Use of wavelet transforms in analysis of time-activity data from cardiac PET

被引:0
|
作者
Lin, JW
Laine, AF
Akinboboye, O
Bergmann, SR
机构
[1] Columbia Univ Coll Phys & Surg, Dept Med, Div Cardiol, New York, NY 10032 USA
[2] Columbia Univ Coll Phys & Surg, Dept Radiol, New York, NY 10032 USA
[3] Columbia Univ, Dept Biomed Engn, New York, NY USA
关键词
quantitative PET; myocardial blood flow; noise reduction; data analysis;
D O I
暂无
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Because of its intrinsic quantitative properties, PET permits measurement of myocardial perfusion and metabolism in absolute terms (i.e., mL/g/min), However, quantification has been limited by errors produced in image acquisition, selection of regions of interest, and data analysis. The goal of this study was to evaluate a newly developed, novel, wavelet-based noise-reduction approach that can objectively extract biologic signals hidden within dynamic PET data. Methods: Quantification of myocardial perfusion using dynamic PET imaging with Rb-82, (H2O)-O-15, and (NH3)-N-13 was selected to evaluate the effects of the wavelet-based noise-reduction protocol. Dynamic PET data were fitted to appropriate mathematic models before and after wavelet-based noise reduction to get flow estimates. Time-activity curves, precision, accuracy, and differentiating capacity derived from the wavelet protocol were compared with those obtained from unmodified data processing, A total of 84 human studies was analyzed, including 43 at rest (18 Rb-82 scans, 18 (H2O)-O-15 scans, and 7 (NH3)-N-13 scans) and 41 after coronary hyperemia with dipyridamole (17 Rb-82 scans, 17 (H2O)-O-15 scans, and 7 (NH3)-N-13 scans). Results: For every tracer tested under all conditions, the wavelet method improved the shape of blood and tissue time-activity curves, increased estimate-to-error ratios, and maintained fidelity of flow in regions as small as 0.85 cm(3). It also improved the accuracy of flow estimates derived from Rb-82 to the level of that achieved with H(2)(15)0, which was not affected markedly by the wavelet process. In studies of patients with coronary disease, regional heterogeneity of myocardial perfusion was preserved and flow estimates in infarcted regions were differentiated more easily from normal regions. Conclusion: The wavelet-based noise-reduction method effectively and objectively extracted tracer time-activity curves from data with low signal-to-noise ratios and improved the accuracy and precision of measurements with all tracer techniques studied. The approach should be generalizable to other image modalities such as functional MRI and CT and, therefore, improve the ability to quantify dynamic physiologic processes.
引用
收藏
页码:194 / 200
页数:7
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