Tatsukawa H, Furukawa K, Katsume H, Kosugi Y, Azuma A, Inoue N, Sugihara H, Inoue D, Asayama J, Nakagawa M
Second Department of Internal Medicine, Kyoto Prefectural University of Medicine.
J Cardiol. 1989 Jun;19(2):563-70.
Based on the fact that ultrasonic myocardial textural patterns are more irregular in the pathological myocardium than in the normal, evaluation of the myocardial tissue character was attempted in vivo using spectral analysis. Parasternal left ventricular long-axis echocardiograms were obtained from five patients with old myocardial infarction diagnosed by history, electrocardiography and coronary angiography. These echocardiograms were transferred to an image analyzer and digitized (256 x 256 x 8). The waveforms of the gray-scale-changes from the normal myocardium showed periodicity in each 8-pixel cycle, but those from the infarcted myocardium did not. To quantify pattern changes in gray-scale values in the ultrasound beam direction, spectral analysis was performed by the maximum entropy method (MEM). There were four peaks in the MEM spectra both in the normal and infarcted myocardia, but there was a great significance in these patterns: with high, steep peaks in normal MEM spectra, and low, blunt peaks in infarcted ones. By discriminatory analysis of these four peak values, normalized by the whole spatial frequencies as multivariate, the misclassification rate was 4.8-22.7% in anteroseptal infarctions and 5.0-20.0% in posterior infarctions. Thus, spectral analysis of the myocardial textural pattern has advantages for analyzing routine echocardiograms without corrections by any absolute ultrasonic references. Furthermore, the misclassification rate is so low that we are able to characterize myocardial tissue.
基于病理心肌的超声心肌纹理模式比正常心肌更不规则这一事实，尝试使用频谱分析在体内评估心肌组织特征。从5例经病史、心电图和冠状动脉造影诊断为陈旧性心肌梗死的患者获取胸骨旁左心室长轴超声心动图。这些超声心动图被传输到图像分析仪并进行数字化处理（256×256×8）。正常心肌灰度变化的波形在每8像素周期显示出周期性，而梗死心肌的波形则没有。为了量化超声束方向上灰度值的模式变化，采用最大熵法（MEM）进行频谱分析。正常心肌和梗死心肌的MEM频谱中均有四个峰值，但这些模式存在显著差异：正常MEM频谱中的峰值高且陡，梗死心肌的峰值低且钝。通过对这四个峰值进行判别分析，并以整个空间频率作为多变量进行归一化，前间隔梗死的误分类率为4.8 - 22.7%，后壁梗死的误分类率为5.0 - 20.0%。因此，心肌纹理模式的频谱分析在分析常规超声心动图时具有优势，无需任何绝对超声参考进行校正。此外，误分类率非常低，以至于我们能够对心肌组织进行特征描述。
