Suppr超能文献

[Detection, quantification and localization of myocardial infarcts: comparison of thallium single photon emission computer tomography with biplane angiography].

作者信息

Hoffmeister H M, Kaiser W, Hanke H, Müller-Schauenburg W, Karsch K R, Feine U, Seipel L

出版信息

Z Kardiol. 1985 Nov;74(11):625-32.

PMID:3879054
Abstract

Thallium-201 single photon emission computed tomography (SPECT) is a new method for the scintigraphic visualization of the left ventricular myocardium. With SPECT a three-dimensional imaging by computerized slicing of the myocardium in various axes is possible. To investigate the capabilities of this new imaging technique, detection and quantification of remote transmural infarctions were compared with ventriculographic, coronarographic and electrocardiographic findings. 31 of 80 investigated patients had had a prior myocardial infarction. The left ventricular myocardium was divided into 7 regions in the scintigraphic as well as in the angiographic studies. In a total of 560 segments the sensitivity of SPECT for infarct detection was 87.5% with a specificity of 99.8%. Infarcts which were not detected scintigraphically were relatively small (mean 13.5% of the circumference). To quantify the infarct, the size of the defect was determined scintigraphically from a sagittal long axis and two short axes, and the images compared with angiographic infarct sizes (% of the circumference) according to the method of Feild et al. A good correlation without overestimation of the size by one method (SPECT defect = 0.93 X ventriculographic defect - 1.2%; r = 0.7, p less than 0.001) was obtained. Also a good separation of the perfusion areas of the coronary arteries due to the three-dimensional imaging with SPECT was possible. Thus, by employing Thallium-201 SPECT of the left ventricular myocardium exact localization and quantification of transmural myocardial infarcts with a positive predictive value of 98% can be achieved.

摘要

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验