Atrial fibrillation rotor site real-time localization method

Abstract

The application discloses a real-time positioning method for rotor sites of atrial fibrillation. The method performs three-dimensional modeling on an atrium in operation, derives bipolar endocardial electrical signals and electrode positions collected by a multi-pole mapping catheter PENTARAY electrode pair from a CARTO3 system, then calculates average fuzzy entropy of the bipolar endocardial electrical signals, selects electrodes according to the calculated average fuzzy entropy of each electrode, draws a vector through entropy difference between the selected electrode pairs, finds a direction where the rotor is located by using a vector method and an expression, and finally determines a specific position of the rotor through the expression and a relationship between distance and energy. The application adopts endocardial bipolar electrical signals, can well remove ventricular noise, better guides a doctor to find a rotor direction of the atrial fibrillation in operation, accurately positions a specific position of the rotor site, greatly reduces an ablation area, increases a success rate and a recurrence rate of radiofrequency ablation operation, and can have a lower sequelae after operation.

Description

Technical Field

[0001] This invention belongs to the field of atrial fibrillation technology, specifically relating to a real-time location method for atrial fibrillation rotor sites. Background Technology

[0002] Atrial fibrillation (AF) is the most common sustained arrhythmia and causes significant morbidity and mortality. The natural history of AF is characterized by its progression from paroxysmal to sustained, and then to permanent AF over time. Pulmonary vein isolation is fundamental to almost all AF ablation strategies and can be the sole treatment option in many paroxysmal AF cases. However, because the atrial matrix abnormalities are more severe in sustained AF than in paroxysmal AF, additional matrix modification is required after surrounding the pulmonary veins. With advancements in mapping techniques and a better understanding of AF pathogenesis, rotors have been identified as a key factor in maintaining AF. Accurate intraoperative localization and identification of rotors can significantly improve the success rate of radiofrequency ablation for AF and reduce the probability of postoperative complications. Therefore, rotor-guided ablation has become a potential therapeutic target for sustained AF ablation. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a real-time localization method for the atrial fibrillation rotor site. This method utilizes fuzzy entropy combined with vector methods to accurately locate the rotor site while searching for its direction, significantly reducing the ablation area, increasing the success rate and recurrence rate of radiofrequency ablation surgery, and resulting in lower postoperative sequelae.

[0004] To achieve the above objectives, the present invention provides a real-time localization method for the rotor site of atrial fibrillation, comprising the following steps:

[0005] Step 1: During the procedure, the CARTO3 system and the PENTARAY multipolar mapping catheter are used to create a three-dimensional model of the heart.

[0006] Step 2: Export the data collected by the PENTARAY electrode pair of the multi-polar mapping catheter from the CARTO3 system;

[0007] Step 3: Calculate the multi-scale average fuzzy entropy of each bipolar atrial endocardial electrical signal;

[0008] Step 3.1: Perform ensemble empirical mode decomposition on each bipolar atrial endocardial electrical signal to obtain time series of each bipolar atrial endocardial electrical signal at multiple scales.

[0009] Step 3.2: Calculate the fuzzy entropy of the time series of the bipolar atrial endocardial electrical signal at each scale, and obtain the average fuzzy entropy;

[0010] Step 4: Based on the relationship between the magnitude of the multi-scale average fuzzy entropy calculated in Step 3 and the rotor distance, determine the orientation and location of the rotor point.

[0011] Step 4.1: Calculate the orientation vector of the rotor relative to each electrode based on the multi-scale average fuzzy entropy of each electrode.

[0012] Step 4.2: Based on the rotor orientation vector and the relationship between the average fuzzy entropy and distance, the specific position of the rotor is obtained.

[0013] Furthermore, after the modeling is completed in step 2, the data collected by the PENTARAY electrode pairs of the multipolar mapping catheter are exported from the CARTO3 system as 10 bipolar atrial endocardial electrical signals and the position of each electrode pair.

[0014] Furthermore, in step 3.2, a phase-space reconstruction is performed on a time series of a bipolar atrial endocardial electrical signal at one scale to obtain the time series Y(i):

[0015] Y(i)=[x(i),x(i+1),...,x(i+m-1)]-x0(i),1≤i≤N-m+1 (1)

[0016]

[0017] In the formula, N represents the length of the time series, x(i) represents the element value at time point i, x0(i) is the mean of each time point, and m is the embedding dimension.

[0018] Calculate the Chebyshev distance between Y(i) and Y(j) after phase space reconstruction, which is the maximum absolute value of the difference between the numerical values ​​of each element:

[0019]

[0020] In the formula, Let m represent the Chebyshev distance, and m be the embedding dimension.

[0021] Calculating the similarity between time series using fuzzy membership functions:

[0022]

[0023] In the formula, Indicates the similarity between time series. Let be the Chebyshev distance, N be the length of the time series, r be the similarity tolerance, and m be the embedding dimension.

[0024] The fuzzy entropy is calculated as follows:

[0025]

[0026] in,

[0027]

[0028] In the formula, The similarity of time series is represented by N, where N is the length of the time series and m is the embedding dimension.

[0029] The final average fuzzy entropy is obtained by averaging the fuzzy entropy of the bipolar atrial endocardial electrical signal across multiple scales.

[0030]

[0031] In the formula, MeanFuzz represents the average fuzzy entropy, and Fuzz represents the average fuzzy entropy i Let represent the fuzzy entropy at the i-th scale.

[0032] Furthermore, in step 4.1, the electrode signal with the largest average fuzzy entropy is selected from the 10 bipolar signals, and the electrode signal with the largest average fuzzy entropy is used as the base point for vector superposition. In order to use the entropy difference between other electrodes and the base electrode to measure the weight of the rotor on the vector, two electrodes with equal distances to the base point are selected, and the entropy difference between these two electrodes and the base electrode is used as two vectors for superposition.

[0033] The orientation of the final vector obtained is the orientation of the rotor.

[0034] Furthermore, in step 4.2, assuming the rotor coordinates are (x, y), and the coordinates of the two bipolar signals other than the base point are H1(x1, y1) and H2(x2, y2), then the distance from the rotor to H1 is... The distance from the rotor to H2 is Since the square of the distance is inversely proportional to the energy, therefore Right now Substituting the coordinates of the two bipolar signals and the average fuzzy entropy, we obtain the relationship expression between x and y. From the base point coordinates and the rotor orientation vector, we can obtain the expression for the line where the base point and the rotor are located. By combining the two expressions, we can obtain the coordinates of the rotor, and thus the specific position of the rotor.

[0035] Compared with the prior art, the present invention has the following advantages:

[0036] 1) The use of endocardial bipolar electrical signals can effectively remove ventricular noise;

[0037] 2) Using fuzzy entropy and vector methods to measure the rotor orientation of bipolar electrical signals can better guide doctors to find the atrial fibrillation rotor location during surgery;

[0038] 3) The fuzzy entropy combined with vector method can accurately locate the specific position of the rotor site while searching for the direction of the atrial fibrillation rotor, which greatly reduces the ablation area, increases the success rate and recurrence rate of radiofrequency ablation surgery, and can result in lower sequelae after surgery. Attached Figure Description

[0039] Figure 1 This is a flowchart illustrating the real-time rotor positioning process according to an embodiment of the present invention.

[0040] Figure 2 This is a schematic diagram of the PENTARAY catheter.

[0041] Figure 3 This is a schematic diagram of a three-dimensional atrial model and a 2.5s sampled endocardial bipolar electrical signal, representing an embodiment of the present invention.

[0042] Figure 4 The figure shows the average fuzzy entropy result of 10 bipolar electrical signals in the embodiment of the present invention.

[0043] Figure 5 This is a schematic diagram of the rotor location. Detailed Implementation

[0044] This invention provides a real-time location method for atrial fibrillation rotor sites. The technical solution of this invention will be further described below with reference to the accompanying drawings and embodiments.

[0045] like Figure 1 As shown, the present invention provides a real-time localization method for the rotor site of atrial fibrillation, comprising the following steps:

[0046] Step 1: During the procedure, the CARTO3 system and the PENTARAY multipolar mapping catheter are used to perform three-dimensional modeling of the heart.

[0047] Step 2: Export the data collected by the PENTARAY electrode pair of the multi-polar mapping catheter from the CARTO3 system.

[0048] After modeling was completed, 10 bipolar endocardial electrical signals acquired by the PENTARAY electrode pairs of the multipolar mapping catheter, along with the positions of each electrode pair, were exported from the CARTO3 system. For example... Figure 2 As shown, bipolar signals 1-2 refer to the potential difference between electrode 2 and electrode 1, and the other 9 bipolar signals follow the same pattern.

[0049] Step 3: Calculate the multi-scale average fuzzy entropy of each bipolar atrial endocardial electrical signal.

[0050] Step 3.1: Perform ensemble empirical mode decomposition (EEMD) on the 10 bipolar endocardial electrical signals to obtain time series of each bipolar endocardial electrical signal at multiple scales.

[0051] Step 3.2: Calculate the fuzzy entropy of the time series of the bipolar atrial endocardial electrical signal at each scale, and obtain the average fuzzy entropy.

[0052] Phase space reconstruction of a one-scale time series of a bipolar atrial endocardial electrical signal yields the time series Y(i):

[0053] Y(i)=[x(i),x(i+1),...,x(i+m-1)]-x0(i),1≤i≤N-m+1 (1)

[0054]

[0055] In the formula, N represents the length of the time series, x(i) represents the element value at time point i, x0(i) is the mean of each time point, and m is the embedding dimension. In this embodiment, m = 2.

[0056] Calculate the Chebyshev distance between Y(i) and Y(j) after phase space reconstruction, which is the maximum absolute value of the difference between the numerical values ​​of each element:

[0057]

[0058] In the formula, Let m represent the Chebyshev distance, and m be the embedding dimension. In this embodiment, m = 2.

[0059] Calculating the similarity between time series using fuzzy membership functions:

[0060]

[0061] In the formula, Indicates the similarity between time series; is the Chebyshev distance; N is the length of the time series; r is the similarity tolerance, in this embodiment r = 0.15; m is the embedding dimension, in this embodiment m = 2.

[0062] The fuzzy entropy is calculated as follows:

[0063]

[0064] in,

[0065]

[0066] In the formula, The similarity of time series is represented by N, where N is the length of the time series and m is the embedding dimension. In this embodiment, m = 2.

[0067] The average fuzzy entropy is obtained by averaging the fuzzy entropy of the bipolar atrial endocardial electrical signal across multiple scales.

[0068]

[0069] In the formula, MeanFuzz represents the average fuzzy entropy, and Fuzz represents the average fuzzy entropy. i Let represent the fuzzy entropy at the i-th scale.

[0070] Step 4: Based on the relationship between the magnitude of the multi-scale average fuzzy entropy calculated in Step 3 and the rotor distance, determine the orientation and location of the rotor point.

[0071] Step 4.1: Calculate the orientation vector of the rotor relative to each electrode based on the multi-scale average fuzzy entropy of each electrode.

[0072] From the 10 bipolar signals, the signal with the largest average fuzzy entropy is selected. Since the rotor's orientation is related to the orientation of entropy increase, and the orientation of other electrodes to the electrode with the largest entropy is always the orientation of entropy increase, the electrode with the largest average fuzzy entropy is used as the base point for vector superposition. To use the entropy difference between other electrodes and the base electrode to measure the rotor's weight on this vector, it is necessary to select electrode pairs equidistant from the base point. In this embodiment, the two electrodes closest to the base electrode and equidistant from it are selected. Figure 2 As shown, assuming the electrode with the largest average fuzzy entropy is 1-2, the nearest and equidistant electrode pairs are 5-6 and 17-18. Therefore, the entropy difference between 5-6 and 1-2 is used as one vector, and the entropy difference between 17-18 and 1-2 is used as another vector. These vectors are superimposed to obtain the orientation of the final vector, which represents the rotor's location. Figure 4 As shown, the average fuzzy entropies of the 10 endocardial bipolar electrical signals used in this embodiment are 0.46, 0.36, 0.24, 0.31, 0.26, 0.34, 0.38, 0.30, 0.36, and 0.35, respectively. Therefore, the size of the vector from 1-2 to 5-6 is 0.22, and the size of the vector from 1-2 to 17-18 is 0.10. Figure 5 As shown, vector b is the vector from 5-6 to 1-2, vector a is the vector from 17-18 to 1-2, and c is the rotor orientation vector obtained by the final superposition of vectors.

[0073] Step 4.2: Based on the rotor orientation vector and the relationship between the average fuzzy entropy and distance, determine the specific position of the rotor.

[0074] Assuming the rotor coordinates are (x, y), and the coordinates of the two bipolar signals (excluding the base point) are H1(x1, y1) and H2(x2, y2), then the distance from the rotor to H1 is... The distance from the rotor to H2 is Since the square of the distance is inversely proportional to the energy, therefore Right now In this embodiment, the three selected electrodes are 1-2, 5-6, and 17-18. Meanfuzz1 is the average fuzzy entropy of electrode 5-6, and Meanfuzz2 is the average fuzzy entropy of electrode 17-18. Substituting the coordinates of electrodes 5-6 and 17-18 and the average fuzzy entropy, the relationship between x and y is obtained. From the base point coordinates and the rotor orientation vector, the expression for the line connecting the base point and the rotor can be obtained. By combining the two expressions, the coordinates of the rotor can be obtained, thus determining the rotor's specific position. Figure 5 As shown, the final position of the rotor is point R.

[0075] The specific embodiments described herein are merely illustrative of the spirit of the invention. Those skilled in the art to which this invention pertains may make various modifications or additions to the described specific embodiments or use similar methods to replace them, without departing from the spirit of the invention or exceeding the scope defined by the appended claims.

Claims

1. A method for real-time localization of the atrial fibrillation rotor site, characterized in that, Includes the following steps: Step 1: During the procedure, the CARTO3 system and the PENTARAY multipolar mapping catheter are used to create a three-dimensional model of the heart. Step 2: Export the data collected by the PENTARAY electrode pair of the multi-polar mapping catheter from the CARTO3 system; Step 3: Calculate the multi-scale average fuzzy entropy of each bipolar atrial endocardial electrical signal; Step 3.1: Perform ensemble empirical mode decomposition on each bipolar atrial endocardial electrical signal to obtain time series of each bipolar atrial endocardial electrical signal at multiple scales. Step 3.2: Calculate the fuzzy entropy of the time series of the bipolar atrial endocardial electrical signal at each scale, and obtain the average fuzzy entropy; Step 4: Based on the relationship between the magnitude of the multi-scale average fuzzy entropy calculated in Step 3 and the rotor distance, determine the orientation and location of the rotor point. Step 4.1: Calculate the orientation vector of the rotor relative to each electrode based on the multi-scale average fuzzy entropy of each electrode. Select the electrode signal with the largest average fuzzy entropy from all bipolar signals, and use the electrode signal with the largest average fuzzy entropy as the base point for vector superposition; select two electrodes that are equidistant from the base point, and use the entropy difference between these two electrodes and the base point electrode as two vectors to superimpose. The orientation of the final vector obtained is the orientation of the rotor. Step 4.2: Based on the rotor orientation vector and the relationship between average fuzzy entropy and distance, the specific position of the rotor is obtained; Assume the rotor coordinates are The coordinates of the two bipolar signals other than the base point are respectively , Then the distance from the rotor to H1 is The distance from the rotor to H2 is Since the square of the distance is inversely proportional to the energy, therefore ,Right now , , Let H1 and H2 represent the average fuzzy entropy, respectively; substituting the coordinates and average fuzzy entropy of the two bipolar signals, we obtain... x and y The relationship expression can be obtained from the coordinates of the base point and the rotor orientation vector to obtain the expression of the line where the base point and the rotor are located. By combining the two expressions, the coordinates of the rotor can be obtained, and thus the specific position of the rotor can be obtained.

2. The real-time localization method for atrial fibrillation rotor sites as described in claim 1, characterized in that: After modeling is completed in step 2, the data collected by the PENTARAY electrode pairs of the multipolar mapping catheter are exported from the CARTO3 system as 10 bipolar atrial endocardial electrical signals and the position of each electrode pair.

3. The real-time localization method for atrial fibrillation rotor sites as described in claim 1, characterized in that: Step 3.2 involves performing phase-space reconstruction on a one-scale time series of a bipolar atrial endocardial electrical signal to obtain the time series. for: （1） （2） In the formula, N represents the length of the time series. Indicates a point in time i The element value at that position, The mean value at each time point is m, and the embedding dimension is m. Computing time series after phase space reconstruction and The Chebyshev distance is the maximum absolute value of the differences between the values ​​of the elements: （3） In the formula, This represents the Chebyshev distance, where m is the embedding dimension; Calculating the similarity between time series using fuzzy membership functions: （4） In the formula, Indicates the similarity between time series. Let be the Chebyshev distance, N be the length of the time series, r be the similarity tolerance, and m be the embedding dimension.

4. The real-time localization method for atrial fibrillation rotor sites as described in claim 3, characterized in that: The fuzzy entropy calculation method in step 3.2 is as follows: （5） in, （6） In the formula, The similarity of time series is represented by N, where N is the length of the time series and m is the embedding dimension. The final average fuzzy entropy is obtained by averaging the fuzzy entropy of the bipolar atrial endocardial electrical signal across multiple scales. （7） In the formula, Represents the average fuzzy entropy. Let represent the fuzzy entropy at the i-th scale.

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