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Objective To establish and evaluate a morning check system for linac based on electronic portal image device (EPID).Methods Delivered fluence maps of open and wedge fields at 10 cm×10 cm field size of Synergy Linac were measured by EPID.Figure features from these two images were extracted with matlab codes and analyzed to realize a quick morning check.The repeatability of dose response and mechanical setup,relationship between gray value and machine unit (MU),accuracy of output and field size test were investigated with both EPID and DailyQA3.The status of Synergy linac was monitored both by DailyQA3 and EPID for two months.Results EPID was able to test the linac consistently with a testing error of 0.50 mm,1.00 mm for field size and center,respectively.Both of the test accuracy for flatness and symmetry was 0.17％.The mechanical accuracy test and dosimetric repeatability test were also consistent.The dose response of EPID was linearly related to the linac output (R2＞0.999).EPID was highly sensitive to the change of output and radiation field size.The measurement deviations between EPID and DailyQA3 were consistent and within clinical acceptable tolerance.Conclusions EPID showed great accuracy and stability on monitoring the performance of linac.The established daily check tool based-on EPID is accurate and reliable for clinical usage.
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Objective To evaluate the effect of setup errors on the 2D image projection and image registration, and then propose an improved registration method based on mutual information. Methods An anthropomorphic head phantom was used to simulate the rotational and translational setup errors. The geometric disparities were reflected by the changes of mutual information. Known setup errors were intentionally introduced to twenty cases divided into two groups demarcated by 3 mm translation error and 3° rotation error: ten cases with larger errors and ten with smaller errors. Then the anterior-posterior and lateral portal images were captured by the electronic portal imaging device ( EPID ) , based on which the setup errors were calculated using two mutual information registration method respectively: the vender provided one, and the improved method as proposed. The calculated errors were compared with the actual setup errors to evaluate robustness of the method. Results For the ten cases with smaller setup errors, the average translational registration disparities using the conventional method were 0. 3, 0. 4, and 0. 3 mm in x, y and z directions respectively. The rotational disagreements were 0. 4° in both x and z directions. The average time consumption was 28. 7 s. The corresponding discrepancies analyzed using the improved method were 0. 3, 0. 4, 0. 3 mm, 0. 5° and 0. 4°, respectively. On average, 31. 1 s was needed for registration. For the ten cases with larger setup errors, the mean disparities of the conventional method were 0. 9, 0. 7, 0. 8 mm, 0. 9° and 0. 8°, 29. 9 s taken on average. The corresponding result of the improved method was 0. 5, 0. 4, 0. 5 mm, 0. 6° and 0. 5°, 33. 2 s taken on average. Conclusions Regarding smaller setup errors, the two methods showed little difference and both had good performance in imageregistration accuracy. For larger setup errors, however, the improved mutual information registration method exhibited significantly higher accuracy than the conventional method, at cost of clinically acceptable registration time.
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Objective To evaluate the effect of setup errors on the 2D image projection and image registration, and then propose an improved registration method based on mutual information. Methods An anthropomorphic head phantom was used to simulate the rotational and translational setup errors. The geometric disparities were reflected by the changes of mutual information. Known setup errors were intentionally introduced to twenty cases divided into two groups demarcated by 3 mm translation error and 3° rotation error: ten cases with larger errors and ten with smaller errors. Then the anterior-posterior and lateral portal images were captured by the electronic portal imaging device ( EPID ) , based on which the setup errors were calculated using two mutual information registration method respectively: the vender provided one, and the improved method as proposed. The calculated errors were compared with the actual setup errors to evaluate robustness of the method. Results For the ten cases with smaller setup errors, the average translational registration disparities using the conventional method were 0. 3, 0. 4, and 0. 3 mm in x, y and z directions respectively. The rotational disagreements were 0. 4° in both x and z directions. The average time consumption was 28. 7 s. The corresponding discrepancies analyzed using the improved method were 0. 3, 0. 4, 0. 3 mm, 0. 5° and 0. 4°, respectively. On average, 31. 1 s was needed for registration. For the ten cases with larger setup errors, the mean disparities of the conventional method were 0. 9, 0. 7, 0. 8 mm, 0. 9° and 0. 8°, 29. 9 s taken on average. The corresponding result of the improved method was 0. 5, 0. 4, 0. 5 mm, 0. 6° and 0. 5°, 33. 2 s taken on average. Conclusions Regarding smaller setup errors, the two methods showed little difference and both had good performance in imageregistration accuracy. For larger setup errors, however, the improved mutual information registration method exhibited significantly higher accuracy than the conventional method, at cost of clinically acceptable registration time.
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Objective To explore a fast and precise registration algorithm for megavolt (MV) portal images(PIs) used for radiotherapy positioning verification, and find auto analysis method of set-up error using the computed image processing and mutual information comparison technology, which provide a basis for the development of automatic image guidance software. Methods MV PIs of patients undergoing radiotherapy were tested, pre-processed with noise reduction technique based on improved filtering algorithm and contrasted by gray-scale transforming using partial derivative threshold. The bone structures were then highlighted but soft tissues and the cavities were restrained simultaneously. Improved particle swarm optimization and powell hybrid algorithm were used to optimize and transform the mutual information based on wavelet multiresolution analysis when registering the Pls with digital reconstructed radiographs (DRRs) of treatment planning or X-ray simulation-film images(SIs). Application of the designed registration algorithm was verified and evaluated through simulated set-up shifts of head and neck phantom. Results The improved noise reduction algorithm satisfactorily met the requirements for contrast of bony structures in the MV PIs. The established mutual information registration method well behaved in both accuracy and speed of registration calculation. The processing of automatic registration took only 31.4 seconds averagely for the PIs and X-ray Sis of head-neck phantom. Mean errors of automatic registration of PIs and X-ray Sis in horizontal, vertical and rotational reduced by 62. 74% ,67. 32% and 66. 61% respectively compared with manual registration in the testing of 20-cases head and neck phantom. Conclusions A precise image registration algorithm and set-up error analysis method based on MV portal images is established, and it can meet the clinical application in registration accuracy and speed.
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Objective: To correct the set-up error of patients during radiotherapy is very important for increasing treatment effective. Methods: This paper proposes a registration method based on portal images and reference images. Canny Operator was used to extract edge features. The extracted edge features were set as datum mark to calculate the maximal mutual information between the portal images and reference images. Parameters were optimized with simplex-simulated annealing optimization strategy. Results: The portal images and reference images of 29 patients with the cervix cancer and prostatic carcinoma were registrated in this paper. The results showed that the registration was precise, and the registration speed was increased remarkably. Conclusion: So this registration method can be applied for online estimation for set-up errors in clinical radiation.
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PURPOSE: To develop a patients' setup verification tool (PSVT) to verify the alignment of the machine and the target isocenters, and the reproducibility of patients' setup for three dimensional conformal radiotherapy (3DCRT) and intensity modulated radiotherapy (IMRT). The utilization of this system is evaluated through phantom and patient case studies. MATERIALS AND METHODS: We developed and clinically tested a new method for patients' setup verification, using digitally reconstructed radiography (DRR), simulation, portal and digital images. The PSVT system was networked to a Pentium PC for the transmission of the acquired images to the PC for analysis. To verify the alignment of the machine and target isocenters, orthogonal pairs of simulation images were used as verification images. Errors in the isocenter alignment were measured by comparing the verification images with DRR of CT images. Orthogonal films were taken of all the patients once a week. These verification films were compared with the DRR were used for the treatment setup. By performing this procedure every treatment, using humanoid phantom and patient cases, the errors of localization can be analyzed, with adjustments made from the translation. The reproducibility of the patients' setup was verified using portal and digital images. RESULTS: The PSVT system was developed to verify the alignment of the machine and the target isocenters, and the reproducibility of the patients' setup for 3DCRT and IMRT. The results show that the localization errors are 0.8+/-0.2 mm (AP) and 1.0+/-0.3 mm (Lateral) in the cases relating to the brain and 1.1+/-0.5 mm (AP) and 1.0+/-0.6 mm (Lateral) in the cases relating to the pelvis. The reproducibility of the patients' setup was verified by visualization, using real-time image acquisition, leading to the practical utilization of our software. CONCLUSION: A PSVT system was developed for the verification of the alignment between machine and the target isocenters, and the reproducibility of the patients' setup in 3DCRT and IMRT. With adjustment of the completed GUI-based algorithm, and a good quality DRR image, our software may be used for clinical applications.
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Humans , Brain , Pelvis , Radiography , Radiotherapy , Radiotherapy, ConformalABSTRACT
PURPOSE: Conventional radiation therapy portal images gives low contrast images. The purpose of this study was to enhance image contrast of a linacgram by developing a low-cost image processing method. MATERIALS AND METHODS: Chest linacgram was obtained by irradiating humanoid phantom and scanned using Diagnostic-Pro scanner for image processing. Several types of scan method were used in scanning. These include optical density scan, histogram equalized scan, linear histogram based scan, linear histogram independent scan, linear optical density scan, logarithmic scan, and power square root scan. The histogram distribution of the scanned images were plotted and the ranges of the gray scale were compared among various scan types. The scanned images were then transformed to the gray window by pallette fitting method and the contrast of the reprocessed portal images were evaluated for image improvement. Portal images of patients were also taken at various anatomic sites and the images were processed by Gray Scale Expansion (GSE) method. The patient images were analyzed to examine the feasibility of using the GSE technique in clinic. RESULTS: The histogram distribution showed that minimum and maximum gray scale ranges of 3192 and 21940 were obtained when the image was scanned using logarithmic method and square root method, respectively. Out of 256 gray scale, only 7 to 30% of the steps were used. After expanding the gray scale to full range, contrast of the portal images were improved. Experiment performed with patient image showed that improved identification of organs were achieved by GSE in portal images of knee joint, head and neck, lung, and pelvis. CONCLUSION: Phantom study demonstrated that the GSE technique improved image contrast of a linacgram. This indicates that the decrease in image quality resulting from the dual exposure, could be improved by expanding the gray scale. As a result, the improved technique will make it possible to compare the digitally reconstructed radiographs (DRR) and simulation image for evaluating the patient positioning error.