapy can be merged in ADAC.Conclusions Our program can be used to combine the dose result of EBRT and BT from different TPS.
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Objective To study the application of correlation statistical analysis model in IMRT planning optimization. Methods A correlation statistical analysis model was established. IMRT plans of 5 prostate cancer patients were randomly chosen from the ADAC Pinacal 7.6 version planning system. The beam parameters, objective functions of the target area and optimization parameters of the primary plan were kept unchanged. The main optimization parameters including EUD parameter a,weight (w) and EUD_(max) of OAR were adjusted in optimization procedure successively. The correlation analysis (CF) and optimization efficiency analysis (OF) were carried out on the results of the optimization. The optimal value of parameters (MORt{}) with the best dose distribution was obtained and substituted in the corresponding primary plan.After optimization, the dose distributions of the two IMRT plans were compared. Results There were signif-icant differences with different optimization methods. The EUD parameter a and weight factor (w) almost had no effect on volume dose of OAR (OF < 0.01), though had obvious effect on the maximum dose and mean dose (OF≈1). The CF analysis showed that the correlation between the PTV ( V_(95)) volume and OAR dose was different when the EUD parameter a and w were applied for optimization. Meanwhile, the difference was proportional to the distance between the target area and OAR. The mean dose of OAR was decreased and the mean dose of PTV was more close to the prescription dose when the optimization parameters of the prima-ry plan were substituted with MOR{a} ,MOR{w} and MORt{EUD_(max)}. Besides, the DVH and isedose dis-tribution of the secondary plan were better. Conclusions The correlation statistical analysis model can be used to accurately determine the scope of optimization parameters in the IMRT planning procedure in prostate cancer, and an IMRT plan which fulfils the clinical requirement can be obtained efficiently.
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Objective To develop a beam orientation optimization algorithm for the gantry orientation in three-dimensional conformal radiotherapy(3 DCRT).Methods Patients' data were imported from the Pinnacle v 7.2 treatment planning system.including the DICOMRT and dose distribution files.These imported files were merged using a uniforiB coordinate system.The algorithm determined the optimized beam weight for each beam group and optimized the beam orientation with genetic algorithm.The optimized parameters,including the optimized beam orientations and weights,were exposed back to the Pinnacle v 7.2 to compare with the conventional 3DCRT plan.The optimized algorithm was implemented with our in-house program. The dose distributions, the DVH diagram and the conformity index of two lung cancer patients were compared. Results for the two lung cancer patients,the conformity index of the optimized plan(0.59 and 0.7)was higher than the conwentional 3DCRT plan(0.36 and 0.58).The maximum dose in spinal cord was reduced by 17.8%and 22.4%,the lung V20 reduced by 3.12%and 4.35%,and V30 reduced by 4.47%and 1.49%.For the brain tumor patient. the dose of lens and eyes was also decreased significantly. Conclusion This beam orientation optimization can be used as an assistant planning tool.
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Conformal radiation therapy using multi-leaf collimator (MLC) is considered as a conventional technology in the hospital nowadays. However the stepped leaf edge caused by the finite width of the leaves could influence the conformality that could be achievable. In this paper, the effect produced by rotating the collimator angle on the conformality was investigated. A method, in which multiple MLC fields of various rotation angles are applied, has been proposed to have the targets be more uniformly irradiated and thus to eliminate the cold spots on the targets and hot spots in normal tissues. By simulation, it has been shown that the multiple MLC field method can eliminate the stepped leaf edges and improve the conformality significantly, moreover, the PTV can receive a more uniform delivery with cold spot eliminated.