M. Grégoire, F. Frouin, F. Lavenne, O. de Dreuille, M. Janier, R. Di Paola, L. Cinotti
{"title":"PET研究中心肌灌注因子分析准确性的评价","authors":"M. Grégoire, F. Frouin, F. Lavenne, O. de Dreuille, M. Janier, R. Di Paola, L. Cinotti","doi":"10.1109/NSSMIC.1995.501911","DOIUrl":null,"url":null,"abstract":"Factor Analysis of Medical Image Sequences (FAMIS) estimates kinetics (factors) and corresponding spatial regions (factor images) from dynamic studies, taking into account statistical noise and spillover effects. Factor images obtained from /sup 15/O-water clinical cardiac PET studies are less noisy than conventional subtraction images, and factors match physiologic kinetics. Here, the authors studied FAMIS accuracy and precision depending on the application context. FAMIS was evaluated through kinetics parameters quantification. Numerical simulations and phantom experiments were carried out using a typical left ventricular pattern. This object was simulated in 2D with 3 noise levels and 2 kinds of kinetics: mono-exponentials which correspond to natural tracer decay, and tissue perfusion kinetics obtained with a realistic vascular input function. Mono-exponentials association was adapted to phantom experiments while perfusion kinetics represented clinical cardiac studies. In both phantom experiments and simulations, the inner chamber was filled with /sup 15/O-water and the myocardial space with Carbon-11. The different noise levels which were studied corresponded to ideal, normal and low quality scans. Using the factors estimated by FAMIS, decay constants and an index of flow (k1) were estimated by fitting or modelling. Relative bias to the true value and standard deviation were then estimated, and spatial correlation between factor images and original spatial pattern was computed. Factor images spatial correlation was very good, despite of large overlapping pattern. Oxygen-15 decay constant was assessed from factor with a small relative bias, for all noise levels and trixel sizes. However, Carbon-11 extraction was very sensitive to both noise and spillover in phantom and simulations. A reasonable bias was only achieved by including a spillover term which accounted for an overcorrection. On the contrary, factors associated to perfusion were well extracted and k1 parameter was recovered with a low relative bias (r.b.<6%), except for the higher noise level. It was already shown that FAMIS performances depend on the overlap of the spatial structures. This study demonstrates that factor analysis without a priori information performances depend on kinetics shape. Moreover, in the context of cardiac /sup 15/O-water perfusion studies, FAMIS should provide accurate quantification.","PeriodicalId":409998,"journal":{"name":"1995 IEEE Nuclear Science Symposium and Medical Imaging Conference Record","volume":"102-103 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Evaluation of factor analysis accuracy for myocardial perfusion in PET studies\",\"authors\":\"M. Grégoire, F. Frouin, F. Lavenne, O. de Dreuille, M. Janier, R. Di Paola, L. Cinotti\",\"doi\":\"10.1109/NSSMIC.1995.501911\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Factor Analysis of Medical Image Sequences (FAMIS) estimates kinetics (factors) and corresponding spatial regions (factor images) from dynamic studies, taking into account statistical noise and spillover effects. Factor images obtained from /sup 15/O-water clinical cardiac PET studies are less noisy than conventional subtraction images, and factors match physiologic kinetics. Here, the authors studied FAMIS accuracy and precision depending on the application context. FAMIS was evaluated through kinetics parameters quantification. Numerical simulations and phantom experiments were carried out using a typical left ventricular pattern. This object was simulated in 2D with 3 noise levels and 2 kinds of kinetics: mono-exponentials which correspond to natural tracer decay, and tissue perfusion kinetics obtained with a realistic vascular input function. Mono-exponentials association was adapted to phantom experiments while perfusion kinetics represented clinical cardiac studies. In both phantom experiments and simulations, the inner chamber was filled with /sup 15/O-water and the myocardial space with Carbon-11. The different noise levels which were studied corresponded to ideal, normal and low quality scans. Using the factors estimated by FAMIS, decay constants and an index of flow (k1) were estimated by fitting or modelling. Relative bias to the true value and standard deviation were then estimated, and spatial correlation between factor images and original spatial pattern was computed. Factor images spatial correlation was very good, despite of large overlapping pattern. Oxygen-15 decay constant was assessed from factor with a small relative bias, for all noise levels and trixel sizes. However, Carbon-11 extraction was very sensitive to both noise and spillover in phantom and simulations. A reasonable bias was only achieved by including a spillover term which accounted for an overcorrection. On the contrary, factors associated to perfusion were well extracted and k1 parameter was recovered with a low relative bias (r.b.<6%), except for the higher noise level. 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引用次数: 1
摘要
医学图像序列因子分析(FAMIS)从动态研究中估计动力学(因子)和相应的空间区域(因子图像),考虑到统计噪声和溢出效应。从/sup 15/O-water临床心脏PET研究中获得的因子图像比传统的减法图像噪声更小,并且因子符合生理动力学。在这里,作者研究了FAMIS在不同应用环境下的准确性和精密度。通过动力学参数定量评价FAMIS。采用典型的左心室模式进行了数值模拟和模拟实验。用3种噪声水平和2种动力学对该物体进行了二维模拟:对应于自然示踪剂衰减的单指数和由真实血管输入函数获得的组织灌注动力学。单指数关联适用于幻影实验,而灌注动力学代表临床心脏研究。在模型实验和模拟实验中,内室充满了/sup 15/ o水,心肌空间充满了碳-11。所研究的不同噪声水平对应于理想、正常和低质量扫描。利用FAMIS估算的因子,通过拟合或建模估算衰减常数和流动指数(k1)。然后估计因子图像与真实值的相对偏差和标准差,计算因子图像与原始空间格局的空间相关性。因子图像空间相关性较好,但重叠模式较大。对于所有噪声水平和三轴尺寸,从相对偏差较小的因素评估氧-15衰变常数。然而,在模拟和模拟中,碳-11提取对噪声和溢出都非常敏感。一个合理的偏差只能通过包括一个溢出项来实现,这个溢出项可以解释过度修正。相反,除了较高的噪声水平外,与灌注相关的因素被很好地提取出来,k1参数以较低的相对偏差(r.b.<6%)恢复。已经表明,FAMIS的性能取决于空间结构的重叠。该研究表明,没有先验信息的因子分析性能取决于动力学形状。此外,在心脏/sup 15/ o -水灌注研究的背景下,FAMIS应该提供准确的量化。
Evaluation of factor analysis accuracy for myocardial perfusion in PET studies
Factor Analysis of Medical Image Sequences (FAMIS) estimates kinetics (factors) and corresponding spatial regions (factor images) from dynamic studies, taking into account statistical noise and spillover effects. Factor images obtained from /sup 15/O-water clinical cardiac PET studies are less noisy than conventional subtraction images, and factors match physiologic kinetics. Here, the authors studied FAMIS accuracy and precision depending on the application context. FAMIS was evaluated through kinetics parameters quantification. Numerical simulations and phantom experiments were carried out using a typical left ventricular pattern. This object was simulated in 2D with 3 noise levels and 2 kinds of kinetics: mono-exponentials which correspond to natural tracer decay, and tissue perfusion kinetics obtained with a realistic vascular input function. Mono-exponentials association was adapted to phantom experiments while perfusion kinetics represented clinical cardiac studies. In both phantom experiments and simulations, the inner chamber was filled with /sup 15/O-water and the myocardial space with Carbon-11. The different noise levels which were studied corresponded to ideal, normal and low quality scans. Using the factors estimated by FAMIS, decay constants and an index of flow (k1) were estimated by fitting or modelling. Relative bias to the true value and standard deviation were then estimated, and spatial correlation between factor images and original spatial pattern was computed. Factor images spatial correlation was very good, despite of large overlapping pattern. Oxygen-15 decay constant was assessed from factor with a small relative bias, for all noise levels and trixel sizes. However, Carbon-11 extraction was very sensitive to both noise and spillover in phantom and simulations. A reasonable bias was only achieved by including a spillover term which accounted for an overcorrection. On the contrary, factors associated to perfusion were well extracted and k1 parameter was recovered with a low relative bias (r.b.<6%), except for the higher noise level. It was already shown that FAMIS performances depend on the overlap of the spatial structures. This study demonstrates that factor analysis without a priori information performances depend on kinetics shape. Moreover, in the context of cardiac /sup 15/O-water perfusion studies, FAMIS should provide accurate quantification.