Milanič Matija, Jazbinšek Vojko, Macleod Robert S, Brooks Dana H, Hren Rok
Jozef Stefan Institute, Ljubljana, Slovenia.
Institute of Mathematics, Physics, and Mechanics, Ljubljana, Slovenia.
J Electrocardiol. 2014 Jan-Feb;47(1):20-8. doi: 10.1016/j.jelectrocard.2013.10.004. Epub 2013 Oct 17.
A widely used approach to solving the inverse problem in electrocardiography involves computing potentials on the epicardium from measured electrocardiograms (ECGs) on the torso surface. The main challenge of solving this electrocardiographic imaging (ECGI) problem lies in its intrinsic ill-posedness. While many regularization techniques have been developed to control wild oscillations of the solution, the choice of proper regularization methods for obtaining clinically acceptable solutions is still a subject of ongoing research. However there has been little rigorous comparison across methods proposed by different groups. This study systematically compared various regularization techniques for solving the ECGI problem under a unified simulation framework, consisting of both 1) progressively more complex idealized source models (from single dipole to triplet of dipoles), and 2) an electrolytic human torso tank containing a live canine heart, with the cardiac source being modeled by potentials measured on a cylindrical cage placed around the heart. We tested 13 different regularization techniques to solve the inverse problem of recovering epicardial potentials, and found that non-quadratic methods (total variation algorithms) and first-order and second-order Tikhonov regularizations outperformed other methodologies and resulted in similar average reconstruction errors.
一种广泛用于解决心电图逆问题的方法是根据在躯干表面测得的心电图（ECG）来计算心外膜上的电位。解决这种心电图成像（ECGI）问题的主要挑战在于其内在的不适定性。虽然已经开发了许多正则化技术来控制解的剧烈振荡，但选择合适的正则化方法以获得临床上可接受的解仍然是一个正在进行研究的课题。然而，不同团队提出的方法之间几乎没有进行过严格的比较。本研究在一个统一的模拟框架下系统地比较了用于解决ECGI问题的各种正则化技术，该框架包括：1）逐渐更复杂的理想化源模型（从单偶极子到三偶极子），以及2）一个包含活体犬心脏的电解人体躯干模型，心脏源由放置在心脏周围的圆柱形笼上测得的电位来建模。我们测试了13种不同的正则化技术来解决恢复心外膜电位的逆问题，发现非二次方法（总变分算法）以及一阶和二阶蒂霍诺夫正则化优于其他方法，并导致了相似的平均重建误差。
