환자맞춤형 4D 사면체 전산팬텀을 이용한 4D 몬테칼로 선량계산의 정확성 평가

한민철,염연수,김찬형,김성훈,Jason W. Sohn 대한방사선방어학회 2014 대한방사선방어학회 학술발표회 논문요약집 Vol.2014 No.11

Design and Development of Spine Phantom to Verify Dosimetric Accuracy of Stereotactic Body Radiation Therapy using 3D Printer

Seu-Ran Lee,Min-Young Lee,Min-Joo Kim,So-Hyun Park,Ji-Hye Song,Jason W. Sohn,Tae-Suk Suh 대한방사선방어학회 2015 대한방사선방어학회 학술발표회 논문요약집 Vol.2015 No.10

Computer Assisted EPID Analysis of Breast Intrafractional and Interfractional Positioning Error

Sohn Jason W.,Mansur David B.,Monroe James I.,Drzymala Robert E.,Jin Ho-Sang,Suh Tae-Suk,Dempsey James F.,Klein Eric E. Korean Society of Medical Physics 2006 의학물리 Vol.17 No.1

유방암 환자의 방사선치료에 있어 치료도중(intrafractional) 및 분할 치료 간(intefractional)에 발생되는 오차를 측정하는 자동분석소프트웨어를 개발하였다. 오차 분석 결과는 3차원 입체조형 방사선치료를 임상에 적용하기에 앞서 적절한 치료계획용적(Planning Target Volume, PTV)을 설정하는 데 있어 매우 중요하다. 본 연구에서는 전자포탈영상장치(Electrical Portal imaging Device, EPID)로써 Portal Vision LC250 액체 충전형 이온화 검출기를 사용하였다(fast frame-averaging 모드, 초당 1.4 프레임, 256X256 픽셀). 12명의 환자에 대해 최소 7일 이상씩 영상을 획득하였다. 매 치료마다 평균 8 내지 9개의 영상을 각 빔에 대해 얻었다(분당 400 MU 선량률). 총 2,931 (720 측정을 포함하는)개의 영상을 정량적으로 분석할 수 있는 자동화 영상 분석 소프트웨어를 개발하였다. 이를 통해 호흡으로 인해 발생하는 치료도중 오차와 분할 치료간 발생하는 분할치료오차의 표준편차($\sigma$)들을 계산하였다. 신뢰 구간 95%로 임상표적체적(Clinical Target Volume, CTV)을 포함할 수 있는 PTV 마진은 $2\;(1.96\;{\sigma})$으로 계산되었다. 주로 호흡으로 인해 유발되는 치료도중오차를 보상하기 위해 필요한 PTV 마진은 2 mm에서 4 mm이었다. 반면에 분할 치료간 오차를 보상하기위해 필요한 PTV 마진은 7 mm에서 31 mm이었다. 12명의 환자에 대한 전체 평균오차는 17 mm이었다. 분할치료 간 오차는 호흡에 의해 유발되는 치료도중 오차에 비해 2배에서 15배까지 더 크게 나타났다. 유방암 치료에 있어 3차원 입체정형조사나 세기조절방사선치료(Intensity Modulated Radiation Therapy, IMRT)를 적용하기에 앞서 반드시 셋업 오차의 크기를 측정하여 PTV에 적절히 반영되어야 한다. 유방에 대한 3차원 입체정형조사나 세기조절방사선치료를 위해 반드시 필요한 것은 아니지만, 큰 PTV 마진을 줄여주기 위해서는 영상유도방사선치료(Image Guided Radiation Therapy, IGRT)가 매우 유용하게 이용될 수 있다. 전자포탈영상장치 들은 본 보고서에서 기술한 바와 같은 자동분석소프트웨어를 반드시 포함하여야 한다. 이를 통해 수많은 EPID 영상들을 자동화 처리하고 오차분석을 시행함으로써 각 병원의 임상적용 방법 및 환경에 따라 상이하게 나타날 수 있는 오차의 크기를 감안한 적절한 PTV마진을 구하는데 도움을 얻을 수 있다. 이러한 장치들은 또한 최소의 노력으로 환자 치료를 관찰할 수 있는 귀중한 정보를 제공해 준다. Automated analysis software was developed to measure the magnitude of the intrafractional and interfractional errors during breast radiation treatments. Error analysis results are important for determining suitable planning target volumes (PTV) prior to Implementing breast-conserving 3-D conformal radiation treatment (CRT). The electrical portal imaging device (EPID) used for this study was a Portal Vision LC250 liquid-filled ionization detector (fast frame-averaging mode, 1.4 frames per second, 256X256 pixels). Twelve patients were imaged for a minimum of 7 treatment days. During each treatment day, an average of 8 to 9 images per field were acquired (dose rate of 400 MU/minute). We developed automated image analysis software to quantitatively analyze 2,931 images (encompassing 720 measurements). Standard deviations ($\sigma$) of intrafractional (breathing motion) and intefractional (setup uncertainty) errors were calculated. The PTV margin to include the clinical target volume (CTV) with 95% confidence level was calculated as $2\;(1.96\;{\sigma})$. To compensate for intra-fractional error (mainly due to breathing motion) the required PTV margin ranged from 2 mm to 4 mm. However, PTV margins compensating for intefractional error ranged from 7 mm to 31 mm. The total average error observed for 12 patients was 17 mm. The intefractional setup error ranged from 2 to 15 times larger than intrafractional errors associated with breathing motion. Prior to 3-D conformal radiation treatment or IMRT breast treatment, the magnitude of setup errors must be measured and properly incorporated into the PTV. To reduce large PTVs for breast IMRT or 3-D CRT, an image-guided system would be extremely valuable, if not required. EPID systems should incorporate automated analysis software as described in this report to process and take advantage of the large numbers of EPID images available for error analysis which will help Individual clinics arrive at an appropriate PTV for their practice. Such systems can also provide valuable patient monitoring information with minimal effort.

Independent dose validation system for Gamma Knife radiosurgery, using a DICOM-RT interface and Geant4

Choi, Hyun Joon,Chung, Hyun-Tai,Sohn, Jason W.,Min, Chul Hee Elsevier 2018 PHYSICA MEDICA Vol.51 No.-

<P><B>Abstract</B></P> <P>Leksell GammaPlan was specifically designed for Gamma Knife (GK) radiosurgery planning, but it has limited accuracy for estimating the dose distribution in inhomogeneous areas, such as the embolization of arteriovenous malformations. We aimed to develop an independent patient dose validation system based on a patient-specific model, constructed using a DICOM-RT interface and the Geant4 toolkit. Leksell Gamma Knife Perfexion was designed in Geant4.10.00 and includes a DICOM-RT interface. Output factors for each collimator in a sector and dose distributions in a spherical water phantom calculated using a Monte Carlo (MC) algorithm were compared with the output factors calculated by the tissue maximum ratio (TMR) 10 algorithm and dose distributions measured using film, respectively. Studies using two types of water phantom and two patient simulation cases were evaluated by comparing the dose distributions calculated by the MC, the TMR and the convolution algorithms. The water phantom studies showed that if the beam size is small and the target is located in heterogeneous media, the dose difference could be up to 11%. In the two patient simulations, the TMR algorithm overestimated the dose by about 4% of the maximum dose if a complex and large bony structure was located on the beam path, whereas the convolution algorithm showed similar results to those of the MC algorithm. This study demonstrated that the in-house system could accurately verify the patient dose based on full MC simulation and so would be useful for patient cases where the dose differences are suspected.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The Geant4 model of Gamma Knife treatment and its validation are presented. </LI> <LI> The clinical application of the Geant4 model of Gamma Knife is provided. </LI> <LI> The necessity of an independent patient dose validation system is presented. </LI> </UL> </P>

Preclinical investigation for developing injectable fiducial markers using a mixture of BaSO4 and biodegradable polymer for proton therapy.

Ahn, Sang Hee,Gil, Moon Soo,Lee, Doo Sung,Han, Youngyih,Park, Hee Chul,Sohn, Jason W,Kim, Hye Yeong,Shin, Eun Hyuk,Yu, Jeong Il,Noh, Jae Myoung,Cho, Jun Sang,Ahn, Sung Hwan,Choi, Doo Ho Published for the American Association of Physicis 2015 Medical physics Vol.42 No.5

<P>The aim of this study is to investigate the use of mixture of BaSO4 and biodegradable polymer as an injectable nonmetallic fiducial marker to reduce artifacts in x-ray images, decrease the absorbed dose distortion in proton therapy, and replace permanent metal markers.</P>

Quantitative Analysis Tools and Digital Phantoms for Deformable Image Registration Quality Assurance

Kim, Haksoo,Park, Samuel B.,Monroe, James I.,Traughber, Bryan J.,Zheng, Yiran,Lo, Simon S.,Yao, Min,Mansur, David,Ellis, Rodney,Machtay, Mitchell,Sohn, Jason W. SAGE Publications 2015 Technology in cancer research & treatment Vol.14 No.4

Continuously Deforming 4D Voxel Phantom for Realistic Representation of Respiratory Motion in Monte Carlo Dose Calculation

Han, Min Cheol,Seo, Jeong Min,Lee, Se Hyung,Kim, Chan Hyeong,Yeom, Yeon Soo,Nguyen, Thang Tat,Choi, Chansoo,Kim, Seonghoon,Jeong, Jong Hwi,Sohn, Jason W. Professional Technical Group on Nuclear Science 2016 IEEE transactions on nuclear science Vol.63 No.6

<P>We propose a new type of computational phantom, the '4D voxel phantom,' for realistic modeling of continuous respiratory motion in Monte Carlo dose calculation. In this phantom, continuous respiratory motion is realized by linear interpolation of the deformation vector fields (DVFs) between the neighboring original phases in the 4D CT data of a patient and by subsequent application of the DVFs to the phase images or to the reference image to produce multiple inter-phase images between the neighboring original phase images. A 4D voxel phantom is a combination of high-temporal-resolution voxel phantoms and on-the-fly dose registration to the reference phase image. In the course of particle transport simulation, the dose or deposited energy is directly registered to the reference phase image on-the-fly (i.e., after each event) using a DVF for dose registration. In the present study, we investigated two methods-DRP (DIR [deformable image registration] with respect to Reference Phase image) and DNP (DIR with respect to Neighboring original Phase image) - for production of multiple inter-phase images or high-temporal-resolution voxel phantoms. Utilizing these two methods, two 4D voxel phantoms each with 100 phases were produced from the original 10-phase images of the 4D CT data of a real patient in order to compare the two methods and to test the feasibility of the 4D voxel phantom methodology in general. We found that it is possible to produce a 4D voxel phantom very rapidly (i.e., <40 min on a 4-core personal computer for a 100-phase phantom) in a fully automated process. The dose calculation results showed that the constructed 100-phase 4D voxel phantoms provide cumulative-dose distributions very similar to those of the conventional 10-phase approach for stationary proton-beam irradiation. The passing rates of the dose distributions of the 4D voxel phantoms were higher than 99.9% according to the 3% and 3 mm gamma criteria, which results validate the 4D voxel phantom methodology. The point- and dose-tracking analysis data showed that the DRP method, which uses the minimal number of DIR operations but uses inverse DVFs, provides significantly better results than those of the DNP method, which uses only DIR to generate the DVFs for inter-phase image generation and dose registration. The present study also showed that the computation time does not significantly increase when the number of phases in the 4D voxel phantom is increased for more realistic representation of continuous respiratory motion; the only significant increase is in the memory occupancy, which grows almost linearly with the number of phases.</P>