• Progress in Medical Physics
• /
• v.31 no.3
• /
• pp.54-62
• /
• 2020

Dose calculation algorithms play an important role in radiation therapy and are even the basis for optimizing treatment plans, an important feature in the development of complex treatment technologies such as intensity-modulated radiation therapy. We reviewed the past and current status of dose calculation algorithms used in the treatment planning system for radiation therapy. The radiation-calculating dose calculation algorithm can be broadly classified into three main groups based on the mechanisms used: (1) factor-based, (2) model-based, and (3) principle-based. Factor-based algorithms are a type of empirical dose calculation that interpolates or extrapolates the dose in some basic measurements. Model-based algorithms, represented by the pencil beam convolution, analytical anisotropic, and collapse cone convolution algorithms, use a simplified physical process by using a convolution equation that convolutes the primary photon energy fluence with a kernel. Model-based algorithms allowing side scattering when beams are transmitted to the heterogeneous media provide more precise dose calculation results than correction-based algorithms. Principle-based algorithms, represented by Monte Carlo dose calculations, simulate all real physical processes involving beam particles during transportation; therefore, dose calculations are accurate but time consuming. For approximately 70 years, through the development of dose calculation algorithms and computing technology, the accuracy of dose calculation seems close to our clinical needs. Next-generation dose calculation algorithms are expected to include biologically equivalent doses or biologically effective doses, and doctors expect to be able to use them to improve the quality of treatment in the near future.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.27 no.8
• /
• pp.665-675
• /
• 2016

With the development of active phased array radar technology in recent years, active phased array antennas, which digitally combine signals received from subarray units using dozens of digital receiver, have been developed. The beam characteristics are greatly affected by the shape of the subarray structure as well as the weight of subarray in digital beamforming. So in this paper, the method to generate subarray structures by using recursive element exchanging method and the method to optimize subarray structures that can minimize sidelobes of operating beams are proposed. Additionally it presents the result to find the optimized subarray structure to minimize the maximum sidelobe of monopulse beam and pencil multi-beam respectively or simultaneously which are commonly used for digital beamforming by applying the algorithm propsed in this paper.

• Progress in Medical Physics
• /
• v.23 no.1
• /
• pp.48-53
• /
• 2012

The pencil beam convolution (PBC) algorithms in radiation treatment planning system have been widely used to calculate the radiation dose. A new photon dose calculation algorithm, referred to as the anisotropic analytical algorithm (AAA), was released for use by the Varian medical system. The aim of this paper was to investigate the difference in dose calculation between the AAA and PBC algorithm using the intensity modulated radiation therapy (IMRT) plan for lung cancer cases that were inhomogeneous in the low density. We quantitatively analyzed the differences in dose using the eclipse planning system (Varian Medical System, Palo Alto, CA) and I'mRT matirxx (IBA, Schwarzenbruck, Germany) equipment to compare the gamma evaluation. 11 patients with lung cancer at various sites were used in this study. We also used the TLD-100 (LiF) to measure the differences in dose between the calculated dose and measured dose in the Alderson Rando phantom. The maximum, mean, minimum dose for the normal tissue did not change significantly. But the volume of the PTV covered by the 95% isodose curve was decreased by 6% in the lung due to the difference in the algorithms. The difference dose between the calculated dose by the PBC algorithms and AAA algorithms and the measured dose with TLD-100 (LiF) in the Alderson Rando phantom was -4.6% and -2.7% respectively. Based on the results of this study, the treatment plan calculated using the AAA algorithms is more accurate in lung sites with a low density when compared to the treatment plan calculated using the PBC algorithms.

• The Journal of Korean Society for Radiation Therapy
• /
• v.26 no.1
• /
• pp.11-19
• /
• 2014

Purpose : To derive the most appropriate factors by considering the effects of the major factors when applied to the optimization algorithm, thereby aiding the effective designing of a ideal treatment plan. Materials and Methods : The eclipse treatment planning system(Eclipse 10.0, Varian, USA) was used in this study. The PBC (Pencil Beam Convolution) algorithm was used for dose calculation, and the DVO (Dose Volume Optimizer 10.0.28) Optimization algorithm was used for intensity modulated radiation therapy. The experimental group consists of patients receiving intensity modulated radiation therapy for the head and neck cancer and dose prescription to two planned target volume was 2.2 Gy and 2.0 Gy simultaneously. Treatment plan was done with inverse dose calculation methods utilizing 6 MV beam and 7 fields. The optimal algorithm parameter of the established plan was selected based on volume dose-priority(Constrain), dose fluence smooth value and the impact of the treatment plan was analyzed according to the variation of each factors. Volume dose-priority determines the reference conditions and the optimization process was carried out under the condition using same ratio, but different absolute values. We evaluated the surrounding normal organs of treatment volume according to the changing conditions of the absolute values of the volume dose-priority. Dose fluence smooth value was applied by simply changing the reference conditions (absolute value) and by changing the related volume dose-priority. The treatment plan was evaluated using Conformal Index, Paddick's Conformal Index, Homogeneity Index and the average dose of each organs. Results : When the volume dose-priority values were directly proportioned by changing the absolute values, the CI values were found to be different. However PCI was $1.299{\pm}0.006$ and HI was $1.095{\pm}0.004$ while D5%/D95% was $1.090{\pm}1.011$. The impact on the prescribed dose were similar. The average dose of parotid gland decreased to 67.4, 50.3, 51.2, 47.1 Gy when the absolute values of the volume dose-priority increased by 40,60,70,90. When the dose smooth strength from each treatment plan was increased, PCI value increased to $1.338{\pm}0.006$. Conclusion : The optimization algorithm was more influenced by the ratio of each condition than the absolute value of volume dose-priority. If the same ratio was maintained, similar treatment plan was established even if the absolute values were different. Volume dose-priority of the treatment volume should be more than 50% of the normal organ volume dose-priority in order to achieve a successful treatment plan. Dose fluence smooth value should increase or decrease proportional to the volume dose-priority. Volume dose-priority is not enough to satisfy the conditions when the absolute value are applied solely.

• The Journal of Korean Society for Radiation Therapy
• /
• v.24 no.1
• /
• pp.23-30
• /
• 2012

Purpose: There was a problem with using MU verification programs for the reasons that there were errors of MU when using MU verification programs based on Pencil Beam Convolution (PBC) Algorithm with radiation treatment plans around lung using Analytical Anisotropic Algorithm (AAA). On this study, we studied the methods that can verify the calculated treatment plans using AAA. Materials and Methods: Using Eclipse treatment planning system (Version 8.9, Varian, USA), for each 57 fields of 7 cases of Lung Stereotactic Body Radiation Therapy (SBRT), we have calculated using PBC and AAA with dose calculation algorithm. By developing MU of established plans, we compared and analyzed with MU of manual calculation programs. We have analyzed relationship between errors and 4 variables such as field size, lung path distance of radiation, Tumor path distance of radiation, effective depth that can affect on errors created from PBC algorithm and AAA using commonly used programs. Results: Errors of PBC algorithm have showned $0.2{\pm}1.0%$ and errors of AAA have showned $3.5{\pm}2.8%$. Moreover, as a result of analyzing 4 variables that can affect on errors, relationship in errors between lung path distance and MU, connection coefficient 0.648 (P=0.000) has been increased and we could calculate MU correction factor that is A.E=L.P 0.00903+0.02048 and as a result of replying for manual calculation program, errors of $3.5{\pm}2.8%$ before the application has been decreased within $0.4{\pm}2.0%$. Conclusion: On this study, we have learned that errors from manual calculation program have been increased as lung path distance of radiation increases and we could verified MU of AAA with a simple method that is called MU correction factor.

• Proceedings of the Korean Society of Medical Physics Conference
• /
• 2002.09a
• /
• pp.68-73
• /
• 2002

In standard teletherapy, a treatment plan is generated with the aid of a treatment planning system, but it is common to perform an independent monitor unit verification calculation (MUVC). In exact analogy, we propose and demonstrate that a simple and accurate MUVC in Intensity Modulated Radiotherapy (IMRT) is possible. We introduce a concept of Modified Clarkson Integration (MCI). In MCI, we exploit the rotational symmetry of scattering to simplify the dose calculation. For dose calculation along a central axis (CAX), we first replace the incident IMRT fluence by an azimuthally averaged fluence. Second, the Clarkson Integration is carried over annular sectors instead of over pie sectors. We wrote a computer code, implementing the MCI technique, in order to perform a MUVC for IMRT purposes. We applied the code to IMRT plans generated by CORVUS. The input to the code consists of CORVUS plan data (e.g., DMLC files, jaw settings, MU for each IMRT field, depth to isocenter for each IMRT field), and the output is dose contribution by individual IMRT field to the isocenter. The code uses measured beam data for Sc, Sp, TPR, (D/Mu)$\_$ref/ and includes effects from MLC transmission, and radiation field offset. On a 266 MHZ desktop computer, the code takes less than 15 sec to calculate a dose. The doses calculated with MCI algorithm agreed within +/- 3% with the doses calculated by CORVUS, which uses a 1cm x 1cm pencil beam in dose calculation. In the present version of MCI, skin contour variations and inhomogeneities were neglected.

• Progress in Medical Physics
• /
• v.30 no.1
• /
• pp.1-6
• /
• 2019

Purpose: This study conducts a comparative evaluation of the skin dose in CyberKnife (CK) and Helical Tomotherapy (HT) to predict the accurate dose of radiation and minimize skin burns in head-and-neck stereotactic body radiotherapy. Materials and Methods: Arbitrarily-defined planning target volume (PTV) close to the skin was drawn on the planning computed tomography acquired from a head-and-neck phantom with 19 optically stimulated luminescent dosimeters (OSLDs) attached to the surface (3 OSLDs were positioned at the skin close to PTV and 16 OSLDs were near sideburns and forehead, away from PTV). The calculation doses were obtained from the MultiPlan 5.1.2 treatment planning system using raytracing (RT), finite size pencil beam (FSPB), and Monte Carlo (MC) algorithms for CK. For HT, the skin dose was estimated via convolution superposition (CS) algorithm from the Tomotherapy planning station 5.0.2.5. The prescribed dose was 8 Gy for 95% coverage of the PTV. Results and Conclusions: The mean differences between calculation and measurement values were $-1.2{\pm}3.1%$, $2.5{\pm}7.9%$, $-2.8{\pm}3.8%$, $-6.6{\pm}8.8%$, and $-1.4{\pm}1.8%$ in CS, RT, RT with contour correction (CC), FSPB, and MC, respectively. FSPB showed a dose error comparable to RT. CS and RT with CC led to a small error as compared to FSPB and RT. Considering OSLDs close to PTV, MC minimized the uncertainty of skin dose as compared to other algorithms.

• The Journal of Korean Society for Radiation Therapy
• /
• v.26 no.2
• /
• pp.207-216
• /
• 2014

Purpose : We present a method to reduce this gap and complete the treatment plan, to be made by the re-optimization is performed in the same conditions as the initial treatment plan different from Monaco treatment planning system. Materials and Methods : The optimization is carried in two steps when performing the inverse calculation for volumetric modulated radiation therapy or intensity modulated radiation therapy in Monaco treatment planning system. This study was the first plan with a complete optimization in two steps by performing all of the treatment plan, without changing the optimized condition from Step 1 to Step 2, a typical sequential optimization performed. At this time, the experiment was carried out with a pencil beam and Monte Carlo algorithm is applied In step 2. We compared initial plan and re-optimized plan with the same optimized conditions. And then evaluated the planning dose by measurement. When performing a re-optimization for the initial treatment plan, the second plan applied the step optimization. Results : When the common optimization again carried out in the same conditions in the initial treatment plan was completed, the result is not the same. From a comparison of the treatment planning system, similar to the dose-volume the histogram showed a similar trend, but exhibit different values that do not satisfy the conditions best optimized dose, dose homogeneity and dose limits. Also showed more than 20% different in comparison dosimetry. If different dose algorithms, this measure is not the same out. Conclusion : The process of performing a number of trial and error, and you get to the ultimate goal of treatment planning optimization process. If carried out to optimize the completion of the initial trust only the treatment plan, we could be made of another treatment plan. The similar treatment plan could not satisfy to optimization results. When you perform re-optimization process, you will need to apply the step optimized conditions, making sure the dose distribution through the optimization process.