PhySense, DTIC, Universitat Pompeu Fabra, Barcelona, Spain.
Arrhythmia Section, Cardiology Department, Thorax Institute, Hospital Clinic, Barcelona, Spain.
Med Image Anal. 2016 Aug;32:131-44. doi: 10.1016/j.media.2016.03.010. Epub 2016 Apr 4.
Integration of electrical and structural information for scar characterization in the left ventricle (LV) is a crucial step to better guide radio-frequency ablation therapies, which are usually performed in complex ventricular tachycardia (VT) cases. This integration requires finding a common representation where to map the electrical information from the electro-anatomical map (EAM) surfaces and tissue viability information from delay-enhancement magnetic resonance images (DE-MRI). However, the development of a consistent integration method is still an open problem due to the lack of a proper evaluation framework to assess its accuracy. In this paper we present both: (i) an evaluation framework to assess the accuracy of EAM and imaging integration strategies with simulated EAM data and a set of global and local measures; and (ii) a new integration methodology based on a planar disk representation where the LV surface meshes are quasi-conformally mapped (QCM) by flattening, allowing for simultaneous visualization and joint analysis of the multi-modal data. The developed evaluation framework was applied to estimate the accuracy of the QCM-based integration strategy on a benchmark dataset of 128 synthetically generated ground-truth cases presenting different scar configurations and EAM characteristics. The obtained results demonstrate a significant reduction in global overlap errors (50-100%) with respect to state-of-the-art integration techniques, also better preserving the local topology of small structures such as conduction channels in scars. Data from seventeen VT patients were also used to study the feasibility of the QCM technique in a clinical setting, consistently outperforming the alternative integration techniques in the presence of sparse and noisy clinical data. The proposed evaluation framework has allowed a rigorous comparison of different EAM and imaging data integration strategies, providing useful information to better guide clinical practice in complex cardiac interventions.
将电信息和结构信息整合用于左心室 (LV) 瘢痕特征描述是更好地指导射频消融治疗的关键步骤，这种治疗通常用于复杂室性心动过速 (VT) 病例。这种整合需要找到一个通用的表示形式，将电信息从电解剖图 (EAM) 表面映射到延迟增强磁共振图像 (DE-MRI) 的组织活力信息。然而，由于缺乏适当的评估框架来评估其准确性，因此开发一致的整合方法仍然是一个开放问题。在本文中，我们提出了：（i）一种使用模拟 EAM 数据和全局和局部度量的评估框架来评估 EAM 和成像整合策略的准确性；（ii）一种新的基于平面圆盘表示的整合方法，其中 LV 表面网格通过扁平化进行准共形映射 (QCM)，允许对多模态数据进行同时可视化和联合分析。所开发的评估框架应用于一组 128 个合成生成的基准数据集，这些数据集具有不同的瘢痕配置和 EAM 特征，以估计基于 QCM 的整合策略的准确性。结果表明，与最先进的整合技术相比，全局重叠误差显著降低了 50-100%，同时更好地保留了瘢痕中传导通道等小结构的局部拓扑。还使用来自 17 名 VT 患者的数据来研究 QCM 技术在临床环境中的可行性，在存在稀疏和嘈杂的临床数据的情况下，始终优于替代的整合技术。所提出的评估框架允许对不同的 EAM 和成像数据整合策略进行严格比较，为在复杂心脏介入中更好地指导临床实践提供了有用的信息。
