ISSN:
1619-7089
Schlagwort(e):
Radionuclide ventriculography
;
Myocardial scanning
;
Functional imaging
Quelle:
Springer Online Journal Archives 1860-2000
Thema:
Medizin
Notizen:
Abstract Myocardial scanning (MS) and radionuclide ventriculography (RNV) are the foundation of nuclear cardiology. These procedures aim in two completely different directions: RNV tries to image heart motion, that is, mechanical (pump) function, and therefore belongs to the group of first-order functional imaging (FI, imaging mechanical function), whereas MS is based on myocardial metabolism, and therefore can be attributed to third-order functional imaging (metabolism). This statement is relevant for the assessment of the clinical position of RNV: Third-order (metabolism) functional imaging is the domain of nuclear medicine (NM), whereas first-order FI has to face the competition of alternative noninvasive procedures such as ultrasound (US), digital subtraction angiography (DSA), computer tomography (CT), and nuclear magnetic resonance (NMR). The domain of RNV includes stages two (acute infarction) and three (postinfarction period) of coronary arterial disease (CAD). The advantageous combination of quantitative data on global, left ventricular (LV) function and imaging of regional motion ensures the superiority of RNV over US. However, RNV is inferior to MS in physical examinations in the preinfarction stage of CAD, whereas US is clearly inferior to both NM procedures. Recent progress could be attained by gated SPECT (GASPECT). A proposal is presented for simplification of this time-consuming procedure. Technetium-labeled isonitriles offer the chance for the combination of “perfusion-motion” imaging of the myocardium. However, even standard RNV offers new possibilities. The multitude of parameters produced by quantitation has not yet been exploited completely. This can be done by discriminant analysis. The computer finds out an optimal subset from the whole set of parameters for the solution of a significant clinical problem. The software “learns” to find the “label” of a special pathognomonic entity. This computer work is supported by a relational data bank (Oracle) and an optical disk. Two examples for the effectiveness of the computer in problem solving are presented. It is concluded that RNV, even in the very competitive class of first-order functional imaging, enjoys a preferred position. The future indeed seems brighter because labeled isonitriles offer the chance for the combination of perfusion-motion imaging of the myocardium.
Materialart:
Digitale Medien
URL:
http://dx.doi.org/10.1007/BF00256391
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