Unipolar electrogram-based voltage mapping with far-field cancellation to improve detection of abnormal atrial substrate during atrial fibrillation.

INTRODUCTION: An important substrate for atrial fibrillation (AF) is fibrotic atrial myopathy. Identifying low voltage, myopathic regions during AF using traditional bipolar voltage mapping is limited by the directional dependency of wave propagation. Our objective was to evaluate directionally independent unipolar voltage mapping, but with far-field cancellation, to identify low-voltage regions during AF. METHODS: In 12 patients undergoing pulmonary vein isolation for AF, high-resolution voltage mapping was performed in the left atrium during sinus rhythm and AF using a roving 20-pole circular catheter. Bipolar electrograms (EGMs) (Bi) < 0.5 mV in sinus rhythm identified low-voltage regions. During AF, bipolar voltage and unipolar voltage maps were created, the latter with (uni-res) and without (uni-orig) far-field cancellation using a novel, validated least-squares algorithm. RESULTS: Uni-res voltage was ~25% lower than uni-orig for both low voltage and normal atrial regions. Far-field EGM had a dominant frequency (DF) of 4.5-6.0 Hz, and its removal resulted in a lower DF for uni-orig compared with uni-res (5.1 ± 1.5 vs. 4.8 ± 1.5 Hz; p < .001). Compared with Bi, uni-res had a significantly greater area under the receiver operator curve (0.80 vs. 0.77; p < .05), specificity (86% vs. 76%; p < .001), and positive predictive value (43% vs. 30%; p < .001) for detecting low-voltage during AF. Similar improvements in specificity and positive predictive value were evident for uni-res versus uni-orig. CONCLUSION: Far-field EGM can be reliably removed from uni-orig using our novel, least-squares algorithm. Compared with Bi and uni-orig, uni-res is more accurate in detecting low-voltage regions during AF. This approach may improve substrate mapping and ablation during AF, and merits further study.

Quantification of abnormal QRS peaks predicts response to cardiac resynchronization therapy and tracks structural remodeling.

BACKGROUND: Although QRS duration (QRSd) is an important determinant of cardiac resynchronization therapy (CRT) response, non-responder rates remain high. QRS fragmentation can also reflect electrical dyssynchrony. We hypothesized that quantification of abnormal QRS peaks (QRSp) would predict CRT response. METHODS: Forty-seven CRT patients (left ventricular ejection fraction = 23±7%) were prospectively studied. Digital 12-lead ECGs were recorded during native rhythm at baseline and 6 months post-CRT. For each precordial lead, QRSp was defined as the total number of peaks detected on the unfiltered QRS minus those detected on a smoothed moving average template QRS. CRT response was defined as >5% increase in left ventricular ejection fraction post-CRT. RESULTS: Sixty-percent of patients responded to CRT. Baseline QRSd was similar in CRT responders and non-responders, and did not change post-CRT regardless of response. Baseline QRSp was greater in responders than non-responders (9.1±3.5 vs. 5.9±2.2, p = 0.001) and decreased in responders (9.2±3.6 vs. 7.9±2.8, p = 0.03) but increased in non-responders (5.5±2.3 vs. 7.5±2.8, p = 0.049) post-CRT. In multivariable analysis, QRSp was the only independent predictor of CRT response (Odds Ratio [95% Confidence Interval]: 1.5 [1.1-2.1], p = 0.01). ROC analysis revealed QRSp (area under curve = 0.80) to better discriminate response than QRSd (area under curve = 0.67). Compared to QRSd ≥150ms, QRSp ≥7 identified response with similar sensitivity but greater specificity (74 vs. 32%, p<0.05). Amongst patients with QRSd <150ms, more patients with QRSp ≥7 responded than those with QRSp <7 (75 vs. 0%, p<0.05). CONCLUSIONS: Our novel automated QRSp metric independently predicts CRT response and decreases in responders. Electrical dyssynchrony assessed by QRSp may improve CRT selection and track structural remodeling, especially in those with QRSd <150ms.

Reduced T wave alternans in heart failure responders to cardiac resynchronization therapy: Evidence of electrical remodeling.

BACKGROUND: T-wave alternans (TWA), a marker of electrical instability, can be modulated by cardiac resynchronization therapy (CRT). The relationship between TWA and heart failure response to CRT has not been clearly defined. METHODS AND RESULTS: In 40-patients (age 65±11 years, left ventricular ejection-fraction [LVEF] 23±7%), TWA was evaluated prospectively at median of 2 months (baseline) and 8 months (follow-up) post-CRT implant. TWA-magnitude (Valt >0µV, k≥3), its duration (d), and burden (Valt ·d) were quantified in moving 128-beat segments during incremental atrial (AAI, native-TWA) and atrio-biventricular (DDD-CRT) pacing. The immediate and long-term effect of CRT on TWA was examined. Clinical response to CRT was defined as an increase in LVEF of ≥5%. Native-TWA was clinically significant (Valt ≥1.9µV, k≥3) in 68% of subjects at baseline. Compared to native-TWA at baseline, DDD-CRT pacing at baseline and follow-up reduced the number of positive TWA segments, peak-magnitude, longest-duration and peak-burden of TWA (44±5 to 33±5 to 28±4%, p = 0.02 and 0.002; 5.9±0.8 to 4.1±0.7 to 3.8±0.7µV, p = 0.01 and 0.01; 97±9 to 76±8 to 67±8sec, p = 0.004 and <0.001; and 334±65 to 178±58 to 146±54µV.sec, p = 0.01 and 0.004). In addition, the number of positive segments and longest-duration of native-TWA diminished during follow-up (44±5 to 35±6%, p = 0.044; and 97±9 to 81±9sec, p = 0.02). Clinical response to CRT was observed in 71% of patients; the reduction in DDD-CRT paced TWA both at baseline and follow-up was present only in responders (interaction p-values <0.1). CONCLUSION: Long-term CRT reduces the prevalence and magnitude of TWA. This CRT induced beneficial electrical remodeling is a marker of clinical response after CRT.

Automated Quantification of Low-Amplitude Abnormal QRS Peaks From High-Resolution ECG Recordings Predicts Arrhythmic Events in Patients With Cardiomyopathy.

BACKGROUND: Cardiomyopathy patients are at risk of sudden death, typically from scar-related abnormalities of electrical activation that promote ventricular tachyarrhythmias. Abnormal intra-QRS peaks may provide a measure of altered activation. We hypothesized that quantification of such QRS peaks (QRSp) in high-resolution ECGs would predict arrhythmic events in implantable cardioverter-defibrillator (ICD)-eligible cardiomyopathy patients. METHODS AND RESULTS: Ninety-nine patients with ischemic or non-ischemic dilated cardiomyopathy undergoing prophylactic ICD implantation were prospectively enrolled (age 62±11 years, left ventricular ejection fraction 27±7%). High-resolution (1024 Hz) digital 12-lead ECGs were recorded during intrinsic rhythm. QRSp was quantified for each precordial lead as the total number of low-amplitude deflections that deviated from their respective naive QRS template. The primary end point of arrhythmic events was defined as appropriate ICD therapy or sustained ventricular tachyarrhythmias. After a median follow-up of 24 (15-43) months, 20 (20%) patients had arrhythmic events. Both QRSp and QRS duration were greater in those with arrhythmic events (both P<0.001) and this was consistent for QRSp for both cardiomyopathy types. In a multivariable Cox regression model that included age, left ventricular ejection fraction, QRS duration, and QRSp, only QRSp was an independent predictor of arrhythmic events (hazard ratio, 2.1; P<0.001). Receiver operating characteristic analysis revealed that a QRSp ≥2.25 identified arrhythmic events with greater sensitivity (100% versus 70%, P<0.05) and negative predictive value (100% versus 89%, P<0.05) than QRS duration ≥120 ms. CONCLUSIONS: QRSp measured from high-resolution digital 12-lead ECGs independently predicts ventricular tachyarrhythmias in ICD-eligible cardiomyopathy patients. This novel QRS morphology index has the potential to improve sudden death risk stratification and patient selection for prophylactic ICD therapy.

Spatial Relationships of Complex Fractionated Atrial Electrograms and Continuous Electrical Activity to Focal Electrical Sources: Implications for Substrate Ablation in Human Atrial Fibrillation.

OBJECTIVES: This study sought to evaluate the spatial relationships of focal electrical sources (FSs) to complex fractionated atrial electrograms (CFAE) and continuous electrical activity (CEA). BACKGROUND: Fractionated atrial electrograms have been associated with atrial fibrillation (AF) drivers in computational studies and represent ablation targets in the management of persistent AF. METHODS: We included a subset of 66 patients (age: 63 [56, 67] years, 69% persistent AF) with electroanatomic data from the SELECT AF (Selective complex fractionated atrial electrograms targeting for atrial fibrillation) randomized control trial that compared the efficacy of CFAE with CEA ablation in AF patients undergoing pulmonary vein antral ablation. Focal sources were identified based on bipolar electrogram periodicity and QS unipolar electrogram morphology. RESULTS: A total of 77 FSs (median: 1 [1st quartile, 3rd quartile: 1, 2] per patient) were identified most commonly in the pulmonary vein antrum and left atrial appendage. The proportions of FSs inside CFAE and CEA regions were similar (13% vs. 1.3%, respectively; p = 0.13). Focal sources were more likely to be on the border zone of CFAEs than in CEAs (49% vs. 7.8%, respectively; p = 0.012). Following ablation, 53% of patients had ≥1 unablated extrapulmonary vein FS. The median number of unablated FS was higher in patients with AF recurrence post ablation than in patients without (median: 1 [0, 1] vs. 0 [0, 1], respectively; p = 0.026). CONCLUSIONS: One-half of the FSs detected during AF localized to the border of CFAE areas, whereas most of the FSs were found outside CEA areas. CFAE or CEA ablation leaves a number of FS unablated, which is associated with AF recurrence. These findings suggest that many CFAEs may arise from passive wave propagation, remote from FS, which may limit their therapeutic efficacy in AF substrate modification.

An algorithm for rotor tracking in atrial fibrillation using graph search-based periodic peak detection.

Rotors are rotating electrical waves that may sustain atrial fibrillation (AF); thereby providing therapeutic targets for catheter ablation. We propose a method for identifying rotors from circular catheter recordings of bipolar intracardiac electrograms (EGM) during AF. We use dominant frequency-based periodicity detection along with a graph search algorithm to identify the most dominant periodic activations or peaks of interest in each bipolar EGM recorded by a multipolar circular catheter. We then track the activations across catheter bipoles to determine whether they conform to the rotational pattern of a rotor. The performance of the proposed method is tested on simulated bipolar EGM arrays containing rotor activation corrupted by noise and complex aperiodic signal features. The method is shown to perform with high accuracy (up to 98% sensitivity and 100% specificity) in detecting simulated rotors and may serve to guide rotor ablation in patients with AF.

Identification and annotation of multiple periodic pulse trains using dominant frequency and graph search: Applications in atrial fibrillation rotor detection.

Biological signals, such as intracardiac electrograms during atrial fibrillation (AF), can contain multiple periodic components or peaks. We propose a method for identifying individual periodic peak trains in signals containing multiple such periodic sequences. We use dominant frequency-based periodicity detection along with a graph search algorithm to identify the most dominant periodic activation set or peaks of interest. We then remove these peaks and iterate until all periodic sequences are identified. The proposed method is tested on simulated AF intra-cardiac electrograms with periodic activation trains of three distinct frequencies corrupted by noise and complex aperiodic signal features. The method is shown to have high accuracy (up to 100% sensitivity and 100% specificity) in detecting the three individual periodic peak trains. The method has application in biomedical signal analysis, such as detecting the periodic activations of a rotor, amidst other periodic activations during AF.

Hierarchical Schema for Identifying Focal Electrical Sources During Human Atrial Fibrillation: Implications for Catheter-Based Atrial Substrate Ablation.

OBJECTIVES: The study sought to localize focal sources (FS) during atrial fibrillation (AF) using periodic component analysis (PiCA) and QS unipolar electrogram (EGM) morphology based on the assumption that periodic activation with centrifugal propagation is inherent to a FS. BACKGROUND: The localization of FS maintaining AF remains challenging, due to limitations in conventional time-frequency domain analysis. This is relevant to identifying targets for AF substrate ablation. METHODS: In 41 patients (age 56 ± 9 years, 76% persistent AF), bipolar EGMs were recorded in the left atrium (LA) during AF with a roving 20-pole catheter. Bipolar EGMs with periodicity were determined using PiCA. FS were defined as periodic sites with predominantly QS unipolar EGM morphology. RESULTS: For each patient, 456 ± 109 bipolar EGMs were recorded, of which 261 ± 15 (60%) demonstrated periodicity. FS were identified in 63% of patients (pulmonary vein [PV] 1.5 ± 1.5; extra-PV 2.6 ± 2.3). After PV antral ablation and follow-up of 14 ± 9 months, 37% of patients had symptomatic AF recurrence. Mean global LA periodicity cycle length was shorter in patients with AF recurrence compared to those without (143 ± 20 ms vs. 154 ± 9 ms; p = 0.02). Among 12 (29%) patients with FS exclusively in the PV, only 1 (8%) had AF recurrence. AF recurrence was significantly higher (50%; p = 0.01) in 14 (34%) patients with extra-PV FS. CONCLUSIONS: Our novel hierarchical analysis schema, incorporating PiCA and unipolar EGM morphology, detected a small number of FS in patients with predominantly persistent AF. FS in the PV was associated with successful PV antral ablation. Further prospective studies are required to determine whether these FS maintain AF and represent ablation targets.

Relationship of bipolar and unipolar electrogram voltage to scar transmurality and composition derived by magnetic resonance imaging in patients with nonischemic cardiomyopathy undergoing VT ablation.

BACKGROUND: Bipolar voltage mapping has a role in defining endocardial-based scar in postinfarct patients undergoing ventricular tachycardia catheter ablation. The utility of bipolar and unipolar voltages in characterizing scar has not been evaluated in patients with nonischemic cardiomyopathy. OBJECTIVE: To relate left ventricular (LV) endocardial bipolar and unipolar voltages in these patients to scar transmurality (endocardial vs nonendocardial) and composition (homogeneous core vs heterogeneous gray). METHODS: Ten consecutive cardiomyopathy patients undergoing endocardial LV tachycardia ablation were included (age 48 ± 14 years; left ventricular ejection fraction 43% ± 15%). Preablation late gadolinium-enhanced magnetic resonance imaging was used to quantify core and gray scar by using signal-intensity thresholding. Electroanatomic LV endocardial mapping provided bipolar and unipolar voltages. Electroanatomic maps and late gadolinium-enhanced magnetic resonance imaging were rigidly registered in order to relate voltage to scar (registration error 3.6 ± 2.9 mm). RESULTS: Bipolar voltage was lower in endocardial core than in no scar (P <.001). Unipolar voltage was lower in endocardial core and nonendocardial core than in no scar (P <.001). Endocardial and nonendocardial gray scar had an effect similar to that of core in reducing bipolar and unipolar voltages (P <.001). The mass of healthy myocardium and endocardial core scar independently predicted bipolar and unipolar voltages using general estimating equation modeling. With receiver operating characteristic curve analysis, bipolar voltage >1.9 mV and unipolar voltage <6.7 mV had a high negative predictive value (91%) for detecting nonendocardial scar from either endocardial scar or no scar. CONCLUSIONS: In patients with nonischemic cardiomyopathy, LV endocardial bipolar voltage is dependent on endocardial core and gray scar, while the unipolar voltage is influenced by core and gray scar across the LV wall as defined by late gadolinium-enhanced magnetic resonance imaging.

Fast feature based multi slice to volume registration using phase congruency.

Slice to volume registration is very useful in many medical imaging applications, for example, fusing static high resolution three dimensional (3D) image volumes to dynamic two dimensional (2D) slice data for deriving motion information in 3D. Though information theoretic registration methods such as Mutual Information are usually robust, they are time intensive and typically require a high level of field-of-view correspondence between the source and target images. In single slice to volume registration scenarios, where such correspondence is limited, registration accuracy and robustness often deteriorate. In this paper, we present a novel registration method that maintains robustness and accuracy while significantly increasing registration speed. Our approach employs multiple slice (as opposed to single slice) to volume registration, which increases the amount of potential matching information while maintaining a small number of slices and hence facilitates the often necessary high speed dynamic image acquisition. Our proposed registration approach first extracts phase congruency information from the slices/volume using oriented 2D Gabor wavelets. Using local non maximum suppression, we then automatically obtain a robust and accurate set of feature points that are subsequently matched using an Iterative Closest Point (ICP) approach. Validation on BrainWeb simulated magnetic resonance imaging (MRI) data showed significant gains in speed ( approximately 40-fold increase) when compared to conventional Mutual Information based volumetric registration while maintaining comparable robustness and accuracy levels.

Multi-contrast MR for enhanced bone imaging and segmentation.

Musculoskeletal applications of MRI are increasing rapidly but a major challenge for researchers is the ability to efficiently and accurately segment structures of interest, such as bone, which is typically required to perform further quantitative analyses. Manual tracing is extremely time consuming and introduces problematic user variability. Automated segmentation is usually preferred; however, the accuracy and robustness of current methods still suffer from significant limitations. In this paper, we propose a novel approach for simplifying such segmentation tasks by optimizing MR protocols specifically for bone data acquisition. We present multi-contrast MR bone data acquired using short-TR T1W and fat suppression scans and demonstrate how this data can be used within an automated segmentation framework in order to improve accuracy of bone segmentation. Validation was performed on knee joint data with quantitative segmentation results on our multi-contrast data showing superior performance compared to results obtained using conventional single-contrast data. Improvements in contrast to noise ratio of 39.24 and in sensitivity and specificity of 4.09% and 4.17%, respectively, for the tibia, and 4.4% and 5.74% for the femur, were achieved.