Cell Unexcitability and Electrotonic Coupling Phenomenon Analysis of Ablation-Created Lesions: A Study Case with Ablated Explanted Human Heart.

This study investigates the effects of radiofrequency ablation (RFA)-created lesions on an explanted human heart in wedge preparation by simultaneous endo and sub-endo optical mapping. The heart in Langendorff perfusion was ablated under 40 W. The ventricle was stained with Vm sensitive dye Di-4-ANBDQPQ and two excitation light bands of different penetration depths were used (red = 660 nm, green = 525 nm) to perform a conduction velocity (CV) difference analysis for identification of CV alter-nans. The relative change in fluorescence (ΔF/F) traces were analyzed before and after ablation. Local activation time (LAT) was determined by the 50% approach. Local CV was obtained using the circle method, and RFA created lesions were characterized by examining the CV alternans correlated with transmural heterogeneities. The presence of CV alternans results from reduced excitability in a non-homogeneous lesion consisting of excitable and non-excitable cells. The absence of CV alternans in optical mapping with green light and their presence with deep-red light illustrates incomplete ablation across the ventricular wall or non-homogeneous ablation in the mid-myocardial layer. The presence of an intramural scar impairs the efficacy of the RFA procedure, suggesting a need for alternative ablations strategies.

A robust wavelet-based approach for dominant frequency analysis of atrial fibrillation in body surface signals.

OBJECTIVE: Atrial dominant frequency (DF) maps undergoing atrial fibrillation (AF) presented good spatial correlation with those obtained with the non-invasive body surface potential mapping (BSPM). In this study, a robust BSPM-DF calculation method based on wavelet analysis is proposed. APPROACH: Continuous wavelet transform along 40 scales in the pseudo-frequency range of 3-30 Hz is performed in each BSPM signal using a Gaussian mother wavelet. DFs are estimated from the intervals between the peaks, representing the activation times, in the maximum energy scale. The results are compared with the traditionally widely applied Welch periodogram and the robustness was tested on different protocols: increasing levels of white Gaussian noise, artificial DF harmonics presence and reduction in the number of leads. A total of 11 AF simulations and 12 AF patients are considered in the analysis. For each patient, intracardiac electrograms were acquired in 15 locations from both atria. The accuracy of both methods was assessed by calculating the absolute errors of the highest DF BSPM (HDF BSPM ) with respect to the atrial HDF, either simulated or intracardially measured, and assumed correct if ≤1 Hz. The spatial distribution of the errors between torso DFs and atrial HDFs were compared with atria driving mechanism locations. Torso HDF regions, defined as portions of the maps with [Formula: see text] Hz were identified and the percentage of the torso occuping these regions was compared between methods. The robustness of both methods to white Gaussian noise, ventricular influence and harmonics, and to lower spatial resolution BSPM lead layouts was analyzed: computer AF models (567 leads vs 256 leads down to 16 leads) and patient data (67 leads vs 32 and 16 leads). MAIN RESULTS: The proposed method allowed an improvement in non-invasive estimation of the atria HDF. For the models the median relative errors were 7.14% for the wavelet-based algorithm vs 60.00% for the Welch method; in patients, the errors were 10.03% vs 12.66%, respectively. The wavelet method outperformed the Welch approach in correct estimations of atrial HDFs in models (81.82% vs 45.45%, respectively) and patients (66.67% vs 41.67%). A low positive BSPM-DF map correlation was seen between the techniques (0.47 for models and 0.63 for patients), highlighting the overall differences in DF distributions. The wavelet-based algorithm was more robust to white Gaussian noise, residual ventricular activity and harmonics, and presented more consistent results in lead layouts with low spatial resolution. SIGNIFICANCE: Estimation of atrial HDFs using BSPM is improved by the proposed wavelet-based algorithm, helping to increase the non-invasive diagnostic ability in AF.

Analysis of QRS-T subtraction in unipolar atrial fibrillation electrograms.

This paper presents a QRS-T subtraction approach for atrial fibrillation (AF) intracardiac atrial electrograms (AEG). It also presents a comparison between the proposed method and two alternative ventricular subtraction techniques: average beat subtraction (ABS) using a fixed length window and an approach based on flat interpolation for QRS cancellation. Areas of the atrium close to the mitral valve showed stronger ventricular influence on the AEGs when compared with the remaining atrial regions. Ventricular influence affects the spectral power distribution of the AEG and can also affect the estimation of the dominant frequency unless the whole ventricular activity influence (QRS-T) is removed. The average power after QRS-T subtraction is significantly reduced for frequencies above 10 Hz (mostly associated with QRS complexes), as well as for frequencies between 3 and 5.5 Hz, (mostly related to T waves). The results indicate that the proposed approach removes ventricular influence on the AF AEGs better than the QRS cancellation method. Spectral analysis showed that both the ABS and the proposed method do well and no method should be preferred to the other. In the time domain, the proposed approach is matched to the lengths and timings of onset and offset for individual QRS-T segments while the ABS approach uses an arbitrary length around the QRS for the pattern used for QRS-T removal.

QRS subtraction for atrial electrograms: flat, linear and spline interpolations.

The main objective of this article is to implement and compare QRS subtraction techniques for intra-cardiac atrial electrograms based on using the surface ECG as a reference. A band-pass filter between 8 and 20 Hz followed by rectification, and then a low-pass filter at 6 Hz are used for QRS detection. QRS subtraction was performed using three different approaches: flat, linear and spline interpolations. QRS subtraction affects the power of the signals but it normally does not affect the dominant frequency. The average power of the atrial electrograms after QRS subtraction is significantly reduced for frequencies above 10 Hz.