• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.2
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• pp.63-67
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• 2015

Purpose Among various causes that influence image quality degradation, various methods for decrease in Artifact occurred by respiration of patients are being used. Among them, this study intended to evaluate CTAC Shift correction method and additional scan compare to the Scan(Q static scan) using respiratory gated system. Materials and Methods This study was conducted on 10 patients, and used PET-CT Discovery 710 (GE Healthcare, MI, USA) and Varian's RPM system. 5.18 Mbq per kg of $^{18}F$-FDG was injected on patients, asked them to take a rest for 1 hour in the bed, and conducted test after urination. Images were visualized through Q static scan, CTAC Shift correction method, Additional scan based on the Whole body scan(WBS) with Artifact. Decrease in Artifact was compared in each image, conducted Gross Evalution, and measured changes of SUVmax. Results For image obtained through the CTAC Shift correction method through WBS with Artifact, 12~56%, Q static scan image showed 17~54% of change rate and Additional Scan showed -27~46% of change rate. In Blind Test, the CTAC Shift correction image showed the highest point with 4 points, Q static scan image showed 3.5 points, and Additional scan image showed 3.4 points. The standardized WBS scan through Oneway ANOVA and three types of Scan method showed significant difference(p<0.05), and did not show significant difference between the three Scan methods(p>0.05). However, the three Scan methods showed significant difference in Blind test. Conclusion Additional scan and Q static scan require more time than the CTAC Shift correction method, there is concern about excessive exposure to patients by CT rescan and Q static scan is difficult to apply on patients with inconsistent respiration or irregular respiration cycle due to pain. For CTAC Shift correction method, limited correction is possible and the range is limited as well. It is considered as a useful method of improving diagnostic value when hospitals use the system appropriately and develop various advantageous factors of each method.

• Progress in Medical Physics
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• v.20 no.3
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• pp.132-138
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• 2009

Studies on target motion in 4-dimensional radiotherapy are being world-widely conducted to enhance treatment record and protection of normal organs. Prediction of tumor motion might be very useful and/or essential for especially free-breathing system during radiation delivery such as respiratory gating system and tumor tracking system. Neural network is powerful to express a time series with nonlinearity because its prediction algorithm is not governed by statistic formula but finds a rule of data expression. This study intended to assess applicability of neural network method to predict tumor motion in 4-dimensional radiotherapy. Scaled Conjugate Gradient algorithm was employed as a learning algorithm. Considering reparation data for 10 patients, prediction by the neural network algorithms was compared with the measurement by the real-time position management (RPM) system. The results showed that the neural network algorithm has the excellent accuracy of maximum absolute error smaller than 3 mm, except for the cases in which the maximum amplitude of respiration is over the range of respiration used in the learning process of neural network. It indicates the insufficient learning of the neural network for extrapolation. The problem could be solved by acquiring a full range of respiration before learning procedure. Further works are programmed to verify a feasibility of practical application for 4-dimensional treatment system, including prediction performance according to various system latency and irregular patterns of respiration.

• Progress in Medical Physics
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• v.25 no.2
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• pp.100-109
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• 2014

In stereotactic body radiotherapy (SBRT), the accurate location of treatment sites should be guaranteed from the respiratory motions of patients. Lots of studies on this topic have been conducted. In this letter, a new verification method simulating the real respiratory motion of heterogenous treatment regions was proposed to investigate the accuracy of lung SBRT for Volumetric Modulated Arc Therapy. Based on the CT images of lung cancer patients, lung phantoms were fabricated to equip in $QUASAR^{TM}$ respiratory moving phantom using 3D printer. The phantom was bisected in order to measure 2D dose distributions by the insertion of EBT3 film. To ensure the dose calculation accuracy in heterogeneous condition, The homogeneous plastic phantom were also utilized. Two dose algorithms; Analytical Anisotropic Algorithm (AAA) and AcurosXB (AXB) were applied in plan dose calculation processes. In order to evaluate the accuracy of treatments under respiratory motion, we analyzed the gamma index between the plan dose and film dose measured under various moving conditions; static and moving target with or without gating. The CT number of GTV region was 78 HU for real patient and 92 HU for the homemade lung phantom. The gamma pass rates with 3%/3 mm criteria between the plan dose calculated by AAA algorithm and the film doses measured in heterogeneous lung phantom under gated and no gated beam delivery with respiratory motion were 88% and 78%. In static case, 95% of gamma pass rate was presented. In the all cases of homogeneous phantom, the gamma pass rates were more than 99%. Applied AcurosXB algorithm, for heterogeneous phantom, more than 98% and for homogeneous phantom, more than 99% of gamma pass rates were achieved. Since the respiratory amplitude was relatively small and the breath pattern had the longer exhale phase than inhale, the gamma pass rates in 3%/3 mm criteria didn't make any significant difference for various motion conditions. In this study, the new phantom model of 4D dose distribution verification using patient-specific lung phantoms moving in real breathing patterns was successfully implemented. It was also evaluated that the model provides the capability to verify dose distributions delivered in the more realistic condition and also the accuracy of dose calculation.