Purpose: To compare the dose distributions between three-dimensional (3D) and four-dimensional (4D) radiation treatment plans calculated by Ray-tracing or the Monte Carlo algorithm, and to highlight the difference of dose calculation between two algorithms for lung heterogeneity correction in lung cancers. Materials and Methods: Prospectively gated 4D CTs in seven patients were obtained with a Brilliance CT64-Channel scanner along with a respiratory bellows gating device. After 4D treatment planning with the Ray Tracing algorithm in Multiplan 3.5.1, a CyberKnife stereotactic radiotherapy planning system, 3D Ray Tracing, 3D and 4D Monte Carlo dose calculations were performed under the same beam conditions (same number, directions, monitor units of beams). The 3D plan was performed in a primary CT image setting corresponding to middle phase expiration (50%). Relative dose coverage, D95 of gross tumor volume and planning target volume, maximum doses of tumor, and the spinal cord were compared for each plan, taking into consideration the tumor location. Results: According to the Monte Carlo calculations, mean tumor volume coverage of the 4D plans was 4.4% higher than the 3D plans when tumors were located in the lower lobes of the lung, but were 4.6% lower when tumors were located in the upper lobes of the lung. Similarly, the D95 of 4D plans was 4.8% higher than 3D plans when tumors were located in the lower lobes of lung, but was 1.7% lower when tumors were located in the upper lobes of lung. This tendency was also observed at the maximum dose of the spinal cord. Lastly, a 30% reduction in the PTV volume coverage was observed for the Monte Carlo calculation compared with the Ray-tracing calculation. Conclusion: 3D and 4D robotic radiotherapy treatment plans for lung cancers were compared according to a dosimetric viewpoint for a tumor and the spinal cord. The difference of tumor dose distributions between 3D and 4D treatment plans was only significant when large tumor movement and deformation was suspected. Therefore, 4D treatment planning is only necessary for large tumor motion and deformation. However, a Monte Carlo calculation is always necessary, independent of tumor motion in the lung.
Son, Sang Jun;Park, Jang Pil;Kim, Min Jeong;Yoo, Suk Hyun
The Journal of Korean Society for Radiation Therapy
/
v.26
no.1
/
pp.107-114
/
2014
Purpose : The purpose of this study is evaluation for the applicability of O-MAR(Metal artifact Reduction for Orthopedic Implants)(ver. 3.6.0, Philips, Netherlands) in head & neck radiation treatment planning CT with metal artifact created by dental implant. Materials and Methods : All of the in this study's CT images were scanned by Brilliance Big Bore CT(Philips, Netherlands) at 120kVp, 2mm sliced and Metal artifact reduced by O-MAR. To compare the original and reconstructed CT images worked on RTPS(Eclipse ver 10.0.42, Varian, USA). In order to test the basic performance of the O-MAR, The phantom was made to create metal artifact by dental implant and other phantoms used for without artifact images. To measure a difference of HU in with artifact images and without artifact images, homogeneous phantom and inhomogeneous phantoms were used with cerrobend rods. Each of images were compared a difference of HU in ROIs. And also, 1 case of patient's original CT image applied O-MAR and density corrected CT were evaluated for dose distributions with SNC Patient(Sun Nuclear Co., USA). Results : In cases of head&neck phantom, the difference of dose distibution is appeared 99.8% gamma passing rate(criteria 2 mm / 2%) between original and CT images applied O-MAR. And 98.5% appeared in patient case, among original CT, O-MAR and density corrected CT. The difference of total dose distribution is less than 2% that appeared both phantom and patient case study. Though the dose deviations are little, there are still matters to discuss that the dose deviations are concentrated so locally. In this study, The quality of all images applied O-MAR was improved. Unexpectedly, Increase of max. HU was founded in air cavity of the O-MAR images compare to cavity of the original images and wrong corrections were appeared, too. Conclusion : The result of study assuming restrained case of O-MAR adapted to near skin and low density area, it appeared image distortion and artifact correction simultaneously. In O-MAR CT, air cavity area even turned tissue HU by wrong correction was founded, too. Consequentially, It seems O-MAR algorithm is not perfect to distinguish air cavity and photon starvation artifact. Nevertheless, the differences of HU and dose distribution are not a huge that is not suitable for clinical use. And there are more advantages in clinic for improved quality of CT images and DRRs, precision of contouring OARs or tumors and correcting artifact area. So original and O-MAR CT must be used together in clinic for more accurate treatment plan.
In this paper, we propose an DAP system for dose evaluation of medical and industrial X-ray generator. Based on the DAP measurement technique using the Ion-Chamber, the proposed system can clearly measure the exposure radiation dose generated by the diagnostic X-ray apparatus. The hardware part of the DAP measures the amount of charge in the air that is captured by an X-ray. The high-speed processing algorithm part for cumulative radiation dose measurement through microcurrent measures the amount of charge captured by X-ray at a low implementation cost (power) with no input loss. The wired/wireless transmission/reception protocol part synchronized with the operation of the X-ray generator improves communication speed. The PC-based control program part for interlocking and aging measures the amount of X-ray generated in real time and enables measurement graphs and numerical value monitoring through PC GUI. As a result of evaluating the performance of the proposed system in an accredited testing laboratory, the measured values using DAP increased linearly in each energy band (30, 60, 100, 150 kV). In addition, since the standard deviation of the measured value at the point of 4 division was ${\pm}1.25%$, it was confirmed that the DAP showed uniform measurements regardless of location. It was confirmed that the normal operation was not less than ${\pm}4.2%$ of the international standard.
The virtual compensator which are realized using a multileaf collimator(MLC) and three-dimensional radiation therapy Planning(3D RTP) system was designed. And the feasibility study of the virtual compensator was done to verify that it can do the function of the conventional compensator properly. As a model for the design of compensator, styrofoam phantom and mini water phantom were prepared to simulate the missing tissue area and the calculated dose distribution was produced through the 3D RTP system. The fluence maps which are basic materials for the design of virtual compensator were produced based on the dose distribution and the MLC leaf sequence file was made for the realization of the produced fluence map. Ma's algorithm were applied to design the MLC leaf sequence and all the design tools were programmed with IDL5.4. To verify the feasibility of the designed virtual compensator, the results of irradiation with or without a virtual compensator were analyzed by comparing the irradiated films inserted into the mini water phantom. The higher dose area produced due to the missing tissue was removed and intended regular dose distribution was achieved when the virtual compensator was applied.
Hyunjung Yeoh;Sung Hwan Hong;Chulkyun Ahn;Ja-Young Choi;Hee-Dong Chae;Hye Jin Yoo;Jong Hyo Kim
Korean Journal of Radiology
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v.22
no.11
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pp.1850-1857
/
2021
Objective: The purpose of this study was to assess whether a deep learning (DL) algorithm could enable simultaneous noise reduction and edge sharpening in low-dose lumbar spine CT. Materials and Methods: This retrospective study included 52 patients (26 male and 26 female; median age, 60.5 years) who had undergone CT-guided lumbar bone biopsy between October 2015 and April 2020. Initial 100-mAs survey images and 50-mAs intraprocedural images were reconstructed by filtered back projection. Denoising was performed using a vendor-agnostic DL model (ClariCT.AITM, ClariPI) for the 50-mAS images, and the 50-mAs, denoised 50-mAs, and 100-mAs CT images were compared. Noise, signal-to-noise ratio (SNR), and edge rise distance (ERD) for image sharpness were measured. The data were summarized as the mean ± standard deviation for these parameters. Two musculoskeletal radiologists assessed the visibility of the normal anatomical structures. Results: Noise was lower in the denoised 50-mAs images (36.38 ± 7.03 Hounsfield unit [HU]) than the 50-mAs (93.33 ± 25.36 HU) and 100-mAs (63.33 ± 16.09 HU) images (p < 0.001). The SNRs for the images in descending order were as follows: denoised 50-mAs (1.46 ± 0.54), 100-mAs (0.99 ± 0.34), and 50-mAs (0.58 ± 0.18) images (p < 0.001). The denoised 50-mAs images had better edge sharpness than the 100-mAs images at the vertebral body (ERD; 0.94 ± 0.2 mm vs. 1.05 ± 0.24 mm, p = 0.036) and the psoas (ERD; 0.42 ± 0.09 mm vs. 0.50 ± 0.12 mm, p = 0.002). The denoised 50-mAs images significantly improved the visualization of the normal anatomical structures (p < 0.001). Conclusion: DL-based reconstruction may enable simultaneous noise reduction and improvement in image quality with the preservation of edge sharpness on low-dose lumbar spine CT. Investigations on further radiation dose reduction and the clinical applicability of this technique are warranted.
Park Suk Won;Oh Do Hoon;Bae Hoon Sik;Cho Byung Chul;Park Jae Hong;Han Seung Hee
Radiation Oncology Journal
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v.20
no.1
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pp.68-72
/
2002
This study was done to implement intensity-modulated radiation therapy (IMRT) for the treatment of primary prostate cancer and to compare this technique with conventional treatment methods. A 72-year-old male patient with prostate cancer stage T2a was treated with IMRT delivered with dynamic multi-leaf collimation. Treatment was designed using an inverse planning algorithm, which accepts dose and dose-volume constraints for targets and normal structures. The IMRT plan was compared with a three-dimensional (3D) plan using the same 6 fields technique. Lower normal tissue doses and improved target coverage were achieved using IMRT at current dose levels, and facilitate dose escalation to further enhance locoregional control and organ movement during radiotherapy is an important issue of IMRT in prostate cancer.
The Monte Carlo method cannot have been used for routine treatment planning because of heavy time consumption for the acceptable accuracy. Since calculation time is proportional to particle histories, we can save time by decreasing the number of histories. However, a small number of histories can cause serious uncertainties. In this study, we proposed Monte Carlo dose computation time and uncertainty reduction method using specially designed filters and adaptive denoising process. Proposed algorithm was applied to 6 MV photon and 21 MeV electron dose calculations in homogeneous and heterogeneous phantoms. Filtering time was negligible comparing to Monte Carlo simulation time. The accuracy was improved dramatically in all situations and the simulation of 1 $\%$ to 10$\%$ number of histories of benchmark in photon and electron dose calculation showed the most beneficial result. The empirical reduction of necessary histories was about a factor of ten to fifty from the result.
Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.
Computed tomography (CT) has the problem of having more radiation exposure compared to other radiographic apparatus. There is a low-dose imaging technique for reducing exposure, but it has a disadvantage of increasing noise in the image. To compensate for this, various noise reduction algorithms have been developed that improve image quality while reducing the exposure dose of patients, of which the median modified Wiener filter (MMWF) algorithm that can be effectively applied to CT devices with excellent time resolution has been presented. The purpose of this study is to optimize the mask size of MMWF algorithm and to see the excellence of noise reduction of MMWF algorithm for existing algorithms. After applying the MMWF algorithm with each mask sizes set from the MASH phantom abdominal images acquired using the MATLAB program, which includes Gaussian noise added, and compared the values of root mean square error (RMSE), peak signal-to-noise ratio (PSNR), coefficient correlation (CC), and universal image quality index (UQI). The results showed that RMSE value was the lowest and PSNR, CC and UQI values were the highest in the 5 x 5 mask size. In addition, comparing Gaussian filter, median filter, Wiener filter, and MMWF with RMSE, PSNR, CC, and UQI by applying the optimized mask size. As a result, the most improved RMSE, PSNR, CC, and UQI values were showed in MMWF algorithms.
Oh, Hye Gyung;Son, Sang Jun;Park, Jang Pil;Lee, Je Hee
The Journal of Korean Society for Radiation Therapy
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v.31
no.1
/
pp.7-15
/
2019
Purpose: The purpose of this study is to evaluate beam delivery accuracy for small sized lung SBRT through experiment. In order to assess the accuracy, Eclipse TPS(Treatment planning system) equipped Acuros XB and radiochromic film were used for the dose distribution. Comparing calculated and measured dose distribution, evaluated the margin for PTV(Planning target volume) in lung tissue. Materials and Methods : Acquiring CT images for Rando phantom, planned virtual target volume by size(diameter 2, 3, 4, 5 cm) in right lung. All plans were normalized to the target Volume=prescribed 95 % with 6MV FFF VMAT 2 Arc. To compare with calculated and measured dose distribution, film was inserted in rando phantom and irradiated in axial direction. The indexes of evaluation are percentage difference(%Diff) for absolute dose, RMSE(Root-mean-square-error) value for relative dose, coverage ratio and average dose in PTV. Results: The maximum difference at center point was -4.65 % in diameter 2 cm size. And the RMSE value between the calculated and measured off-axis dose distribution indicated that the measured dose distribution in diameter 2 cm was different from calculated and inaccurate compare to diameter 5 cm. In addition, Distance prescribed 95 % dose($D_{95}$) in diameter 2 cm was not covered in PTV and average dose value was lowest in all sizes. Conclusion: This study demonstrated that small sized PTV was not enough covered with prescribed dose in low density lung tissue. All indexes of experimental results in diameter 2 cm were much different from other sizes. It is showed that minimized PTV is not accurate and affects the results of radiation therapy. It is considered that extended margin at small PTV in low density lung tissue for enhancing target center dose is necessary and don't need to constraint Maximum dose in optimization.
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