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Development of Film Verification as the QA of IMRT for Advanced Hepatoma Patients (간암 환자의 세기조절 방사선치료에서 임상적응 가능한 QA 기법의 개발)

  • Kim Myung-Se
    • Progress in Medical Physics
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    • v.17 no.1
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    • pp.40-46
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    • 2006
  • Hepatoma is one of 3 most common malignancies in Korea, the survival rate is not improved since last decades because of delayed diagnosis and limited treatment conditions. Radiation was one of treatment options but the impact on the survival is not remarkable. High dose exposure to target area was suggested for improved effect but low tolerance dose of normal liver tissue is the main limited factor. IMRT is the advanced form of 3DCRT, for focusing high dose on target with minimal dose to surrounding normal tissues. Motion of the tumor by respiration, cardiac pulsation and peristalsis is the main treatment harrier of IMRT for treatment of hepatoma patients. Development of QA technique for acceptable geometrical uncertainties and dose error on target volume is essential for IMRT in clinical treatment but proper QA technique is not yet developed. This study compared the verification film dosimetry with measured dose in phantom and calculated dose in planning computer on exactly same conditions of patient treatments. Within 3% dose differences between 3 groups were confirmed. We suggest that our verification QA technique is easy, economic, iterative and acceptable in clinical application for advanced hepatoma patients.

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Convolution-Superposition Based IMRT Plan Study for the PTV Containing the Air Region: A Prostate Cancer Case (Convolution-Superposition 알고리즘을 이용한 치료계획시스템에서 공기가 포함된 표적체적에 대한 IMRT 플랜: 전립선 케이스)

  • Kang, Sei-Kwon;Yoon, Jai-Woong;Park, Soah;Hwang, Taejin;Cheong, Kwang-Ho;Han, Taejin;Kim, Haeyoung;Lee, Me-Yeon;Kim, Kyoung Ju;Bae, Hoonsik
    • Progress in Medical Physics
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    • v.24 no.4
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    • pp.271-277
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    • 2013
  • In prostate IMRT planning, the planning target volume (PTV), extended from a clinical target volume (CTV), often contains an overlap air volume from the rectum, which poses a problem inoptimization and prescription. This study was aimed to establish a planning method for such a case. There can be three options in which volume should be considered the target during optimization process; PTV including the air volume of air density ('airOpt'), PTV including the air volume of density value one, mimicking the tissue material ('density1Opt'), and PTV excluding the air volume ('noAirOpt'). Using 10 MV photon beams, seven field IMRT plans for each target were created with the same parameter condition. For these three cases, DVHs for the PTV, bladder and the rectum were compared. Also, the dose coverage for the CTV and the shifted CTV were evaluated in which the shifted CTV was a copied and translated virtual CTV toward the rectum inside the PTV, thus occupying the initial position of the overlap air volume, simulating the worst condition for the dose coverage in the target. Among the three options, only density1Opt plan gave clinically acceptable result in terms of target coverage and maximum dose. The airOpt plan gave exceedingly higher dose and excessive dose coverage for the target volume whereas noAirOpt plan gave underdose for the shifted CTV. Therefore, for prostate IMRT plan, having an air region in the PTV, density modification of the included air to the value of one, is suggested, prior to optimization and prescription for the PTV. This idea can be equally applied to any cases including the head and neck cancer with the PTV having the overlapped air region. Further study is being under process.

The NCAM Land-Atmosphere Modeling Package (LAMP) Version 1: Implementation and Evaluation (국가농림기상센터 지면대기모델링패키지(NCAM-LAMP) 버전 1: 구축 및 평가)

  • Lee, Seung-Jae;Song, Jiae;Kim, Yu-Jung
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.18 no.4
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    • pp.307-319
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    • 2016
  • A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.