보고서 정보
주관연구기관 |
분당서울대학교병원 |
보고서유형 | 2단계보고서 |
발행국가 | 대한민국 |
언어 |
한국어
|
발행년월 | 2013-02 |
과제시작연도 |
2012 |
주관부처 |
교육과학기술부 Ministry of Education and Science Technology(MEST) |
등록번호 |
TRKO201400022133 |
과제고유번호 |
1345169998 |
사업명 |
기초공동연구소 |
DB 구축일자 |
2014-11-10
|
키워드 |
영상융합.영상분할.종양볼륨.다중영상.방사선수술및치료.image registration.segmentation.target tumor volume.stereotactic radiosurgery.radiation therapy.
|
DOI |
https://doi.org/10.23000/TRKO201400022133 |
초록
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◦정량적 방사선치료계획 수립을 위한 다중영상기반 생물학적 영상특성을 분석하여 PET 영상융합 및 영상분할 최적화 프로토콜을 검증하였으며, 대사 영상의 특징적 파라미터로 종양볼륨최적화를 구현하였고 종양볼륨분할의 방향성을 Tractography를 통해 fiber tract을 고려하여 종양볼륨최적화 기술을 구현하였으며, 장기움직임을 고려한 4D PET/CT에서 영상융합을 적용한 Dynamic PET분석에 의해 종양볼륨최적화와 방사선치료 및 방사선 수술최적화 수행을 위한 Dose volume histogram을 비교하였고, 영상융합하여 분
◦정량적 방사선치료계획 수립을 위한 다중영상기반 생물학적 영상특성을 분석하여 PET 영상융합 및 영상분할 최적화 프로토콜을 검증하였으며, 대사 영상의 특징적 파라미터로 종양볼륨최적화를 구현하였고 종양볼륨분할의 방향성을 Tractography를 통해 fiber tract을 고려하여 종양볼륨최적화 기술을 구현하였으며, 장기움직임을 고려한 4D PET/CT에서 영상융합을 적용한 Dynamic PET분석에 의해 종양볼륨최적화와 방사선치료 및 방사선 수술최적화 수행을 위한 Dose volume histogram을 비교하였고, 영상융합하여 분석한 PET과 CT영상에서 호흡주기에 따른 종양모델의 hysteresis와 영상융합을 통해 호흡주기를 반영한 종양볼륨 및 종양움직임의 hysteresis로 결과를 도출하였다. 4D dynamic PET/CT에서 호흡조절 40% 또는 90%등에 정의된 시간의 phase에서만 트리거 신호를 발생시켜 데이터만을 수집하여 4D PET/CT 데이터를 획득하고 normalized mutual information 방법으로 영상융합하여 gross tumor volume (GTV)설정하면 정확한 방사선수술 및 방사선 치료에 유용하게 적용될 것임.
◦PET 영상융합을 이용한 대사영상의 종양특징 파라미터를 추출하여 뇌 확산영상과 대사영상 그리고 T2강조영상 등 다중영상융합기반으로 한 종양 볼륨최적화로 방사선 수술 및 방사선치료최적화에 적용하고자함.
◦종양볼륨 segmentation의 문제점은 종양이 갖고 있는 방향성의 propagation과 direction이 3D surface에서 어떻게 표현되느냐에 따라 결정되며 Tractography 는 fiber tract의 stream line으로 fiber tract 이종양조직을 만나면 fiber tract의 stream line의 방향이 바뀌는 특성을 갖고 있어서 Tumor volume optimize 하는 최적의 종양볼륨시각화 구현기술로 적용하였고 뇌정위적 방사선수술최적화를 수행하기위한 뇌조직 백질의 tractography분석과 Diffusion tensor imaging을 활용한 종양볼륨분석은 높은 sensitivity를 보이며 종양볼륨 분석과 segmentation 수행을 위한 높은 대조도를 보임.
◦CT상에 나타난 종양볼륨으로 최적화하기 어려운 두경부 암종에서는 정상 조직의 dose를 증가시킬 필요없이 hypoxic tumor volume으로 영상융합에 의한 target의 최외경계를 구분하여 방사선치료나 수술시의 dose를 결정할 수 있으며 hypoxic tumor PET tracer imaging 으로는 F-18 fluoromisonidazole (FMISO)가 대표적이며 hypoxic tumor cell은 두경 부암과 폐암에서 특이하게 반응하며 hypoxic PET영상획득으로 tumor volume을 종양의 target으로 설정하여 방사선치료나 방사선 수술을 위한 dose calculation에서 방사선량을 최적화 하고자함.
◦PET 과 Diffusion 및 T2 강조영상융합에서 종양볼륨비교분석은 GTV에서 uniform planning 파라미터를 적용할 수 있는 영상기준으로 tissue blood ratio를 1.3으로 결정함.
◦동적 4D-PET 영상에서는 병변의 SUV값의 향상과 대조도의 증가를 확인할 수 있다. 정적 영상과 비교하여 병변의 SUV 값을 160% 향상시키고, 병변의 부피를 34% 감소시킬 수 있다. 정적 PET 기반으로 설정한 tumor delineation은 SUV(Source Uptake Value)로 tumor-to-background signal ratio에 의해 결정된 maximal SUV값으로 결정한다. 정적 PET에서 측정된 volume과 diameter는 동적 PET analysis에 의해 분석된 결과보다 장기움직임에 의한 hysteresis분석에서 높은 차이를 보였다. 동적 PET analysis는 volumes (P = 0.357), diameters (P = 0.423) 측정에서 significant differences를 보이지 않았고 평균오차는 diameter 측정에서 0.85±1.48%, volume측정에서 3.60±1.90%, 정적 PET SUV analysis에서는 significant differences를 보이며 volumes 측정에서 2.56±2.56%(P=0.003), diameters 측정에서는 6.67±0.62%(P=0.003)으로 통계적으로 유의미한 결과를 보였다. normalized mutual information 방법으로 동적 PET data와 CT 영상 융합하여 gross tumor volume (GTV)설정하면 정확한 방사선수술과 방사선 치료 수행을 수행하는데 유용하게 활용될 것으로 예측됨.
◦방사선수술과 방사선치료의 표적 설정에 있어 영상융합은 매우 중요하며 동적 PET/CT의 진단의 예민도는 87~90%, 특이도 80~93%를 보였으며, 방사선수술 및 방사선치료에 종양볼륨을 결정하여 방사선치료 계획 수립을 할 수 있는 결정인자이며 다중영상융합하면 target volume을 보다 정확하게 결정할 수 있으며 생물학적 영상특성을 방사선수술 및 방사선치료기술에 통합하면 정확한 방사선수술과 방사선 치료 수행을 수행하는데 유용하게 활용될 것으로 예측됨.
Abstract
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Non-invasive assessment of tumor delineation and characterization of tumor tissue using the biological multimodal imaging methods are important for effective treatment selection, planning and monitoring in radiation therapy and stereotactic radiosurgery. Accurate target definition is one of the most
Non-invasive assessment of tumor delineation and characterization of tumor tissue using the biological multimodal imaging methods are important for effective treatment selection, planning and monitoring in radiation therapy and stereotactic radiosurgery. Accurate target definition is one of the most important factors to reduce complications because, it can reduce unwanted radiation to surrounding normal tissue. The target of radiosurgery and radiation therapy are primarily visualized by radiological studies such as computed tomography(CT), magnetic resonance imaging(MRI) and positron emission tomography (PET). Owing to this, the accuracy of treatment largely depends on multimodality image registration and neuroimaging technology. Radiotherapy is one of the most important treatment modalities for locally advanced. Although dose intensification strategies, such as concomitant radiation, altered and dose escalated schemes have been shown to improve the tumor local control and survival and their clinical implementations remain problematic. It might result in unacceptable short term and long term toxicities when dose intensification is considered. Therefore, the recent development of additional techniques, such as intensity modulated radiotherapy, image guided radiotherapy and stereotactic radiosurgery offers new perspectives by providing high precision in radiation dose delivery. They require, however, a thorough selection and delineation of the tumor volumes, particularly the gross tumor volume (GTV). CT is the reference imaging modality for the treatment planning, F18-fluorodeoxyglucose (FDG) PET and diffusion tensor images are functional imaging modality that provides higher sensitivity and specificity than CT for the detection of primary tumor. In radiation therapy, FDG-PET has already been shown to significantly modify the size, location, and shape of the primary tumor, leading to the opportunity to adapt the treatment planning. PET can provide insights in the presence and distribution of malignant tissue due todifferences in biochemical properties. FDG labeled with the positron emitting radioactive isotope fluorine-18 [18F],is the most used biological PET imaging tracer in oncology, showing enhanced uptake within tumor tissue due to increased glucose uptake and glycolysis within malignant cells.
Multimodality integration of MRI and FDG-PET in the treatment planning remains technically complex, especially for the accurate definition of the tumor boundaries. Current imaging techniques such as CT and MRI detect only the part of the tumor with a high concentration of tumor cells. The radiotherapy is conventionally applied to a margin of about 2cm around the visible tumor which is a very rough approximation of the probable location of tumor cells. To improve the therapeutic outcome, more accurate prediction of the tumor invasion margin is necessary. In conclusion, normalized mutual information registration method is more robust and the gradient based segmentation was most accurate and consistent PET tumor segmentation. More recent approaches use anisotropic diffusion along white matter tract as given by the diffusion tensor to tumor control.
Diffusion tensor imaging (DTI) is a good for the evaluation of tumor control and improvement of tumor margin although, the limitations of this study cannot exclude some degree of partial volume effect on the measurements, heterogeneity and susceptibility artifacts might have impaired study. Diffusion tensor tractography, one of the major recent advances in neuroimaging, enabled clear visualization of various fibers inside the white matter of the brain, which was not visualized by conventional imaging modalities. Although the pointed limitation of tractography is its reliability to targeting for radiosurgery and radiation therapy using multimodality image registration that there are help to delineation of tumor volume. On the other hand, such a shift does not occur in the setting of integration of tractography into radiosurgery. We suggested to be potentially reduced by integrating DTI into treatment planning of radiosurgery. Two major concerns regarding were i) whether integration of tractography significantly reduced morbidity and ii) whether alteration of dose planning using tractography compromised. Radiation therapy and radiosurgery were quite dependent on multimodal image registration because the target of radiosurgery was solely defined by imaging studies. Thus, more accurate target definition enabled by advances in multimodal image registration truly resulted in safer treatment.
Multimodality imaging registration with advances in CT, MRI and PET themselves achieved not only images of higher resolution but also imaging studies of completely different quality such as metabolic and functional information. Technological progress of treatment planning radiosurgery made it possible to utilize wide variety of multimodality image registration for process of target definition in planning. PET enabled access to metabolic information of lesions at the time of treatment planning for radiosurgery and we utilized PET in patients with malignant tumors to visualize the possibly active component among diffuse enhancement on MRI. PET/CT scans can be acquired in two modes, static and dynamic. In static scans, accounting for the majority of PET scans made nowadays, the activity of the tracer is counted over a single fixed period. In most cases, it delineates the tumor based on the PET/CT images, but recently new auto delineation methods have become increasingly important.
Automatic tumor delineation can be based on a fixed standardized uptake value (SUV) e.g. 2.5, being a fixed percentage of the maximum SUV (e.g. 42% of SUVmax) or a variable threshold based on the tumor-to-background ratio. In this case a certain tumor-to-background ratio is coupled to a certain threshold percentage of the maximum SUV. In the case of a 4D dynamic scan, the activity of the tracer is measured for each voxel at multiple points in timep hase with respiratory period, resulting in a time activity curve. In static PET analysis versus dynamic PET analysis, the tumor contour resulting from static SUV analysis was found to be significantly larger (30.2±48.0%) than the tumor contour resulting from dynamic PET analysis (P=0.018). A mean concordance index of 73% was found when comparing both contours. Ninety-two percent of the dynamic PET contour was present within the contour resulting from static SUV analysis, whereas 79% of the static SUV tumor contour was present within the contour resulting from dynamic PET analysis. In dynamic PET analysis, showed no significant differences between the volumes (P = 0.357) and diameters (P = 0.423) compared to the true volume and diameter of the phantom insert. Mean errors of 0.85±1.48% for diameter and 3.60±1.90% for volume were found. For static SUV analysis, significant differences of 2.56±2.56% (P=0.003) and 6.67±0.62% (P=0.003) were respectively found target diameter and volume in comparison to the true volume and diameter. Registered PET/CT image with anatomical and functional information have improved medical diagnosis and interpretation. This multimodal image registration has resulted in more precise localization and characterization of sites of radio-tracer uptake. However, a motion during whole-body imaging has been recognized as a source of image quality degradation and reduced the quantitative accuracy of PET/CT study. The respiratory motion problem is more challenging in combined PET/CT imaging. An accurate spatial registration of PET and CT image sets is a prerequisite for accurate diagnosis and SUV measurement. Correcting for the spatial mismatch caused by motion represents a particular challenge for the requisite registration accuracy as a result of differences in PET/CT image.
Therefore, the more effective brain radiation therapy and radiosurgery will be continued in the future as long as progress of multimodality image registration. Optimized tumor volume delineation was suggested relying multimodality image registration and segmentation, surely when they are poorly identifiable and ambiguous tumor biological effect.
목차 Contents
- 표지 ... 1
- 제출문 ... 2
- 보고서 요약서 ... 3
- 요약문 ... 7
- SUMMARY ... 11
- CONTENTS ... 15
- 목차 ... 16
- 제 1 장 연구개발과제의 개요 ... 17
- 1. 연구개발의 목적 ... 17
- 2. 연구개발의 필요성 ... 17
- (1) 기술적 측면 ... 19
- (2) 경제ㆍ산업적 측면 ... 20
- 제 2 장 국내외 기술개발 현황 ... 23
- 1. 국내 연구 ... 23
- 2. 국외 연구 ... 24
- 제3장 연구개발수행 내용 및 결과 ... 27
- 1. 다중영상 기반 생물학적 최적화 방사선치료기술 심화연구 ... 27
- 가. 뇌대사 및 확산 MRI/PET 활용 volume visualization 분석연구 ... 27
- 나. Tumor volume과 Tumor segmentation분석 ... 29
- 다. Tumor segmentation 알고리즘 정립 ... 35
- 2. 4D 다중영상 기반 생물학적 최적화 방사선치료기술 기초연구 ... 38
- 가. 장기움직임을 고려한 Hypoxic tracer PET 영상융합 최적화 기술 개발 ... 38
- 나. PET영상정합을 이용한 대사영상의 종양 특징 파라미터 추출 ... 48
- 다. 장기움직임을 고려한 4D CT/PET 영상융합 상관관계 분석 ... 54
- 제4장 목표달성도 및 관련분야에의 기여도 ... 61
- 제5장 연구개발결과의 활용계획 ... 62
- 제6장 연구개발과정에서 수집한 해외과학기술정보 ... 63
- 제7장 참고문헌 ... 64
- 수정ㆍ보완요구사항 대비표 ... 67
- 끝페이지 ... 67
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