Sensitivity of Noninvasive Cardiac Electrophysiological Imaging to Variations in Personalized Anatomical Modeling

Abstract

Objective Noninvasive cardiac electrophysiological (EP) imaging techniques rely on anatomically-detailed heart-torso models derived from high-quality tomographic images of individual subjects. However, anatomical modeling involves variations that lead to unresolved uncertainties in the outcome of EP imaging, bringing questions to the robustness of these methods in clinical practice. In this study, we design a systematic statistical approach to assess the sensitivity of EP imaging methods to the variations in personalized anatomical modeling. Methods We first quantify the variations in personalized anatomical models by a novel application of statistical shape modeling. Given the statistical distribution of the variation in personalized anatomical models, we then employ unscented transform to determine the sensitivity of EP imaging outputs to the variation in input personalized anatomical modeling. Results We test the feasibility of our proposed approach using two of the existing EP imaging methods: epicardial-based electrocardiographic imaging and transmural electrophysiological imaging. Both phantom and real-data experiments show that variations in personalized anatomical models have negligible impact on the outcome of EP imaging. Conclusion This study verifies the robustness of EP imaging methods to the errors in personalized anatomical modeling and suggests the possibility to simplify the process of anatomical modeling in future clinical practice. Significance This study proposes a systematic statistical approach to quantify anatomical modeling variations and assess their impact on EP imaging, which can be extended to find a balance between the quality of personalized anatomical models and the accuracy of EP imaging that may improve the clinical feasibility of EP imaging.

Influence of Torso Model Complexity on the Noninvasive Localization of Ectopic Ventricular Activity

“…Precision of the reconstruction of the patient-specific geometry from CT images was studied by Prakosa in [19] and its influence on accurate electrophysiological imaging by Rahimi [20]. In this study specialized image-processing software TomoCon PACS® was used to construct precise patient-specific torso geometries from whole torso CT scans.…”

Transfer Learning From Simulations on a Reference Anatomy for ECGI in Personalized Cardiac Resynchronization Therapy

“…They concluded that it was crucial to adapt both the outer shape of the torso model and the position of electrodes according to reality. Yet, it has been also shown that some adapted ventricle-torso standard model were able to get good ECGI results while excluding local geometrical details [20], [21]. Lastly, a recent study uses a generic ventricle-torso model in order to build an EP model training set [15], however the training phase had to be patient-specific as the generic geometry was first registered to every patient geometry.…”

Three-Dimensional Noninvasive Imaging of Ventricular Arrhythmias in Patients With Premature Ventricular Contractions

“…Further endeavors have been made to image the electrical activities throughout the three-dimensional (3D) ventricles [11], [24]–[33]. Results from previous studies have demonstrated that the 3D cardiac electrical imaging technique is capable of localizing the 3D ectopic initiation site of different types of arrhythmia [25], [34], [35].…”