Ramanathan Charulatha, Jia Ping, Ghanem Raja, Calvetti Daniela, Rudy Yoram
Cardiac Bioelectricity Research and Training Center, Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106-7207, USA.
Ann Biomed Eng. 2003 Sep;31(8):981-94. doi: 10.1114/1.1588655.
Electrocardiographic imaging (ECGI) is a developing imaging modality for cardiac electrophysiology and arrhythmias. It reconstructs epicardial potentials, electrograms, and isochrones from electrocardiographic body-surface potentials noninvasively. Current ECGI methodology employs Tikhonov regularization, which imposes constraints on the reconstructed potentials or their derivatives. This approach can sometimes reduce spatial resolution by smoothing the solution. Accuracy depends on a priori knowledge of solution characteristics and determination of an optimal regularization parameter. These properties led us to implement an independent, iterative approach for ECGI--the generalized minimal residual (GMRes) method--which does not apply constraints. GMRes was applied to experimental data during activation/repolarization of normal and infarcted hearts. GMRes reconstructions were compared to Tikhonov reconstructions and to measured "gold standards" in isolated hearts. Overall, the accuracy of GMRes solutions was similar to Tikhonov regularization. However, in certain cases GMRes recovered localized potential features (e.g., multiple potential minima), which were lost in the Tikhonov solution. Simultaneous use of these two complementary methods in clinical ECGI will ensure reliability and maximal extraction of diagnostic information in the absence of a priori information about a patient's condition.
心电图成像(ECGI)是一种用于心脏电生理学和心律失常的新兴成像方式。它能从体表心电图电位无创地重建心外膜电位、心电图和等时线。当前的ECGI方法采用蒂霍诺夫正则化,该方法对重建电位或其导数施加约束。这种方法有时会通过平滑解来降低空间分辨率。准确性取决于解的特征的先验知识以及最优正则化参数的确定。这些特性促使我们为ECGI实现一种独立的迭代方法——广义极小残差(GMRes)方法,该方法不施加约束。GMRes被应用于正常和梗死心脏激活/复极过程中的实验数据。将GMRes重建结果与蒂霍诺夫重建结果以及离体心脏中测量的“金标准”进行比较。总体而言,GMRes解的准确性与蒂霍诺夫正则化相似。然而,在某些情况下,GMRes恢复了局部电位特征(例如多个电位极小值),而这些特征在蒂霍诺夫解中丢失了。在临床ECGI中同时使用这两种互补方法将确保在缺乏患者病情先验信息的情况下诊断信息的可靠性和最大程度提取。