• Title/Summary/Keyword: Lung Registration

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Multimodality Image Registration and Fusion using Feature Extraction (특징 추출을 이용한 다중 영상 정합 및 융합 연구)

  • Woo, Sang-Keun;Kim, Jee-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.2 s.46
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    • pp.123-130
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    • 2007
  • The aim of this study was to propose a fusion and registration method with heterogeneous small animal acquisition system in small animal in-vivo study. After an intravenous injection of $^{18}F$-FDG through tail vain and 60 min delay for uptake, mouse was placed on an acryl plate with fiducial markers that were made for fusion between small animal PET (microPET R4, Concorde Microsystems, Knoxville TN) and Discovery LS CT images. The acquired emission list-mode data was sorted to temporally framed sinograms and reconstructed using FORE rebining and 2D-OSEM algorithms without correction of attenuation and scatter. After PET imaging, CT images were acquired by mean of a clinical PET/CT with high-resolution mode. The microPET and CT images were fusion and co-registered using the fiducial markers and segmented lung region in both data sets to perform a point-based rigid co-registration. This method improves the quantitative accuracy and interpretation of the tracer.

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Detection of Lung Nodule on Temporal Subtraction Images Based on Artificial Neural Network

  • Tokisa, Takumi;Miyake, Noriaki;Maeda, Shinya;Kim, Hyoung-Seop;Tan, Joo Kooi;Ishikawa, Seiji;Murakami, Seiichi;Aoki, Takatoshi
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.2
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    • pp.137-142
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    • 2012
  • The temporal subtraction technique as one of computer aided diagnosis has been introduced in medical fields to enhance the interval changes such as formation of new lesions and changes in existing abnormalities on deference image. With the temporal subtraction technique radiologists can easily detect lung nodules on visual screening. Until now, two-dimensional temporal subtraction imaging technique has been introduced for the clinical test. We have developed new temporal subtraction method to remove the subtraction artifacts which is caused by mis-registration on temporal subtraction images of lungs on MDCT images. In this paper, we propose a new computer aided diagnosis scheme for automatic enhancing the lung nodules from the temporal subtraction of thoracic MDCT images. At first, the candidates regions included nodules are detected by the multiple threshold technique in terms of the pixel value on the temporal subtraction images. Then, a rule-base method and artificial neural networks is utilized to remove the false positives of nodule candidates which is obtained temporal subtraction images. We have applied our detection of lung nodules to 30 thoracic MDCT image sets including lung nodules. With the detection method, satisfactory experimental results are obtained. Some experimental results are shown with discussion.

A Study on the Image Registration Algorithms for the Accurate Application of Multimodality Image in Radiation Treatment Planning (방사선치료 계획시 다중영상 활용의 정확도 향상을 위한 영상정합 알고리즘 분석)

  • 송주영;이형구;최보영;윤세철;서태석
    • Progress in Medical Physics
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    • v.13 no.4
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    • pp.209-217
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    • 2002
  • There have been many studies on the application of the reciprocal advantages of multimodality image to define accurate target volume in the Process of radiation treatment planning. For the proper use of the multimodality images, the registration works between different modality images should be performed in advance. In this study, we selected chamfer matching method and mutual information method as most popular methods in recent image registration studies considering the registration accuracy and clinical practicality. And the two registration methods were analyzed to deduce the optimal registration method according to the characteristics of images. Lung phantom of which multimodality images could be acquired was fabricated and CT, MRI and SPECT images of the phantom were used in this study. We developed the registration program which can perform the two registration methods properly and analyzed the registration results which were produced by the developed program in many different images' conditions. Although the overall accuracy of the registration in both chamfer matching method and mutual information method was acceptable, the registration errors in SPECT images which had lower resolution and in degraded images of which data were removed in some part were increased when chamfer matching method was applied. Especially in the case of degraded reference image, chamfer matching methods produce relatively large errors compared with mutual information method. Mutual information method can be estimated as more robust registration method than chamfer matching method in this study because it did not need the prerequisite works, the extraction of accurate contour points, and it produced more accurate registration results consistently regardless of the images' characteristics. The analysis of the registration methods in this study can be expected to provide useful information to the utilization of multimodality images in delineating target volume for radiation treatment planning and in many other clinical applications.

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Evaluation of the Geometric Accuracy of Anatomic Landmarks as Surrogates for Intrapulmonary Tumors in Image-guided Radiotherapy

  • Li, Hong-Sheng;Kong, Ling-Ling;Zhang, Jian;Li, Bao-Sheng;Chen, Jin-Hu;Zhu, Jian;Liu, Tong-Hai;Yin, Yong
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.5
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    • pp.2393-2398
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    • 2012
  • Objectives: The purpose of this study was to evaluate the geometric accuracy of thoracic anatomic landmarks as target surrogates of intrapulmonary tumors for manual rigid registration during image-guided radiotherapy (IGRT). Methods: Kilovolt cone-beam computed tomography (CBCT) images acquired during IGRT for 29 lung cancer patients with 33 tumors, including 16 central and 17 peripheral lesions, were analyzed. We selected the "vertebrae", "carina", and "large bronchi" as the candidate surrogates for central targets, and the "vertebrae", "carina", and "ribs" as the candidate surrogates for peripheral lesions. Three to six pairs of small identifiable markers were noted in the tumors for the planning CT and Day 1 CBCT. The accuracy of the candidate surrogates was evaluated by comparing the distances of the corresponding markers after manual rigid matching based on the "tumor" and a particular surrogate. Differences between the surrogates were assessed using 1-way analysis of variance and post hoc least-significant-difference tests. Results: For central targets, the residual errors increased in the following ascending order: "tumor", "bronchi", "carina", and "vertebrae"; there was a significant difference between "tumor" and "vertebrae" (p = 0.010). For peripheral diseases, the residual errors increased in the following ascending order: "tumor", "rib", "vertebrae", and "carina"; There was a significant difference between "tumor" and "carina" (p = 0.005). Conclusions: The "bronchi" and "carina" are the optimal surrogates for central lung targets, while "rib" and "vertebrae" are the optimal surrogates for peripheral lung targets for manual matching of online and planned tumors.

Analysis of Intrafractional Mass Variabilities Using Deformable Image Registration Program (영상변조 프로그램을 이용한 호흡 위상 간 종양의 움직임 특성 분석)

  • Cho, Jeong-Hee;Kim, Joo-Hoo;Seo, Sun-Youl;Han, Dong-Kyoon
    • Journal of radiological science and technology
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    • v.35 no.2
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    • pp.173-181
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    • 2012
  • The aim of this study is to compare the geometric characteristics of the lung tumor, such as tumor centroid, HU change relative to breath phase, depending on tumor location and adhesion using 4DCT and deformable image registration program (MIMVista). The Y axis change was most significant and the mean Y axis centroid fluctuation was $7.32{\pm}6.88mm$ in lower lung tumor. The mean HU variation in lower lung mass has changed more than other locations, and its mean HU variation was $7.7{\pm}4.97%$ and non-adhered mass was more changed. Correlation for the mass volume between 3DCT and MIP was very high and its coefficient was 0.998. The effect of tumor location, adhesion and diaphragm excursion to geometric uncertainties was analyzed by linear regression model, it was influenced to mass deformation and geometrical variation so much except diaphragm excursion. but intra-fractional and inter-patient's uncertainties were great, so it couldn't find any exact deformation trend.

Verification of X-sight Lung Tracking System in the CyberKnife (사이버나이프에서 폐종양 추적 시스템의 정확도 분석)

  • Huh, Hyun-Do;Choi, Sang-Hyoun;Kim, Woo-Chul;Kim, Hun-Jeong;Kim, Seong-Hoon;Cho, Sam-Ju;Min, Chul-Ki;Cho, Kwang-Hwan;Lee, Sang-Hoon;Choi, Jin-Ho;Lim, Sang-Wook;Shin, Dong-Oh
    • Progress in Medical Physics
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    • v.20 no.3
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    • pp.174-179
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    • 2009
  • To track moving tumor in real time, CyberKnife system imports a technique of the synchrony respiratory tracking system. The fiducial marker which are detectable in X-ray images were demand in CyberKnife Robotic radiosurgery system. It issued as reference markers to locate and track tumor location during patient alignment and treatment delivery. Fiducial marker implantation is an invasive surgical operation that carries a relatively high risk of pneumothorax. Most recently, it was developed a direct lung tumor registration method that does not require the use of fiducials. The purpose of this study is to measure the accuracy of target applying X-sight lung tracking using the Gafchromic film in dynamic moving thorax phantom. The X-sight Lung Tracking quality assurance motion phantom simulates simple respiratory motion of a lung tumor and provides Gafchromic dosimetry film-based test capability at locations inside the phantom corresponding to a typical lung tumor. The total average error for the X-sight Lung Tracking System with a moving target was $0.85{\pm}0.22$ mm. The results were considered reliable and applicable for lung tumor treatment in CyberKnife radiosurgery system. Clinically, breathing patterns of patients may vary during radiation therapy. Therefore, additional studies with a set real patient data are necessary to evaluate the target accuracy for the X-sight Lung Tracking system.

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Lung Cancer in a Rural Area of China: Rapid Rise in Incidence and Poor Improvement in Survival

  • Yang, Juan;Zhu, Jian;Zhang, Yong-Hui;Chen, Yong-Sheng;Ding, Lu-Lu;Kensler, Thomas W;Chen, Jian-Guo
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.16
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    • pp.7295-7302
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    • 2015
  • Background: Lung cancer has been a major health problem in developed countries for several decades, and has emerged recently as the leading cause of cancer death in many developing countries. The incidence of lung cancer appears to be increasing more rapidly in rural than in urban areas of China. This paper presents the trends of lung cancer incidence and survival derived from a 40-year population-based cancer monitoring program in a rural area, Qidong, China. Materials and Methods: The Qidong cancer registration data of 1972-2011 were used to calculate the crude rate, age-standardized rate by Chinese population (CASR) and by world population (WASR), birth cohort rates, and other descriptive features. Active and passive methods were used to construct the data set, with a deadline of the latest follow-up of April 30, 2012. Results: The total number of lung cancer cases was 15,340, accounting for 16.5% of all sites combined. The crude incidence rate, CASR and WASR of this cancer were 34.1, 15.7 and 25.4 per 100,000, respectively. Males had higher crude rates than females (49.7 vs 19.0). Rapidly increasing trends were found in annual percent change resulting in lung cancer being a number one cancer site after year 2010 in Qidong. Birth cohort analysis showed incidence rates have increased for all age groups over 24 years old. The 5 year observed survival rates were 3.55% in 1973-1977, 3.92 in 1983-1987, 3.69% in 1993-1997, and 6.32% in 2003-2007. Males experienced poorer survival than did females. Conclusions: Lung cancer has become a major cancer-related health problem in this rural area. The rapid increases in incidence likely result from an increased cigarette smoking rate and evolving environmental risk factors. Lung cancer survival, while showing some improvement in prognosis, still remains well below that observed in the developed areas of the world.

Preliminary Application of Synthetic Computed Tomography Image Generation from Magnetic Resonance Image Using Deep-Learning in Breast Cancer Patients

  • Jeon, Wan;An, Hyun Joon;Kim, Jung-in;Park, Jong Min;Kim, Hyoungnyoun;Shin, Kyung Hwan;Chie, Eui Kyu
    • Journal of Radiation Protection and Research
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    • v.44 no.4
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    • pp.149-155
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    • 2019
  • Background: Magnetic resonance (MR) image guided radiation therapy system, enables real time MR guided radiotherapy (RT) without additional radiation exposure to patients during treatment. However, MR image lacks electron density information required for dose calculation. Image fusion algorithm with deformable registration between MR and computed tomography (CT) was developed to solve this issue. However, delivered dose may be different due to volumetric changes during image registration process. In this respect, synthetic CT generated from the MR image would provide more accurate information required for the real time RT. Materials and Methods: We analyzed 1,209 MR images from 16 patients who underwent MR guided RT. Structures were divided into five tissue types, air, lung, fat, soft tissue and bone, according to the Hounsfield unit of deformed CT. Using the deep learning model (U-NET model), synthetic CT images were generated from the MR images acquired during RT. This synthetic CT images were compared to deformed CT generated using the deformable registration. Pixel-to-pixel match was conducted to compare the synthetic and deformed CT images. Results and Discussion: In two test image sets, average pixel match rate per section was more than 70% (67.9 to 80.3% and 60.1 to 79%; synthetic CT pixel/deformed planning CT pixel) and the average pixel match rate in the entire patient image set was 69.8%. Conclusion: The synthetic CT generated from the MR images were comparable to deformed CT, suggesting possible use for real time RT. Deep learning model may further improve match rate of synthetic CT with larger MR imaging data.

Population-Based Cancer Registration in Indonesia

  • Wahidin, Mugi;Noviani, Rini;Hermawan, Sofia;Andriani, Vita;Ardian, Ardi;Djarir, Hernani
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.4
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    • pp.1709-1710
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    • 2012
  • Cancer is a major public health problem in Indonesia, becoming the 7th largest cause of death based on a national survey in 2007, accounting for 5.7 of all mortality. A cancer registry was started in 1970, but it was partial and was stopped mainly because no government body was responsible. Realizing the above situation, the Indonesian government established the Sub Directorate of Cancer Control within the Ministry of Health, with responsibility for developing a national cancer control program, including a cancer registry. A sustainable cancer registry was then started in 2007 within Jakarta Province, first hospital-based but then expanded to be population-based. Steps of cancer registration in Jakarta are data collection, data verification, data validation, data management and analysis, and data publication. Data collection is conducted by health facilities (hospitals, laboratories, primary health centers) at the district/municipal level, with reports to the provincial level. Data are collected passively by holding meetings every three months in the district/municipality. Verification of data is the responsibility of the medical doctor or pathologist in each data source. Data validation is conducted by a team in the cancer registry, consisting of district/municipal/province health officers, pathologists, and registrars. Data management and analyses are conducted by a cancer registry team at the provincial level, assisted by the national team. We use software named Indonesian Cancer Registry System (SRIKANDI) which is adopted from CanReg4 IARC. Data from the population-based cancer registry in Jakarta Province showed the leading cancers among females in 2005-2007 to be breast cancer, cervical cancer, ovarian cancer, colorectal cancer and among males are bronchus and lung cancer, colorectal cancer, liver cancer, pharyngeal cancer, and prostate cancer. The leading childhood cancers are leukaemia and retinoblastoma.

Feasibility of Shrinking Field Radiation Therapy through 18F-FDG PET/CT after 40 Gy for Stage III Non-Small Cell Lung Cancers

  • Ding, Xiu-Ping;Zhang, Jian;Li, Bao-Sheng;Li, Hong-Sheng;Wang, Zhong-Tang;Yi, Yan;Sun, Hong-Fu;Wang, Dong-Qing
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.1
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    • pp.319-323
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    • 2012
  • Objective: To explore the feasibility of shrinking field technique after 40 Gy radiation through 18F-FDG PET/CT during treatment for patients with stage III non-small cell lung cancer (NSCLC). Methods: In 66 consecutive patients with local-advanced NSCLC, 18F-FDG PET/CT scanning was performed prior to treatment and repeated after 40 Gy. Conventionally fractionated IMRT or CRT plans to a median total dose of 66Gy (range, 60-78Gy) were generated. The target volumes were delineated in composite images of CT and PET. Plan 1 was designed for 40 Gy to the initial planning target volume (PTV) with a subsequent 20-28 Gy-boost to the shrunken PTV. Plan 2 was delivering the same dose to the initial PTV without shrinking field. Accumulated doses of normal tissues were calculated using deformable image registration during the treatment course. Results: The median GTV and PTV reduction were 35% and 30% after 40 Gy treatment. Target volume reduction was correlated with chemotherapy and sex. In plan 2, delivering the same dose to the initial PTV could have only been achieved in 10 (15.2%) patients. Significant differences (p<0.05) were observed regarding doses to the lung, spinal cord, esophagus and heart. Conclusions: Radiotherapy adaptive to tumor shrinkage determined by repeated 18F-FDG PET/CT after 40 Gy during treatment course might be feasible to spare more normal tissues, and has the potential to allow dose escalation and increased local control.