Van Kriekinge S D, Berman D S, Germano G
Department of Medicine, Burns and Allen Research Institute, Cedars-Sinai Medical Center, Los Angeles, Calif 90048, USA.
J Nucl Cardiol. 1999 Sep-Oct;6(5):498-506. doi: 10.1016/s1071-3581(99)90022-3.
Cardiac gated blood pool single photon emission computed tomography (GBPS) better separates cardiac chambers compared with planar radionuclide ventriculography (PRNV). We have developed a completely automatic algorithm to measure quantitatively the left ventricular ejection fraction (LVEF) from gated technetium 99m-red blood cells (RBC) GBPS short-axis 3-dimensional image volumes.
The algorithm determines an ellipsoidal coordinate system for the left ventricle and then computes a static estimate of the endocardial surface by use of counts and count gradients. A dynamic surface representing the endocardium is computed for each interval of the cardiac cycle by use of additional information from the temporal Fourier transform of the image data sets. The algorithm then calculates the left ventricular volume for each interval and computes LVEF from the end-diastolic and end-systolic volumes. The algorithm was developed in a pilot group (N = 45) and validated in a second group (N = 89) of patients who underwent PRNV and 8-interval GBPS. Technically inadequate studies (N = 38) were rejected before grouping and processing. Automatic identification and contouring of the left ventricle was successful in 121/172 patients (70%) globally and in 76/89 patients (85 %) in the validation group. Correlation between LVEFs measured from GBPS and PRNV was high (y = 2.00 + 1.01x, r = 0.89), with GBPS LVEF significantly higher than PRNV LVEF (average difference = 2.8%, P < .004).
Our automatic algorithm agrees with conventional radionuclide measurements of LVEF and provides the basis for 3-dimensional analysis of wall motion.
与平面放射性核素心室造影(PRNV)相比,心脏门控血池单光子发射计算机断层扫描(GBPS)能更好地分离心腔。我们开发了一种完全自动的算法,用于从门控锝99m红细胞(RBC)GBPS短轴三维图像容积中定量测量左心室射血分数(LVEF)。
该算法为左心室确定一个椭球坐标系,然后利用计数和计数梯度计算心内膜表面的静态估计值。通过使用图像数据集的时间傅里叶变换的附加信息,为心动周期的每个间期计算代表心内膜的动态表面。然后,该算法计算每个间期的左心室容积,并根据舒张末期和收缩末期容积计算LVEF。该算法在一个试验组(N = 45)中开发,并在另一组(N = 89)接受PRNV和8间期GBPS检查的患者中进行验证。在分组和处理之前,排除了技术上不合格的研究(N = 38)。在全球范围内,121/172例患者(70%)成功实现了左心室的自动识别和轮廓描绘,在验证组中,76/89例患者(85%)成功实现。GBPS测量的LVEF与PRNV测量的LVEF之间的相关性很高(y = 2.00 + 1.01x,r = 0.89),GBPS的LVEF显著高于PRNV的LVEF(平均差异 = 2.8%,P < .004)。
我们的自动算法与传统放射性核素测量的LVEF结果一致,并为壁运动的三维分析提供了基础。