Atrial fibrillation (AF), the most common type of cardiac arrythmia, has been a huge concern of public health. It affects more than 6 million people in the United States and over 33 million people worldwide. In the current standard of care, an electrogram and geometry map is generated by electroanatomic mapping (EAM) using a mapping catheter, to determine the origins of irregular heart rhythm. Followed by radiofrequency ablation (RFA) using ablation catheter, the targeted sites are ablated as lesions to change the electrical conduction pathway of abnormal electrogram, thus restoring the patients to normal sinus heart rhythm with minimally invasive procedure.
However, a significant proportion of patients suffer from AF recurrences and requires repeated procedures, due to the lack of reliable methods to assess the cardiac structural substrates which are the potential maintaining mechanism of AF signals. In recent years, optical imaging modalities are developed to compensate this limitation, among which near-infrared spectroscopy (NIRS) is a catheter-based technique to enable direct, independent characterization of cardiac tissue pathology from spectrum morphology.
In this thesis, we validate the capability of NIRS to generate map with repeatability and identify AF substrate to improve the efficacy of treatment. First, a near-infrared imaging spectroscopy was combined with an electromagnetic tracking modality, and the system was operated with high acquisition speed and real-time display to generate high-density map. Further, the robustness of NIRS optical parameters was assessed under blood mapping and various, large catheter-tissue contact angle, to simulate the dynamic circumstance of clinical procedures. A classification algorithm was introduced to predict lesion probability including both PBS and blood data, as well as to evaluate the mapping equivalence of blood and PBS.
Next, the spatial resolution and the sampling density requirement of NIRS mapping method was characterized based on small gap, and the spectral properties of gap was assessed comparing to normal tissue and lesion by statistical analysis and machine learning. Lastly, we demonstrate the identification of human left atrial complex substrates using NIRS catheter with different source-detector-separations (SDSs), and reported the spectral features for the AF-related structures such as fibrosis and adipose. To summarize, the catheter-based NIRS technology is robust for in-vivo application and structural target localization, with the potential to enhance the recognition of underlying AF pathology and improve treatment efficacy.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/dfkk-1086 |
| Date | January 2024 |
| Creators | Yang, Haiqiu |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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