Automatic measurement and display of post-pacing intervals

Abstract

To provide methods for automatic post pacing interval measurement and display.SOLUTION: A method is provided. The method is implemented by executing a determination engine stored on a memory as a processor executable code that is executed by a processor. The method includes determining that a stimulating pacing signal is captured from at least a portion of an anatomical structure, and determining a time duration between the stimulating pacing signal and a subsequent response from the portion of an anatomical structure. The method further includes outputting the time duration.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a method and system for signal processing. More specifically, the present invention relates to a method and system for signal processing that provides for the automatic measurement and display of post-pacing intervals.

Background Art

[0002] The treatment of heart diseases such as arrhythmia often requires analyzing a specific area or focus of heart tissue through catheter-based pacing. Pacing involves using the electrodes of a catheter to supply very short current pulses to activate the tissue within a given area (e.g., the pacing / collection site), and generating electrical waves from a specific point (e.g., sinus rhythm from the excitation gap of the circuit) in order to identify the origin (i.e., focus) of the arrhythmia. The given area may be as large as the area covered by the patches of a defibrillator. Since sinus rhythms follow one another, sinus rhythm can be likened to dominoes.

[0003] One aspect of pacing involves identifying the post-pacing interval (PPI). The PPI is generally the time from the last pace signal to the next spontaneous activity. In some cases, the PPI can be the time it takes for the last stimulated wavefront to reach the excitation gap of the circuit, travel around the circuit, and return to the pacing / collection site (e.g., a given area). When the pacing site is within the circuit (e.g., a given area and a specific point coincide), the PPI is equal to the tachycardia cycle length (TCL). However, as the pacing site moves away from the circuit, the difference between PPI - TCL increases correspondingly.

[0004] Conventionally, cardiologists have been manually determining the PPI. For example, a cardiologist supplies a simulated pacing signal and manually determines the PPI (e.g., 200 milliseconds) at which the simulated pacing signal returns to the pacing / collection site. Then, for that PPI, the cardiologist introduces a clinical interpretation. [Overview of the project] [Problems that the invention aims to solve]

[0005] However, this conventional method of assessment is time-consuming and prone to inaccuracies. Automatically observing and / or determining PPI would be advantageous. Therefore, a method for automatic measurement and display of PPI is desirable. [Means for solving the problem]

[0006] A method is provided by exemplary embodiments. The method is implemented by executing a decision engine stored in memory as processor-executable code that is executed by a processor. The method includes determining that a stimulus pacing signal is captured from at least a portion of an anatomical structure, and determining the duration between the stimulus pacing signal and a subsequent response from that portion of the anatomical structure. The method further includes outputting the duration.

[0007] According to one or more embodiments, the exemplary methods described above can be implemented as devices, systems, and / or computer program products. [Brief explanation of the drawing]

[0008] A more detailed understanding can be obtained from the following explanation, which is provided as an example in conjunction with the attached drawings, where similar reference numbers in the drawings indicate similar elements. [Figure 1] This is a diagram of an exemplary system that can implement one or more features of the subject matter of this disclosure by one or more embodiments. [Figure 2] This is a block diagram of an exemplary system for automatic measurement and display of post-pacing intervals, according to one or more embodiments. [Figure 3] An exemplary method is shown according to one or more embodiments. [Figure 4]An exemplary method is shown by one or more exemplary embodiments. [Figure 5] This shows an exemplary interface in one or more embodiments. [Modes for carrying out the invention]

[0009] This specification discloses pacing and diagnostic methods and systems for signal processing, the signal processing by which these methods and systems relate at least to the automated measurement and display of PPI. More specifically, cardiac pacing and diagnostic devices include processor-executable code or software that is necessarily rooted in the processing hardware of such medical devices and instruments, and in the process operations of a medical device instrument that provides a method for automated measurement and display of PPI.

[0010] According to one embodiment, the cardiac pacing and diagnostic device provides specific pacing and capture operations involving multi-step manipulation of electrical signals to the tissue of an anatomical structure in order to more accurately understand the electrophysiology of the tissue of that structure. For ease of explanation, the pacing and diagnostic method and system is described herein in relation to mapping the heart, but any anatomical structure, body part, organ, or part thereof can be the target of mapping by the pacing and diagnostic method and system described herein.

[0011] For example, the pacing and diagnostic method and system includes a determination engine. That is, when the pacing and diagnostic method and system performs the pacing technique, it is necessary not only to know how long the pacing itself will last (e.g., the timing of the pacing) and to identify when the activity will pass through the electrode 111 (e.g., to measure the time until the next activity), but also to confirm that the pacing has captured the tissue (e.g., that the pacing of the focus was successful). Since there is always a possibility that the tissue will not be captured due to improper catheter contact, incorrect timing of pacing (e.g., spontaneous activation of the tissue), or failure to achieve pacing, the determination engine complements the pacing technique by understanding how the electrical signal flows through the circuit (e.g., how the wave propagates). For example, it may determine that the stimulation-pacing signal has been captured from at least a portion of the anatomical structure, determine the duration between the stimulation-pacing signal and the subsequent response from that portion of the anatomical structure, and output the duration.

[0012] One or more advantages, technical effects, and / or benefits of the determination engine may include providing cardiologists and healthcare professionals with automated PPI determination based on detecting signals read after the last stimulus signal. Thus, the determination engine specifically utilizes and transforms medical devices to enable / implement automated PPI determination that is not currently available by other means or is currently performed by cardiologists and healthcare professionals (for example, so that the user may no longer need to track the time between the last stimulus and the signal reading).

[0013] Figure 1 is a diagram of an exemplary system (e.g., a medical device) shown as System 100, which can implement one or more features of the subject matter of this specification according to one or more embodiments. All or part of System 100 may be used to collect information (e.g., biometric data and / or training data sets) and / or to implement machine learning and / or artificial intelligence algorithms (e.g., decision engine 101) as described herein. System 100 shown in the figure includes a probe 105 with a catheter 110 (including at least one electrode 111), a shaft 112, a sheath 113, and a manipulator 114. System 100 shown in the figure also includes a physician 115 (or medical professional or clinician), a heart 120, a patient 125, and a bed 130 (or table). Note that inserts 140 and 150 show the heart 120 and catheter 110 in more detail. System 100 also includes a console 160 (including one or more processors 161 and memory 162) and a display 165, as shown in the figure. Furthermore, note that each element and / or item of System 100 represents one or more of its elements and / or items. The example of System 100 shown in Figure 1 can be modified to implement the embodiments disclosed herein. Embodiments of this disclosure can also be applied in a similar manner using other system components and settings. Furthermore, System 100 may include further components such as elements for sensing electrical activity, wired or wireless connectors, processing and display devices.

[0014] System 100 can be used to detect, diagnose, and / or treat cardiac conditions (for example, using a determination engine 101). Cardiac conditions such as cardiac arrhythmias remain common and dangerous medical conditions, particularly in the elderly population. For example, System 100 can be part of a surgical system (e.g., the CARTO® system sold by Biosense Webster) configured to acquire biometric data (e.g., anatomical and electrical measurements of a patient's organs, such as the heart 120) and perform cardiac ablation procedures. More specifically, in the treatment of cardiac diseases such as cardiac arrhythmias, it is often necessary to obtain detailed mapping of cardiac tissue, cardiac chambers, veins, arteries, and / or electrical pathways. For example, as a prerequisite for successful catheter ablation (as described herein), the cause of the cardiac arrhythmia may be precisely localized in the cardiac chambers of the heart 120. Such localization can be performed by electrophysiological testing, during which spatially resolved potentials can be detected by a mapping catheter (e.g., catheter 110) introduced into the cardiac chambers of the heart 120. Therefore, this electrophysiological examination, so-called electroanatomical mapping, provides 3D mapping data that can be displayed on a monitor. In many cases, the mapping function and the therapeutic function (e.g., ablation) are provided by a single catheter or a group of catheters, and the mapping catheter also operates simultaneously as a therapeutic (e.g., ablation) catheter. In this case, the determination engine 101 can be directly stored and executed by the catheter 110.

[0015] In patients with a normal sinus rhythm (NSR) (e.g., patient 125), the heart (e.g., heart 120), including the atria, ventricles, and excitatory conduction tissue, is electrically excited and beats in a synchronized, patterned manner. This electrical excitation can be detected as intracardiac electrocardiogram (IC ECG) data, for example.

[0016] In patients with cardiac arrhythmias (e.g., atrial fibrillation, i.e., aFib) (e.g., patient 125), abnormal areas of cardiac tissue do not follow the synchronous beating cycle associated with normal conductive tissue, in contrast to patients with NSR. Instead, abnormal conduction occurs in adjacent tissues within the abnormal areas of cardiac tissue, disrupting the cardiac cycle and resulting in an asynchronous rhythm. It should be noted that this asynchronous rhythm can also be detected as IC ECG data. Such abnormal conduction is known to occur in various regions of the heart 120, such as the sinoatrial (SA) node region along the conduction pathway of the atrioventricular (AV) node, or the myocardial tissue forming the walls of the ventricles and atria. Other conditions also exist, such as atrial flutter, in which patterns of abnormally conductive tissue lead to re-entry pathways, causing the cardiac chambers to beat in a regular pattern that can be several times more frequent than the sinus rhythm.

[0017] To assist the system 100 in detecting, diagnosing, and / or treating the condition of the heart, a physician 115 can guide the probe 105 into the heart 120 of a patient 125 lying on a bed 130. For example, the physician 115 can insert the shaft 112 through the sheath 113 while manipulating the distal end of the shaft 112 using a manipulator 114 and / or deflection from the sheath 113 near the proximal end of the catheter 110. The catheter 110 can be attached to the distal end of the shaft 112 as shown in inset 140. The catheter 110 can be inserted through the sheath 113 in a folded state and then expanded within the heart 120.

[0018] Generally, electrical activity at a point within the heart 120 can usually be measured by advancing a catheter 110, which houses an electrical sensor (e.g., at least one electrode 111) at or near its distal tip, to that point within the heart 120, bringing the tissue into contact with the sensor, and acquiring data at that point. One difficulty associated with mapping the cardiac chambers using catheter types that house only a single distal tip electrode is that it can take a long time to collect data point by point across the required number of points for a detailed map of the entire cardiac chamber. Therefore, multi-electrode catheters (e.g., catheter 110) have been developed to simultaneously measure electrical activity at multiple points within the cardiac chambers.

[0019] A catheter 110, which may include at least one electrode 111 and a catheter needle connected to its body, can be configured to obtain biometric data, such as electrical signals, from an internal organ (e.g., the heart 120) and / or to ablate a tissue region (e.g., the cardiac chambers of the heart 120). Note that the electrode 111 may represent any similar element, such as a tracking coil, a piezoelectric transducer, an electrode, or a combination of elements configured to ablate a tissue region or obtain biometric data. According to one or more embodiments, the catheter 110 may include one or more position sensors used to determine trajectory information. This trajectory information can be used to infer kinetic properties, such as tissue contractility.

[0020] Biometric data (e.g., patient biometrics, patient data, or patient biometric data) may include one or more of the following: local activation time (LAT), electrical activity, topology, bipolar mapping, baseline activity, ventricular activity, dominant frequency, impedance, etc. LAT may be the time of threshold activity corresponding to local activation, calculated based on a normalized initial start point. Electrical activity may be any applicable electrical signal that can be measured based on one or more thresholds and may be detected and / or augmented based on signal-to-noise ratio and / or other filters. Topology may correspond to the physical structure of a body part or part of a body part, or to variations in the physical structure of different parts of a body part or different parts of a body part. Dominant frequency may be a frequency or range of frequencies commonly found in a part of a body part and may differ in different parts of the same body part. For example, the dominant frequency of the PV of the heart may differ from the dominant frequency of the right atrium of the same heart. Impedance may be a resistance measurement in a given region of a body part.

[0021] Examples of biometric measurement data include, but are not limited to, patient identification data, IC ECG data, bipolar intracardiac reference signals, anatomical and electrical measurements, trajectory information, body surface (BS) ECG data, historical data, brain biometric measurements, blood pressure data, ultrasonic signals, wireless signals, voice signals, two-dimensional or three-dimensional image data, blood glucose data, and temperature data. Biometric measurement data can generally be used to monitor, diagnose, and treat any number of various diseases such as cardiovascular diseases (e.g., arrhythmia, cardiomyopathy, and coronary artery disease), and autoimmune diseases (e.g., type I and type II diabetes). Note that BS ECG data can include data and signals collected from electrodes on the patient's surface, IC ECG data can include data and signals collected from electrodes within the patient's body, and ablation data can include data and signals collected from ablated tissue. Further, BS ECG data, IC ECG data, and ablation data can be derived from one or more treatment records together with catheter electrode position data.

[0022] For example, catheter 110 can use electrode 111 to perform intravascular ultrasound and / or MRI catheterization to image the heart 120 (e.g., acquire and process biometric measurement data). Insertion diagram 150 shows an enlarged view of catheter 110 within the heart chamber of heart 120. Although catheter  110 is shown as a point catheter, it will be understood that any shape including one or more electrodes 111 can be used to implement the embodiments disclosed herein.

[0023] Examples of the catheter 110 include, but are not limited to, a linear catheter having a plurality of electrodes, a balloon catheter including electrodes dispersed on a plurality of spines forming a balloon, a lasso catheter or a loop catheter having a plurality of electrodes, or any other applicable shape. The linear catheter may be fully or partially elastic so that it can twist, bend, and / or change its shape in other ways based on the received signal and / or based on the action of an external force (e.g., heart tissue) on the linear catheter. The balloon catheter can be designed to hold its electrodes in close contact with the endocardial surface when deployed within the patient's body. As an example, the balloon catheter can be inserted into a lumen such as a pulmonary vein (PV). The balloon catheter can be inserted into the PV in a contracted state, such that the balloon catheter does not occupy its maximum volume while inserted into the PV. The balloon catheter can expand while inside the PV, such that the electrodes on the balloon catheter contact the entire circular portion of the PV. Such contact with the entire circular portion of the PV or any other lumen enables efficient imaging and / or ablation.

[0024] According to other examples, the body patch and / or the BS electrodes can also be placed on or in proximity to the patient 125's body. A catheter 110 having one or more electrodes 111 can be placed inside the body (e.g., inside the heart 120), and the position of the catheter 110 can be determined by the system 100 based on signals transmitted and received between one or more electrodes 111 of the catheter 110 and the body patch and / or the BS electrodes. Further, the electrodes 111 can sense biometric measurement data from inside the patient 125's body, such as inside the heart  120 (e.g., the electrodes 111 sense the tissue potential in real time). The biometric measurement data can be associated with the determined position of the catheter 110, thereby displaying a rendering of the patient's body part (e.g., the heart 120) and showing the biometric measurement data superimposed on the shape of the body part.

[0025] The probe 105 and other items of the system 100 can be connected to the console 160. The console 160 may include any computing device that employs machine learning and / or artificial intelligence algorithms (represented as the decision engine 101). According to one embodiment, the console 160 includes one or more processors 161 (any computing hardware) and memory 162 (any non-temporary tangible medium), where one or more processors 161 execute computer instructions relating to the decision engine 101, and memory 162 stores these instructions for execution by one or more processors 161. For example, the console 160 may be configured to receive and process biometric data and determine whether a given tissue region conducts electricity. In some embodiments, the console 160 may be further programmed by the decision engine 101 (in software) to perform functions of determining that a stimulus pacing signal is captured from at least a portion of an anatomical structure, determining the duration between the stimulus pacing signal and the subsequent response from that portion of the anatomical structure, and outputting the duration. According to one or more embodiments, the determination engine 101 may be located outside the console 160, for example, within the catheter 110, within an external device, within a mobile device, within a cloud-based device, or as a standalone processor. In this regard, the determination engine 101 may be transferable / downloadable in electronic form over a network.

[0026] In one embodiment, the console 160 may be any computing device including hardware such as a general-purpose computer (e.g., a processor 161 and memory 162), which includes a front-end and interface circuitry suitable for sending and receiving signals to and from software (e.g., a decision engine 101) and / or the probe 105, and for controlling other components of the system 100, as described herein. For example, the front-end and interface circuitry may include an input / output (I / O) communication interface that enables the console 160 to receive signals from and / or transfer signals to at least one electrode 111. The console 160 may typically include a real-time noise reduction circuitry configured as a field-programmable gate array (FPGA), followed by an analog-to-digital (A / D) ECG or electromyogram (EMG) signal conversion integrated circuit. Console 160 can transmit signals from an A / D ECG or EMG circuit to another processor and / or can be programmed to perform one or more of the functions disclosed herein.

[0027] A display 165, which may be any electronic device for visually presenting biometric data, is connected to the console 160. According to one embodiment, during a procedure, the console 160 can facilitate the presentation of a rendering of a body part to the physician 115 on the display 165 and store data representing the rendering of the body part in memory 162. For example, a map showing motor characteristics can be rendered / constructed based on trajectory information sampled at a sufficient number of points within the heart 120. As an example, the display 165 may include a touchscreen that, in addition to presenting a rendering of a body part, can be configured to receive input from the medical professional 115.

[0028] In some exemplary embodiments, the physician 115 can manipulate the rendering of elements and / or body parts of the system 100 using one or more input devices such as a touchpad, mouse, keyboard, or gesture recognition device. For example, the position of the catheter 110 can be changed using the input device so that the rendering is updated. Note that the display 165 may be located in the same location or in a remote location such as another hospital or another healthcare provider network.

[0029] According to one or more embodiments, the system 100 can also obtain biometric data using ultrasound, computed tomography (CT), MRI, or other medical imaging techniques utilizing the catheter 110 or other medical devices. For example, the system 100 can obtain ECG data and / or anatomical and electrical measurements (e.g., biometric data) of the heart 120 using one or more catheters 110 or other sensors. More specifically, the console 160 can be connected by cable to a BS electrode, which includes an adhesive skin patch attached to the patient 125. The BS electrode can acquire / generate biometric data in the form of BS ECG data. For example, the processor 161 can determine the position coordinates of the catheter 110 within a body part of the patient 125 (e.g., the heart 120). The position coordinates may be based on impedance or electromagnetic fields measured between the BS electrode and the electrode 111 of the catheter 110 or other electromagnetic component. In addition to or instead of the above, a position pad that generates a magnetic field used for navigation may be placed on the surface of the bed 130, or it may be placed separately from the bed 130. Biometric data can be transmitted to the console 160 and stored in memory 162. Alternatively or additionally, biometric data may be transmitted to a server, which may be local or remote, using a network as further described herein.

[0030] According to one or more embodiments, the catheter 110 may be configured to ablate tissue areas in the cardiac chambers of the heart 120. Insertion figure 150 shows a magnified view of the catheter 110 within the cardiac chambers of the heart 120. For example, an ablation electrode, such as at least one electrode 111, may be configured to deliver energy to a tissue area of ​​an organ in the body (e.g., the heart 120). The energy may be thermal energy and may cause damage to the tissue area, starting from the surface of the tissue area and extending to the thickness of the tissue area. Biometric data relating to the ablation procedure (e.g., ablated tissue, ablation location, etc.) may be considered ablation data.

[0031] For example, with respect to acquiring biometric data, a multi-electrode catheter (e.g., catheter 110) can be advanced into the cardiac chambers of the heart 120. To establish the position and orientation of each electrode, anterior-posterior (AP) and lateral fluorescence images can be acquired. The ECG can be recorded from each of the electrodes 111 that are in contact with the cardiac surface relative to time, such as the generation of P waves in the sinus rhythm from the BS ECG and / or signals from electrodes 111 (which may be called a CS catheter (CSC)) of catheter 110 positioned in the coronary sinus (CS). Systems further disclosed herein can distinguish between electrodes that record electrical activity and electrodes that do not record electrical activity because they are not in close proximity to the endocardial wall. After the initial ECG is recorded, the catheter can be repositioned and fluorescence images and ECGs can be recorded again. An electrical map can then be constructed (e.g., via cardiac mapping) from iterations of the above process.

[0032] Cardiac mapping can be performed using one or more techniques. Generally, mapping of cardiac regions of the heart 120, such as cardiac areas, tissues, veins, arteries, and / or electrical pathways, can lead to the identification of problem areas such as scar tissue, arrhythmia sources (e.g., electrical rotors), and healthy areas. Cardiac regions can be mapped so that a visual rendering of the mapped cardiac regions is provided using a display, as further disclosed herein. Furthermore, cardiac mapping (an example of cardiac imaging) may include, but is not limited to, mapping based on one or more modalities such as LAT, local excitation velocity, electrical activity, topology, bipolar mapping, dominant frequency, or impedance. Data corresponding to multiple modalities (e.g., biometric data) can be acquired using a catheter inserted into the patient's body (e.g., catheter 110) and can be provided for rendering simultaneously or at different times, based on the corresponding settings and / or the preference of the physician 115.

[0033] As an example of the first technique, cardiac mapping can be performed by sensing the electrical properties of cardiac tissue, e.g., LAT, as a function of precise location within the heart 120. Corresponding data (e.g., biometric data) can be acquired by one or more catheters (e.g., catheter 110) that are advanced into the heart 120 and have electrical and position sensors (e.g., electrodes 111) at their distal tip. Specifically, location and electrical activity can be initially measured at approximately 10 to 20 points on the inner surface of the heart 120. These data points are generally sufficient to generate a preliminary reconstruction or map of the cardiac surface with satisfactory quality. The preliminary map can be combined with data measured at further points to generate a more comprehensive map of the cardiac electrical activity. In clinical practice, it is not uncommon to collect data from more than 100 locations (e.g., thousands) to generate a detailed comprehensive map of the electrical activity of the cardiac chambers. The detailed maps generated thereafter can serve as a basis for determining therapeutic actions to alter the propagation of the heart's electrical activity and restore a normal rhythm, such as decisions regarding tissue ablation as described herein.

[0034] Furthermore, cardiac mapping can be generated based on the detection of intracardiac potential fields (e.g., IC ECG data and / or bipolar intracardiac reference signals). Non-contact methods can be employed to simultaneously acquire a large amount of cardiac electrical information. For example, a catheter type with a distal end may be equipped with a series of sensor electrodes distributed across its surface and connected to an insulating conductor for connection to signal sensing and processing means. The size and shape of the end can be such that the electrodes are positioned at a large distance from the walls of the cardiac chambers. The intracardiac potential field can be detected during a single heartbeat. In one example, the sensor electrodes may be distributed on a series of circles located in planes spaced apart from each other. These planes may be perpendicular to the long axis of the end of the catheter. At least two additional electrodes may be arranged adjacent to both ends of the long axis of the end. In a more specific example, the catheter may include four circumferences, each having eight electrodes spaced equally apart on each circumference. Thus, in this particular implementation, the catheter may include at least 34 electrodes (32 circumferential electrodes and 2 end electrodes). As another, more specific example, the catheter may include other multi-spline catheters such as a flip-type catheter with five flexible branches, eight radial splines, or parallel splines (for example, each of which may have a total of 42 electrodes).

[0035] As an example of electrical or cardiac mapping, electrophysiological cardiac mapping systems and techniques based on non-contact and non-expandable multi-electrode catheters (e.g., catheter 110) can be implemented. ECG can be obtained using one or more catheters 110 having multiple electrodes (e.g., 42 to 122 electrodes). This implementation allows insights into the relative geometric shape of the probe and endocardium to be obtained by an independent imaging modality such as transesophageal echocardiography. After independent imaging, cardiac surface potentials can be measured using non-contact electrodes, and a map can be constructed from these surface potentials (e.g., using bipolar intracardiac reference signals in some cases). This technique may include the following steps (after the independent imaging step): (a) measuring potentials using multiple electrodes placed on a probe positioned within the heart 120; (b) determining the geometric relationship between the probe surface and the endocardial surface and / or other references; (c) generating a matrix of coefficients representing the geometric relationship between the probe surface and the endocardial surface; and (d) determining the endocardial potential based on the electrode potentials and the matrix of coefficients.

[0036] As another example of electrical or cardiac mapping, techniques and apparatus for mapping the potential distribution of cardiac chambers can be implemented. An intracardiac multi-electrode mapping catheter assembly can be inserted into the heart 120. The mapping catheter (e.g., catheter 110) assembly may include a multi-electrode array or companion reference catheter having one or more integrated reference electrodes (e.g., one or electrode 111).

[0037] According to one or more embodiments, the electrodes can be deployed in the form of a substantially spherical array, which can be spatially referenced to a point on the endocardial surface by a reference electrode or by a reference catheter in contact with the endocardial surface. A preferred electrode array catheter may have a number of individual electrode sites (e.g., at least 24). In addition, this exemplary technique can be carried out by knowing the position of each electrode site on the array and the geometric shape of the heart. These positions are preferably determined by impedance plethysmography.

[0038] From an electrical or cardiac mapping perspective, and according to another example, the catheter 110 may be a cardiac mapping catheter assembly that includes an electrode array defining a number of electrode sites. This cardiac mapping catheter assembly also includes a lumen for receiving a reference catheter having a distal tip electrode assembly that can be used to probe the cardiac wall. The mapping cardiac mapping catheter assembly may include a braid of insulated wires (e.g., having 24 to 64 wires in the braid), each of which can be used to form an electrode site. The cardiac mapping catheter assembly may be readily placed in the heart 120 to be used to acquire electrical activity information from a first set of non-contact electrode sites and / or a second set of contact electrode sites.

[0039] Furthermore, according to another example, a catheter 110 capable of performing electrophysiological activity mapping within the heart may include a distal tip adapted to supply stimulation pulses for pacing the heart, or an ablation electrode for ablating tissue in contact with this tip. The catheter 110 may further include at least a pair of orthogonal electrodes for generating differential signals indicating local cardiac electrical activity in the vicinity of the orthogonal electrodes.

[0040] As described herein, the system 100 can be used to detect, diagnose, and / or treat cardiac conditions. In exemplary operation, the system 100 can perform a process for measuring electrophysiological data within the cardiac chambers. This process may include, in part, placing a set of active and passive electrodes within the heart 120, supplying current to the active electrodes to generate an electric field within the cardiac chambers, and measuring the electric field at the passive electrode sites. The passive electrodes are contained in an array placed on an inflatable balloon of a balloon catheter. In a preferred embodiment, the array is said to have 60 to 64 electrodes.

[0041] As another exemplary operation, cardiac mapping can be performed by system 100 using one or more ultrasound transducers. The ultrasound transducers can be inserted into the patient's heart 120 and can collect multiple ultrasound slices (e.g., two-dimensional or three-dimensional slices) at various positions and orientations within the heart 120. The position and orientation of a given ultrasound transducer may be known, and the collected ultrasound slices can be stored so that they can be viewed later. One or more ultrasound slices corresponding to the position of probe 105 (e.g., a therapeutic catheter shown as catheter 110) can be viewed later, and probe 105 can be superimposed on one or more ultrasound slices.

[0042] Considering System 100, cardiac arrhythmias, including atrial arrhythmias, can be of the multi-wavelet reentrant type, characterized by multiple asynchronous loops of electrical impulses that scatter around the atria and often self-propagate (e.g., another example of IC ECG data). Instead of, or in addition to, the multi-wavelet reentrant type, cardiac arrhythmias can also have focal sources of excitation, such as when isolated areas of atrial tissue are rapidly and repeatedly excited autonomously (e.g., another example of IC ECG data). Ventricular tachycardia (V-tach or VT) is a tachycardia or rapid heart rhythm that occurs in one of the ventricles (e.g., tachycardia can result in a heart rate of more than 100 beats per minute). This is a potentially fatal arrhythmia, as it can lead to ventricular fibrillation and sudden death.

[0043] For example, aFib occurs when the normal electrical impulses generated by the sinoatrial node (e.g., another example of IC ECG data) are overwhelmed by disordered electrical impulses (e.g., signal interference) occurring in the atrial veins and PV, conducting irregular impulses to the ventricles. This results in an irregular heartbeat, which can last from minutes to weeks, or even years. Often, aFib is a chronic condition that slightly increases the risk of death, often due to stroke. The treatment strategy for aFib is medication to reduce heart rate or restore a normal rhythm. Furthermore, patients with aFib are often given anticoagulants to protect against the risk of stroke. The use of such anticoagulants carries its own risk of internal bleeding. In some patients, medication is insufficient, and their aFib is deemed drug-refractory, i.e., untreatable with standard pharmacological interventions. Synchronized electrical cardioversion can also be used to convert aFib back to a normal rhythm. Alternatively, patients with aFib may also be treated with catheter ablation.

[0044] Catheter ablation-based therapies may include mapping the electrical properties of cardiac tissue, particularly the endocardium and cardiac volume, and selectively ablating cardiac tissue by applying energy. Electrical or cardiac mapping (e.g., performed by any electrophysiological cardiac mapping systems and techniques described herein) includes creating potential maps of wave propagation along cardiac tissue (e.g., voltage maps) or maps of arrival times (e.g., LAT maps) to points located within various tissues. Electrical or cardiac mapping (e.g., cardiac maps) can be used to detect localized cardiac tissue dysfunction. Ablation, such as cardiac mapping-based ablation, can stop or alter unwanted electrical signals from propagating from one part of the heart 120 to another.

[0045] Ablation is a method that disrupts unwanted electrical pathways by creating non-conductive damaged areas. Various energy delivery methods have been disclosed to date for the purpose of creating damaged areas, including the use of microwaves, lasers, and more generally radiofrequency energy to create conduction blocks along the cardiac tissue wall. Another example of an energy delivery method is irreversible electroporation (IRE), which applies a high electric field to damage cell membranes. In a two-step procedure (mapping followed by ablation), a catheter 110 containing one or more electrical sensors (e.g., electrodes 111) is typically advanced into the heart 120, and electrical activity at points within the heart 120 is sensed and measured by acquiring data at multiple points (e.g., generally as biometric data, or specifically as ECG data). This ECG data is then used to select target regions of the endocardium to be ablated.

[0046] Cardiac ablation and other cardiac electrophysiological procedures are becoming increasingly complex when physicians treat difficult conditions such as atrial fibrillation and ventricular tachycardia. Treatment of refractory arrhythmias may now rely on the use of three-dimensional (3D) mapping systems to reconstruct the anatomical morphology of the target cardiac chambers. In this regard, the determination engine 101 used by system 100 herein manipulates and evaluates biometric data, or specifically ECG data, to generate improved tissue data that enables more accurate diagnosis, imaging, scanning, and / or mapping for treating abnormal heartbeats or arrhythmias. For example, cardiologists may rely on software such as the Complex Fractionated Atrial Electrograms (CFAE) module of the CARTO® 3 3D mapping system manufactured by Biosense Webster, Inc. (Diamond Bar, Calif.) to generate and analyze ECG data. The judgment engine 101 of system 100 enhances this software to generate and analyze improved biometric data, thereby further providing multiple pieces of information regarding the electrophysiological properties of the heart 120 (including scar tissue) that represent the cardiac matrix (anatomical and functional) of aFib.

[0047] Therefore, system 100 can implement a 3D mapping system, such as the CARTO® 3 3D mapping system, to identify the location of potential arrhythmogenic substrates in cardiomyopathy from the perspective of detecting abnormal ECGs. These substrates associated with cardiac disease are linked to the presence of segmentation and delayed ECGs in the endocardial and / or epicardial layers of the ventricular chambers (right and left). Generally, abnormal tissue is characterized by low-voltage ECGs. However, early clinical experience in endocardial-epidermal mapping has shown that low-voltage regions are not always present as the sole arrhythmic mechanism in such patients. In fact, low-voltage or medium-voltage regions may show segmentation and delayed activity of the ECG during sinus rhythm, which corresponds to the critical isthmus identified in persistent, cohesive ventricular arrhythmias (e.g., only in unacceptable ventricular tachycardia). Furthermore, in many cases, segmentation and delayed activity of the ECG are observed in regions showing normal or near-normal voltage amplitudes (>1-1.5mV). The latter region can be evaluated according to voltage amplitude, but is not considered normal according to intracardiac signals and therefore represents true arrhythmogenic substrates. 3D mapping may make it possible to identify the location of arrhythmogenic substrates on the endocardial and / or epicardial layers of the right / left ventricle, whose distribution may vary depending on the progression of the major disease.

[0048] As another exemplary operation, cardiac mapping can be performed by system 100 using one or more multi-electrode catheters (e.g., catheter 110). The multi-electrode catheter is used to stimulate and map electrical activity within the heart 120 and to ablate areas where abnormal electrical activity is observed. When used, the multi-electrode catheter is inserted into a major vein or artery, e.g., the femoral vein, and then guided into the cardiac chambers of the target heart 120. A typical ablation procedure involves inserting catheter 110, which has at least one electrode 111 at its distal end, into the cardiac chambers. A reference electrode is provided by being taped to the patient's skin, by a second catheter positioned within or near the heart, or by selecting one or other electrodes 111 of catheter 110. A radiofrequency (RF) current is applied to the tip electrode 111 of the ablation catheter 110, and the current flows through the surrounding medium (i.e., blood and tissue) toward the reference electrode. The distribution of the current depends on the amount of electrode surface in contact with tissue, compared to blood, which has higher conductivity than tissue. Tissue heating occurs due to the electrical resistance of the tissue. When the tissue is sufficiently heated, cell destruction occurs in the cardiac tissue, resulting in the formation of non-conductive damaged areas within the cardiac tissue. In this process, heating of the tip electrode 111 also occurs due to conduction from the heated tissue to the electrode itself. When the electrode temperature becomes sufficiently high, and may exceed 60°C, a thin, transparent film of dehydrated blood proteins may form on the surface of the electrode 111. As the temperature continues to rise, this dehydrated layer may gradually thicken, and blood coagulation occurs on the electrode surface. Since dehydrated biological material has a higher electrical resistance than endocardial tissue, the impedance to the flow of electrical energy into the tissue also increases. When the impedance becomes sufficiently high, an impedance surge occurs, and the catheter 110 must be withdrawn from the body and the tip electrode 111 must be cleaned.

[0049] Referring now to Figure 2, a schematic diagram of a system 200 in which one or more features of the subject matter of this disclosure may be implemented in one or more embodiments. The system 200, in relation to a patient 202 (for example, an example of patient 125 in Figure 1), includes an apparatus 204, a local computing device 206, a remote computing system 208, a first network 210, and a second network 211. Furthermore, the apparatus 204 may include a biometric sensor 221 (for example, an example of catheter 110 in Figure 1), a processor 222, a user input (UI) sensor 223, a memory 224, and a transceiver 225. Note that for ease of explanation and brevity, the determination engine 101 from Figure 1 is reused in Figure 2.

[0050] According to one embodiment, the device 204 may be an example of the system 100 in Figure 1, and the device 204 may include both internal and external components of the patient. According to one embodiment, the device 204 may be an external device of the patient 202, including an attachable patch (e.g., attached to the patient's skin). According to another embodiment, the device 204 may be internal to the patient 202's body (e.g., subcutaneously implantable), and the device 204 may be inserted into the patient 202's body by any applicable method, including oral infusion, surgical insertion via vein or artery, endoscopic surgery, or laparoscopic surgery. According to one embodiment, a single device 204 is shown in Figure 2, but the exemplary system may include multiple devices.

[0051] Therefore, the device 204, the local computing device 206, and / or the remote computing system 208 can be programmed to execute computer instructions relating to the determination engine 101. As an example, memory 223 stores these instructions for processor 222 to execute so that the device 204 can receive and process biometric data via the biometric sensor 201. Thus, processor 222 and memory 223 represent the processor and memory of local computing device 206 and / or remote computing system 208.

[0052] The apparatus 204, the local computing device 206, and / or the remote computing system 208 can be any combination of software and / or hardware that individually or collectively store, execute, and implement the decision engine 101 and its functions. Furthermore, the apparatus 204, the local computing device 206, and / or the remote computing system 208 can be an electronic computer framework that includes and / or uses any number and combination of computing devices and networks utilizing various communication technologies, as described herein. The apparatus 204, the local computing device 206, and / or the remote computing system 208 can be easily scalable, expandable, and modular, allowing for modification to suit different services or the reconfiguration of some functions independently of others.

[0053] Networks 210 and 211 may be wired networks, wireless networks, or may include one or more wired and wireless networks. According to one embodiment, network 210 is an example of a short-range network (e.g., a local area network (LAN) or a personal area network (PAN)). Information can be transmitted between device 204 and local computing device 206 via the short-range network 210 using one of various short-range wireless communication protocols such as Bluetooth, Wi-Fi, Zigbee, Z-Wave, near-field communication (NFC), Ultraband, Zigbee, or infrared (IR). Furthermore, network 211 is an example of one or more of the following: an intranet, a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a direct connection or a series of connections, a cellular telephone network, or any other network or medium that can facilitate communication between local computing device 206 and remote computing system 208. Information can be transmitted over network 211 using any one of various long-range wireless communication protocols (e.g., TCP / IP, HTTP, 3G, 4G / LTE, or 5G / New Radio). The wired connection of either network 210 or 211 can be implemented using Ethernet, Universal Serial Bus (USB), RJ-11, or any other wired connection, while the wireless connection can be implemented using Wi-Fi, WiMAX, Bluetooth, infrared, cellular networks, satellite communications, or any other wireless connection method.

[0054] During operation, the device 204 can continuously or periodically acquire, monitor, store, process, and communicate biometric data related to the patient 202 via the network 210. Furthermore, the device 204, the local computing device 206, and / or the remote computing system 208 communicate via the networks 210 and 211 (for example, the local computing device 206 can be configured as a gateway between the device 204 and the remote computing system 208). For example, the device 204 may be an example of system 100 in Figure 1, configured to communicate with the local computing device 206 via the network 210. The local computing device 206 can be, for example, a fixed / standalone device, a base station, a desktop / laptop computer, a smartphone, a smartwatch, a tablet, or another device configured to communicate with other devices via the networks 211 and 210. A remote computing system 208, implemented as a physical server on or connected to network 211, or as a virtual server within a public cloud computing provider for network 211 (e.g., Amazon Web Services (AWS)), can be configured to communicate with a local computing device 206 via network 211. This allows biometric data related to patient 202 to be communicated throughout the entire system 200.

[0055] The elements of the device 204 are described here. The biometric sensor 221 may include one or more transducers configured to convert one or more environmental conditions into electrical signals, for example, so that different types of biometric data can be observed / acquired / obtained. For example, the biometric sensor 221 may include one or more of the following: electrodes (e.g., electrode 111 in Figure 1), temperature sensors (e.g., thermocouples), blood pressure sensors, blood glucose sensors, blood oxygen sensors, pH sensors, accelerometers, and microphones.

[0056] In executing the determination engine 101, the processor 222 may be configured to receive, process, and manage biometric data acquired by the biometric sensor 221, and to communicate the biometric data to the memory 224 for storage and / or to the entire network 210 via the transceiver 225. Biometric data from one or more other devices 204 may also be received by the processor 222 via the transceiver 225. Furthermore, as will be described in more detail below, the processor 222 may be configured to selectively respond to different tapping patterns (e.g., single tap or double tap) received from the UI sensor 223 so that different tasks on a patch (e.g., data acquisition, storage, or transmission) are triggered based on the detected pattern. In some embodiments, the processor 222 may generate audible feedback with respect to gesture detection.

[0057] The UI sensor 223 includes, for example, a piezoelectric or capacitive sensor configured to receive user input such as a tap or touch. For example, the UI sensor 223 may be controlled to perform capacitive coupling in response to a patient 202 tapping or touching the surface of the device 204. Gesture recognition can be implemented via any one of various capacitive types, such as resistive capacitive, surface capacitive, projected capacitive, surface ultrasonic, piezoelectric, and infrared touch. The capacitive sensor may be positioned over a small area or length of the surface so that a tap or touch on the surface activates the monitoring device.

[0058] Memory 224 is any non-temporary tangible medium such as magnetic, optical, or electronic memory (e.g., any suitable volatile and / or non-volatile memory such as random access memory or a hard disk drive). Memory 224 stores computer instructions executed by processor 222.

[0059] The transceiver 225 may include a separate transmitter and a separate receiver. Alternatively, the transceiver 225 may include a transmitter and receiver integrated into a single device.

[0060] During operation, the device 204 utilizing the determination engine 101 observes / acquires the patient 202's biometric data via the biometric sensor 221, stores the biometric data in memory, and shares this biometric data throughout the system 200 via the transceiver 225. The determination engine 101 may then utilize models, neural networks, machine learning, and / or artificial intelligence to provide cardiologists and healthcare professionals with an automated PPI determination based on detecting signals read after the last stimulus signal.

[0061] Referring here to Figure 3, one or more exemplary embodiments of Method 300 (performed, for example, by the determination engine 101 in Figures 1 and / or 2) are shown. Method 300 addresses the need to automatically track the time between the last stimulus and the signal reading by providing multi-step manipulation of electrical signals, which enables a more accurate and improved understanding of electrophysiology.

[0062] This method is initiated in block 320, and the determination engine 101 determines that a stimuli-pacing signal is being captured from at least a portion of an anatomical structure. As described herein, the anatomical structure may be any anatomical structure, body part, organ, or portion thereof (e.g., the heart or ventricle or atrium) that can be targeted for pacing, mapping, and diagnosis. Furthermore, pacing may be achieved by one or more catheters 110 (e.g., multi-electrode mapping catheters and / or CSCs) associated with body patches and / or BS electrodes.

[0063] The stimulating pacing signal includes at least one signal from pacing using the electrodes 111 of the catheter 110 (e.g., an electrical pacing signal). Note that, generally, pacing may be a series of sequential signals (e.g., signals 1, 2, and 3). In this case, system 100 attempts to perform method 300 at the end of the sequence to determine that the stimulating pacing signal has been captured (and that the next natural event of activity has been detected). In addition, note that the intervals of each sequential pacing signal may vary (e.g., signal 1 has a C1 interval, signal 2 has a C1 interval, and interval 3 has a C2 interval).

[0064] Depending on one or more of these, the capture of the stimulus pacing signal may be performed by the dedicated hardware of system 100 (e.g., a pacing mechanism that knows when pacing will occur) and / or by the advanced reference algorithm (ARA) of the judgment engine 101 (e.g., knowing when pacing will occur). Note that if capture occurs, the dedicated hardware of system 100 and / or the ARA of the judgment engine 101 will recognize that control of the anatomical structure has been acquired.

[0065] For example, when pacing the heart, if the atria are properly captured, the system 100 and / or the determination engine 101 will detect ventricular activity in accordance with the pacing (the ventricles may contract in accordance with the pacing). In practice, the system 100 and / or the determination engine 101 will determine that the heart is captured when cardiac tissue is affected, cardiac activity is synchronized with the pacing, a BS signal is detected 100 milliseconds after the first pacing, another BS signal is detected at the same 100 milliseconds after the second pacing, and so on. However, if ventricular activity is not involved in the pacing or synchronization is not present, the system 100 and / or the determination engine 101 will recognize that thermal tissue is not affected and tissue capture is not present (e.g., cardiac control is not obtained).

[0066] According to one or more embodiments, when the CSC is stationary within the CS (e.g., immobile relative to the multi-electrode mapping catheter), the refractory period may be used by the CSC to detect proper atrial capture (for example, because electrical signals are conducted differently by the CSC within the CS than by the multi-electrode mapping catheter at other points in the heart). For example, if tachycardia is repeated around the left atrium, the CSC detects the sequence and direction of the tachycardia waves (since these electrical signals are repeated), along with any corresponding morphology. In contrast, during pacing, the electrical pacing signals have a different sequence, direction, and morphology from the tachycardia waves, so the electrical pacing signals clear the CSC differently. When this difference is detected, the CSC (and correspondingly the determination engine 101) is informed that the left atrium is functioning properly and the heart has been captured by pacing.

[0067] According to one or more embodiments, a method for capture detection may utilize the presence of one or more catheters 110 within the heart 120. For example, if proper capture is effective, the sequence of activations on the CS catheter may change (e.g., incomplete wavefront propagation and pacing site localization in the heart 120). In some cases, the morphology changes between the pre-pacing state and the pacing state, and these changes are measured to evaluate whether the capture was successful. Furthermore, in some scenarios (e.g., pacing in PV isolated from a multi-electrode catheter), "local capture" may be identified after successful capture.

[0068] In block 340, the determination engine 101 determines the duration between the stimulus pacing signal and the subsequent response from a portion of the anatomical structure. The subsequent response includes the reception of radio waves from a specific point affected by the electrical pacing signal (e.g., sinus rhythm from the excitation gap of the circuit). In this regard, the determination engine 101 measures the time between the last electrical pacing signal transmitted to the cardiac tissue and the first activity wave from the cardiac tissue. This measurement of time yields the PPI.

[0069] In block 360, the judgment engine 101 outputs the duration. The judgment engine 101 can output the duration in a map context, such as by a display 165 that provides a visual rendering of the anatomical structure to the physician 115. The judgment engine 101 can output the duration for storage in memory 162.

[0070] Referring here to Figure 4, one or more exemplary embodiments of Method 400 (performed, for example, by the determination engine 101 in Figures 1 and / or 2) are shown. Method 400 generally first determines that a stimulated pacing signal has triggered a region of an organ, and then automatically determines PPI based on the detection of the subsequent automatic electrical activity following such a stimulated pacing signal triggering that region of the organ. One or more factors may be observed to determine whether a stimulated pacing signal has triggered a region of an organ, including identifying the region of the organ (e.g., ventricle or atrium).

[0071] This method begins in block 410, where the decision engine 101 provides a stimulus-pacing signal to a portion of an anatomical structure (e.g., the decision engine 101 is pacing). The stimulus-pacing signal may be provided at a first time (e.g., t0). Along with providing the stimulus-pacing signal, the decision engine 101 may capture and / or detect additional information. This additional information may include, but is not limited to, biometric data and / or training datasets (e.g., one or more of LAT, electrical activity, topology, bipolar mapping, baseline activity, ventricular activity, dominant frequency, impedance, etc.) along with pacing protocol parameters (e.g., pacing interval, sequence, etc.). Next, the decision engine 101 collects a corpus of information for machine learning and / or to be used by the artificial intelligence algorithm of the decision engine 101 at the first time.

[0072] In block 430, the decision engine 101 captures the stimulus pacing signal. The stimulus pacing signal may be captured at a second time (e.g., t2 = t0 + x1). Along with capturing the stimulus pacing signal, the decision engine 101 may capture and / or detect additional information (similar to block 410). Thus, the decision engine 101 adds this information to the corpus.

[0073] In block 440, the decision engine 101 captures subsequent responses from a portion of an anatomical structure. Stimulus pacing signals may be captured at a third time (e.g., t3 = t0 + x3, where x3 > x2) or a second time (e.g., t3 = t2). In conjunction with capturing subsequent responses, the decision engine 101 may capture and / or detect additional information (similar to blocks 410 and 420). Thus, the decision engine 101 adds to the corpus of information.

[0074] In block 450, the decision engine 101 determines that the subsequent response is related to / synchronized with the stimulation pacing signal (e.g., an anatomical structure was captured). For example, the subsequent response is a contraction of cardiac tissue associated with pacing. If contraction is not related, pacing did not capture the heart when providing the stimulated pacing signal. A determination may be made that the stimulation pacing signal could be captured at a fourth time (e.g., t4 = t0 + x4, where x4 > x3) or a third time (e.g., t3 = t4). The decision engine 101 may utilize a corpus of information to perform big data analysis when making this determination. Note that the values ​​of T0, x1, x2, x3, and / or x4 may be default values, user-defined values, or machine-determined values, stored in memory 162 and accessed by the decision engine 101 during the automatic operation of method 400.

[0075] As another example, when a stimulated pacing signal is delivered into the ventricle, the determination engine 101 may detect a QRS complex or pattern (e.g., a subsequent response) on the body surface ECG. A QRS complex can be a combination of graph deviations (e.g., three deviations) within the ECG, usually the central major spike. A QRS complex may correspond to depolarization of the right and left ventricles of the heart and contraction of the ventricular muscle.

[0076] As another example, when a stimulated pacing signal is delivered to the atria, even if capture is present within the atria, due to the natural mechanism of the cardiac AV node and the electrical isolation between the two ventricles, all activity is converted to ventricular activity. Therefore, a surface ECG may not be sufficient to determine that the stimulated pacing signal has triggered a particular area of ​​the organ. Accordingly, as described herein, the presence of activity within the CS and its timing / morphology relative to other beats may be used to determine that the stimulated pacing signal has triggered a particular area of ​​the atria.

[0077] In block 470, the decision engine 101 determines the duration between the stimulus pacing signal and the subsequent response. The determination of the duration may be automated. Note that the duration (and / or any values ​​associated with the duration, such as a value associated with a given position) is stored in memory 162 and can be accessed by the decision engine 101 during subsequent automated operation of method 400.

[0078] In block 490, the determination engine 101 outputs the duration. In one example, outputting the duration may include displaying the duration in the context of electroanatomical mapping, as described herein. Furthermore, outputting the duration may include providing a corpus of durations and information to a remote computing system 208 for big data analysis. For example, big data analysis can predict and determine one or more of the first, second, third, and fourth times for performing the method by using multiple runs of method 400 in conjunction with multiple manual PPI determinations. In addition, big data analysis may include measuring the effectiveness of capture and determination of method 400 over its multiple iterations. In this way, the determination engine 101 can self-assess the automatic nature of capture and determination in order to further increase the accuracy of PPO observations.

[0079] Referring to Figure 5, one or more embodiments of the interface 500 are shown. The graph 500 may be generated by the decision engine 101. The graph 500 shows the duration (e.g., basic PPI measurement (in the formula, ** This may include scanning or mapping of anatomical structures 510 with an interface 520 that shows a color gradient for grading the duration and / or distance to the TCL related to other PPIs (where represents a number), as well as other PPIs.

[0080] Duration may include fault values. Fault values ​​include values ​​for TCL, pre-identified PPIs, or specific target PPIs. In some cases, when the determination engine 101 performs PPI detection to find a circuit, the determination engine 101 may tolerate deviations from the TCL, and fault values ​​may be associated with these deviations. Duration may be a value of the PPI corresponding to a given location. Alternatively, PPIs corresponding to various given locations may be provided as part of a PPI map that provides PPIs corresponding to different locations on an organ. For example, PPIs for multiple locations on a portion of the heart may be displayed such that the PPI values ​​are superimposed on a rendering of the portion of the heart. PPI values ​​can lead to the determination of potential ablation sites, for example, when used in conjunction with electroanatomical mapping and / or big data analysis.

[0081] The flowcharts and block diagrams in the figures illustrate the structure, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for performing the indicated logical function. In some alternative implementations, the functions shown in a block may be performed in an order other than that shown in the figure. For example, two consecutively shown blocks may actually be executed substantially simultaneously, or they may sometimes be executed in reverse order depending on the relevant functionality. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, may be performed by a dedicated hardware-based system that performs a specific function or operation, or they may operate or execute a combination of dedicated hardware and computer instructions.

[0082] While features and elements are described above in specific combinations, those skilled in the art will understand that each feature or element can be used individually or in combination with other features and elements. In addition, the methods described herein may be implemented in computer programs, software, or firmware incorporated into a computer-readable medium for execution on a computer or processor. The computer-readable medium as used herein should not be interpreted as being a transient signal in itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses passing through fiber optic cables), or electrical signals transmitted through moving wires.

[0083] Examples of computer-readable media include electrical signals (transmitted via wired or wireless connections) and computer-readable storage media. Examples of computer-readable storage media, though not limited to these, include registers, cache memory, semiconductor memory devices, magnetic media such as internal hard disks and removable disks, magneto-optical media, optical media such as compact disks (CDs) and digital versatile disks (DVDs), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), and memory sticks. A processor can be used with software to implement a radio frequency transceiver for use in terminals, base stations, or any host computer.

[0084] The terms used herein are intended solely to describe specific embodiments and are not intended to be limiting. Where used herein, unless otherwise specified in the context, the singular forms "a," "an," and "the" also include the plural forms. The terms "comprise" and / or "comprising," as used herein, indicate the presence of a described feature, integer, process, operation, element, and / or component, but do not exclude the presence or addition of one or more other features, integers, processes, operations, elements, components, and / or groups thereof.

[0085] The descriptions of different embodiments in this specification are for illustrative purposes only and are not intended to be exhaustive or limitful to the embodiments disclosed. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the embodiments described. The terms used herein have been selected to best describe the principles, practical applications, or technical improvements of the embodiments compared to the art available on the market, or to enable those skilled in the art to understand the embodiments disclosed herein.

[0086] [Implementation Method] (1) A method, A determination engine, stored as processor-executable code in memory connected to one or more processors executing the processor-executable code, determines that a stimulus pacing signal has been captured from at least a portion of an anatomical structure. The determination engine determines the duration between the stimulus pacing signal and the subsequent response from the part of the anatomical structure, A method comprising outputting the duration using the determination engine. (2) The method according to Embodiment 1, wherein the determination engine provides the stimulus pacing signal to the portion of the anatomical structure. (3) The method according to Embodiment 2, wherein the stimulation pacing signal is provided by a coronary sinus catheter positioned within the anatomical structure. (4) The method according to Embodiment 1, wherein the duration includes a fault value. (5) The method according to Embodiment 1, wherein the determination engine outputs the duration in the map context.

[0087] (6) The method according to Embodiment 1, wherein the pacing achieved by one or more catheters includes the stimulation pacing signal. (7) The method according to Embodiment 1, wherein the pacing includes the column of sequential signals at the ends of the column, wherein the stimulus pacing signal includes the column of sequential signals at the ends of the column. (8) The method according to Embodiment 7, wherein the subsequent response from the portion of the anatomical structure includes the next natural event of activity. (9) The method according to embodiment 1, wherein the anatomical structure includes a heart. (10) The method according to Embodiment 1, wherein the determination engine utilizes the duration and a corpus of information in big data analysis to determine the accuracy of the duration.

[0088] (11) A system, Memory for storing processor-executable code for the judgment engine, One or more processors, which execute processor executable code to the system, The aforementioned determination engine determines that the stimulus pacing signal is being captured from at least a portion of the anatomical structure, The determination engine determines the duration between the stimulus pacing signal and the subsequent response from the part of the anatomical structure, A system including a processor configured to cause the determination engine to output the duration. (12) The system according to embodiment 11, wherein the determination engine provides the stimulus pacing signal to the portion of the anatomical structure. (13) The system according to embodiment 12, wherein the stimulation pacing signal is provided by a coronary sinus catheter positioned within the anatomical structure. (14) The system according to Embodiment 11, wherein the duration includes a fault value. (15) The system according to embodiment 11, wherein the determination engine outputs the duration in a map context.

[0089] (16) The system according to embodiment 11, wherein pacing achieved by one or more catheters includes the stimulation pacing signal. (17) The system according to embodiment 11, wherein the pacing includes the column of sequential signals at the ends of the column, wherein the stimulus pacing signal is at the end of the column. (18) The system according to Embodiment 17, wherein the subsequent response from the portion of the anatomical structure includes the next natural event of activity. (19) The system according to embodiment 11, wherein the anatomical structure includes a heart. (20) The system according to embodiment 11, wherein the determination engine utilizes the duration and a corpus of information in big data analysis to determine the accuracy of the duration.

Claims

1. It is a system, A memory that stores a determination engine, which is processor-executable code for the automatic measurement and display of PPI values, One or more processors, which execute processor executable code and, in the system, The aforementioned determination engine adds the signals read from the portion of the heart before cardiac pacing and the signals read from the portion of the heart after cardiac pacing, when the stimulation pacing signal captures a portion of the heart, to the corpus of information in big data analysis. The determination engine adds the last stimulus pacing signal and the information of the signal read from the portion of the heart after the last stimulus pacing signal to the corpus. If the determination engine determines, using big data analysis with respect to the corpus, that the last stimulus pacing signal and the signal read from the portion of the heart after the last stimulus pacing signal are related to or synchronized with the last stimulus pacing signal, then the duration, which is the time between the last stimulus pacing signal and the signal read from the portion of the heart after the last stimulus pacing signal, is output as the PPI value. A system including a processor configured to perform the following.

2. The system according to claim 1, wherein the determination engine provides the stimulation pacing signal to the portion of the heart.

3. The system according to claim 2, wherein the stimulus pacing signal is provided by a coronary sinus catheter placed in the heart.

4. The system according to claim 1, wherein the determination engine outputs the duration for display of the duration in electroanatomical mapping.

5. The system according to claim 1, wherein pacing achieved by one or more catheters includes the stimulation pacing signal.

6. A program, which, when loaded by a processor in the system, the processor executes a determination engine, which is processor-executable code for the automatic measurement and display of PPI values, and the system When a stimulation pacing signal captures a portion of the heart, the signal read from that portion of the heart before pacing and the signal read from that portion of the heart after pacing are added to the corpus of information in big data analysis. The information of the last stimulus pacing signal and the signal read from the portion of the heart after the last stimulus pacing signal is added to the corpus. A program that, using big data analysis with the aforementioned corpus, determines that the last stimulus pacing signal and the signal read from the portion of the heart after the last stimulus pacing signal are related to or synchronized with the last stimulus pacing signal, and outputs the duration, which is the time between the last stimulus pacing signal and the signal read from the portion of the heart after the last stimulus pacing signal, as the PPI value.

7. The program according to claim 6, wherein the determination engine provides the stimulation pacing signal to the portion of the heart.

8. The program according to claim 7, wherein the stimulus pacing signal is provided by a coronary sinus catheter implanted in the heart.

9. The program according to claim 6, wherein the determination engine outputs the duration for display of the duration in electroanatomical mapping.

10. The program according to claim 6, wherein pacing achieved by one or more catheters includes the stimulation pacing signal.

11. The system according to claim 1, wherein the determination engine renders a visualization image of the heart and displays the PPI value on a display as a map superimposed on the visualization image.

12. The program according to claim 6, wherein the program includes the determination engine rendering a visualization image of the heart, and the determination engine displaying the PPI value on a display as a map superimposed on the visualization image.

Images