Miri Raz, Reumann Matthias, Farina Dimitry, Dössel Olaf
Institute of Biomedical Engineering, University of Karlsruhe (TH), Karlsruhe, Germany.
Biomed Tech (Berl). 2009 Apr;54(2):55-65. doi: 10.1515/BMT.2009.013.
The efficacy of cardiac resynchronization therapy through biventricular pacing (BVP) has been demonstrated by numerous studies in patients suffering from congestive heart failure. In order to achieve a guideline for optimal treatment with BVP devices, an automated non-invasive strategy based on a computer model of the heart is presented.
The presented research investigates an off-line optimization algorithm regarding electrode positioning and timing delays. The efficacy of the algorithm is demonstrated in four patients suffering from left bundle branch block (LBBB) and myocardial infarction (MI). The computer model of the heart was used to simulate the LBBB in addition to several MI allocations according to the different left ventricular subdivisions introduced by the American Heart Association. Furthermore, simulations with reduced interventricular conduction velocity were performed in order to model interventricular excitation conduction delay. More than 800,000 simulations were carried out by adjusting a variety of 121 pairs of atrioventricular and interventricular delays and 36 different electrode positioning set-ups. Additionally, three different conduction velocities were examined. The optimization measures included the minimum root mean square error (E(RMS)) between physiological, pathological and therapeutic excitation, and also the difference of QRS-complex duration. Both of these measures were computed automatically.
Depending on the patient's pathology and conduction velocity, a reduction of E(RMS) between physiological and therapeutic excitation could be reached. For each patient and pathology, an optimal pacing electrode pair was determined. The results demonstrated the importance of an individual adjustment of BVP parameters to the patient's anatomy and pathology.
This work proposes a novel non-invasive optimization algorithm to find the best electrode positioning sites and timing delays for BVP in patients with LBBB and MI. This algorithm can be used to plan an optimal therapy for an individual patient.
多项研究已证实双心室起搏（BVP）心脏再同步治疗对充血性心力衰竭患者的疗效。为制定BVP设备的最佳治疗指南，本文提出一种基于心脏计算机模型的自动化非侵入性策略。
本研究探讨一种关于电极定位和时间延迟的离线优化算法。该算法在4例左束支传导阻滞（LBBB）和心肌梗死（MI）患者中得到验证。除了根据美国心脏协会引入的不同左心室分区进行的几种MI分配外，还使用心脏计算机模型模拟LBBB。此外，为模拟心室间兴奋传导延迟，进行了心室间传导速度降低的模拟。通过调整121对房室和心室间延迟的各种组合以及36种不同的电极定位设置，进行了超过80万次模拟。此外，还研究了三种不同的传导速度。优化措施包括生理、病理和治疗性兴奋之间的最小均方根误差（E(RMS)）以及QRS波群持续时间的差异。这两种测量均自动计算。
根据患者的病理情况和传导速度，可实现生理和治疗性兴奋之间E(RMS)的降低。针对每位患者和病理情况，确定了最佳起搏电极对。结果表明，针对患者的解剖结构和病理情况对BVP参数进行个体化调整非常重要。
本研究提出了一种新颖的非侵入性优化算法，用于为LBBB和MI患者寻找BVP的最佳电极定位部位和时间延迟。该算法可用于为个体患者规划最佳治疗方案。
