Indicators / scores from predictive modeling, lesion zonation, and PFA application

Abstract

Systems and methods are disclosed that provide information about the ablation lesion zone (width or depth), which can be projected onto an electroanatomical map based on the magnitude of the contact force, the number of times energy is delivered to the tissue, and preclinical data.

Description

[Technical Field]

[0001] The present invention is directed to predictive modeling and lesion index / scores from PFA applications. [Background technology]

[0002] Pulsed field ablation (PFA) is a newly applied technique in the field of cardiac electrophysiology. Lesions created using PFA techniques remain relatively poorly understood compared to RFA lesions. Currently, physicians have no way to determine how deep a lesion will be from a PFA lesion, except for nominal values ​​based on preclinical work. The ability to help predict and understand lesion depth through the use of PFA would provide physicians with a more definitive endpoint and better guidance regarding lesion creation and strategy. Summary of the Invention [Means for solving the problem]

[0003] Multi-parameter and / or single-parameter regression of pulsed field ablation (PFA) application parameter(s) with PFA lesion depth and width is used to determine the zone of irreversible electroporation and reversible ablation lesion zone (width or depth) projected onto a 3D electroanatomical map. This regression correlates the PFA application parameter(s) with lesion depth, width, and spatial location based on distance from the PFA catheter, providing physicians with information about the PFA lesion. Other parameters can include tissue wall thickness, nearby tissue type (e.g., myocardium, smooth muscle), and myocardial fiber orientation.

[0004] After application of PFA, the PFA "realistic" lesion can be projected onto an electroanatomical map to provide a visual representation of the PFA lesion, including lesion width, lesion depth, and cardiac tissue in the zones of irreversible and reversible electroporation. The PFA "realistic" lesion can be color-coded.

[0005] Lesions projected onto the cardiac anatomy (3D electroanatomical map) from the application of PFA can be color-coded according to the zone in which they are located (irreversible (red) and reversible (yellow)) and sized based on the parameters of the application of PFA. The size and spatial projection of the resulting lesions can be determined by multiparametric regressions created and validated from preclinical work relating PFA parameters to lesion size and width. [Brief explanation of the drawings]

[0006] A more detailed understanding may be had from the following description, given by way of example in conjunction with the accompanying drawings, in which like reference numerals indicate similar elements and in which: [Figure 1] FIG. 1 is a diagram of an example system capable of implementing one or more features of the subject matter of this disclosure, according to one or more embodiments. [Figure 2] FIG. 1 is a block diagram of an exemplary system for inspection and optimization of catheter structure using medical procedure information, according to one or more embodiments. [Figure 3] 1 illustrates a lasso-style ablation catheter that may be used in an exemplary system capable of implementing one or more features of the presently disclosed subject matter, according to one or more embodiments. [Figure 4] 1 illustrates a basket-type ablation catheter that may be used in an exemplary system that may implement one or more features of the presently disclosed subject matter, according to one or more embodiments. [Figure 5] 5 illustrates a large electrode that can be implemented with the basket-style ablation catheter of FIG. 4. [Figure 6] 4 illustrates a barrel electrode that may be implemented with the lasso ablation catheter of FIG. 3. [Figure 7] 1 shows exponential plateau curves for other catheter designs. [Figure 8]1 illustrates a visualization of a lesion created with an exemplary system capable of implementing one or more features of the presently disclosed subject matter, in accordance with one or more embodiments. [Figure 9] A sample tissue containing a lesion at the measured depth is shown. [Figure 10] 1 shows a plot of lesion depth as a function of electric field. [Figure 11] 1 shows a graphical representation of the electric field associated with lesion depth measurements. [Figure 12] Parametric curves based on the variables varied are shown. [Figure 13] 1 illustrates a method according to one aspect of the present invention. [Figure 14] The CF range per PFA dose is shown. [Figure 15] The effects of CF and PFA on lesion depth and lesion width are shown. [Figure 16] The effect of CF>5g and PFA dose on lesion size is shown. [Figure 17] The relationship between CF and PFAI is shown. PFAI and CF are linearly related to each PFAI value obtained. [Figure 18] The correlation between lesion depth and PFAI is shown. [Figure 19] The correlation between PFAI and ventricular lesion depth is shown. [Figure 20] This is a depth regression chart. [Figure 21] 10 is a chart of depth interpolation regression. [Figure 22] This is a chart of width regression. [Figure 23] 10 is a chart of width interpolation regression. [Figure 24A] 1 shows an anatomical map of a portion of the heart before ablation. [Figure 24B] 1 shows an anatomical map with information about the projection of the lesion and the zone of the lesion created by the ablation. [Figure 25] 1 illustrates a method according to one aspect of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0007] The following detailed description should be read with reference to the drawings, in which like elements in different drawings are numbered the same. The drawings, which are not necessarily to scale, depict selected embodiments and are not intended to limit the scope of the invention. The detailed description illustrates, by way of example, but not by way of limitation, the principles of the invention. This description will clearly enable any person skilled in the art to make and use the invention and sets forth several embodiments, adaptations, variations, alternatives, and uses of the invention, including what is presently contemplated to be the best mode for carrying out the invention.

[0008] As used herein, the term "about" or "approximately" in relation to any numerical value or range of values ​​indicates a suitable dimensional tolerance that enables a portion of a component or collection of components to function for its intended purpose as described herein. More specifically, "about" or "approximately" can refer to a range of values, such as, by way of example, ±10% of the recited value. Additionally, as used herein, the terms "patient," "host," "user," and "subject" refer to any human or animal subject, and while use of the invention in human patients represents a preferred embodiment, the system or method is not intended to limit use to humans.

[0009] Multi-parameter and / or single-parameter regression of pulsed field ablation (PFA) application parameter(s) with PFA lesion depth and width may be used to determine the zone of irreversible electroporation and reversible ablation lesion zone (width or depth) projected onto a 3D electroanatomical map. This regression correlates the PFA application parameter(s) with lesion depth, width, and spatial location based on distance from the PFA catheter, providing physicians with information about the PFA lesion. Other parameters include tissue wall thickness, nearby tissue type (e.g., myocardium, smooth muscle), and myocardial fiber orientation.

[0010] After application of PFA, the PFA "realistic" lesion can be projected onto an electroanatomical map to provide a visual representation of the PFA lesion, including lesion width, lesion depth, and cardiac tissue in the zones of irreversible and reversible electroporation. The PFA "realistic" lesion can be color-coded.

[0011] Lesions projected onto the cardiac anatomy (3D electroanatomical map) from the application of PFA can be color-coded according to the zone in which they are located (irreversible (red) and reversible (yellow)) and sized based on the parameters of the application of PFA. The size and spatial projection of the resulting lesions can be determined by multiparametric regressions created and validated from preclinical work relating PFA parameters to lesion size and width.

[0012] FIG. 1 is a diagram of a system 100 (e.g., a medical device instrument and / or an EP cardiac mapping system) capable of implementing one or more features of the subject matter herein, according to one or more embodiments. All or a portion 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. As shown, system 100 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 is operated by a physician 115 (or medical professional or clinician) performing a procedure on a heart 120 of a patient 125, as shown. Patient 125 may be positioned on a bed 130 (or table). Insets 140 and 150 show heart 120 and catheter 110 in greater detail. System 100 also includes a console 160 (including one or more processors 161 and memory 162) and a display 165, as shown. Each element and / or item of system 100 represents one or more of that element and / or item. The example system 100 shown in FIG. 1 can be modified to implement the embodiments disclosed herein. The embodiments of the present disclosure can be similarly applied using other system components and configurations. Additionally, system 100 can include additional components, such as elements for sensing electrical activity, wired or wireless connectors, processing devices, and display devices.

[0013] System 100 can be used to detect, diagnose, and / or treat cardiac conditions (e.g., using decision engine 101). Cardiac conditions, such as cardiac arrhythmias, persist as common and dangerous medical ailments, particularly in the aging population. For example, system 100 can be part of a surgical system (e.g., the CARTO® system offered by Biosense Webster) configured to acquire biometric data (e.g., electroanatomical and electrical measurements of a patient's organs, such as heart 120) and perform cardiac ablation procedures. More specifically, treating cardiac conditions, such as cardiac arrhythmias, often requires obtaining detailed mapping of cardiac tissue, chambers, veins, arteries, and / or electrical pathways. For example, successful catheter ablation (as described herein) precisely localizes the source of the cardiac arrhythmia within a chamber of heart 120. Such localization may occur via an EP study, during which spatially resolved electrical potentials are detected by a mapping catheter (e.g., catheter 110) introduced into a chamber of heart 120. This EP study, also known as electroanatomical mapping, provides 3D mapping data that can be displayed on a monitor. Often, mapping and therapy functions (e.g., ablation) are provided by a single catheter or group of catheters, so that the mapping catheter also simultaneously operates as a therapy (e.g., ablation) catheter. In this case, the results or decisions of decision engine 101 can be stored and executed directly by catheter 110.

[0014] In a patient (e.g., patient 125) having normal sinus rhythm (NSR), the heart (e.g., heart 120), including the atria, ventricles, and excitable conductive tissue, is electrically excited to beat in a synchronized, patterned manner. The electrical excitation can be detected, such as in intracardiac electrocardiogram (IC ECG) data.

[0015] In patients (e.g., patient 125) with cardiac arrhythmias (e.g., atrial fibrillation or aFib), abnormal regions of cardiac tissue do not follow the synchronous beating cycle associated with normally conductive tissue, in contrast to patients with NSR. In contrast, abnormal regions of cardiac tissue conduct abnormally to adjacent tissue, disrupting the cardiac cycle and resulting in asynchronous cardiac rhythms. Asynchronous cardiac rhythms can also be detected as IC ECG data. Such abnormal conduction has previously been known to occur in various regions of the heart 120, such as, for example, in the region of the sinoatrial (SA) node along the conductive pathway of the atrioventricular (AV) node, or in the myocardial tissue forming the walls of the ventricles and atria.

[0016] To assist system 100 in detecting, diagnosing, and / or treating a cardiac condition, physician 115 can guide probe 105 into heart 120 of patient 125 reclining on bed 130. For example, physician 115 can insert shaft 112 through sheath 113 while manipulating the distal end of shaft 112 using manipulator 114 near the proximal end of catheter 110 and / or deflection from sheath 113. As shown in inset 140, catheter 110 can be attached to the distal end of shaft 112. Catheter 110 can be inserted through sheath 113 in a collapsed state and then expanded within heart 120.

[0017] In general, electrical activity at a point within the heart 120 may be measured by advancing a catheter 110, typically containing an electrical sensor (e.g., at least one electrode 111) at or near its distal tip, to the point within the heart 120, contacting tissue with the sensor, and acquiring data at the point. One difficulty with mapping a heart chamber using a catheter type containing only a single distal tip electrode is the long time required to collect data for each point across the necessary number of points required for a detailed map of the entire heart chamber. Therefore, multi-electrode catheters (e.g., catheter 110) have been developed to simultaneously measure electrical activity at multiple points within a heart chamber.

[0018] The catheter 110, which may include at least one electrode 111 and a catheter needle coupled on its body, may be configured to obtain biometric data, such as electrical signals, of a body organ (e.g., the heart 120) and / or ablate a tissue region thereof (e.g., a chamber of the heart 120). 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 may be used to infer motion characteristics, such as tissue contractility.

[0019] The biometric data (e.g., patient biometrics, patient data, or patient biometric data) can include one or more of local time activation (LAT), electrical activity, topology, bipolar mapping, baseline activity, ventricular activity, dominant frequency, impedance, etc. LAT can be a time point of threshold activity corresponding to local activation calculated based on a normalized initial starting point. Electrical activity can be any applicable electrical signal that can be measured based on one or more thresholds and can be sensed and / or enhanced based on signal-to-noise ratio and / or other filters. Topology can correspond to the physical structure of a body part or portion of a body part and can correspond to changes in the physical structure for different parts of the body part or for different body parts. The dominant frequency can be a frequency or range of frequencies commonly found in a portion of a body part and can be different in different parts of the same body part. For example, the dominant frequency of the PVs of a heart can be different from the dominant frequency of the right atrium of the same heart. Impedance can be a resistance measurement in a given region of a body part.

[0020] Examples of biometric data include, but are not limited to, patient identification data, IC ECG data, bipolar intracardiac reference signals, electroanatomical and electrical measurements, trajectory information, Body Surface (BS) ECG data, historical data, brain biometrics, blood pressure data, ultrasound signals, radio signals, audio signals, two-dimensional or three-dimensional image data, blood glucose data, and temperature data. Biometric data can generally be used to monitor, diagnose, and treat any number of various diseases, such as cardiovascular diseases (e.g., arrhythmias, cardiomyopathies, 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 inside the patient's body, and ablation data can include data and signals collected from the tissue being ablated. Additionally, BS ECG data, IC ECG data, and ablation data, along with catheter electrode position data, can be derived from one or more procedure records.

[0021] For example, catheter 110 may use electrodes 111 to implement intravascular ultrasound and / or MRI catheterization to image (e.g., acquire and process biometric data) heart 120. Inset 150 shows a close-up of catheter 110 within a chamber of heart 120. While catheter 110 is shown as a point catheter, it will be understood that any shape that includes one or more electrodes 111 can be used to practice the embodiments disclosed herein.

[0022] Examples of catheter 106 include, but are not limited to, a linear catheter with multiple electrodes, a balloon catheter including electrodes distributed on multiple spines forming a balloon, a lasso or loop catheter with multiple electrodes, or any other applicable shape (e.g., basket catheter, multi-arm catheter, etc.). The linear catheter can be fully or partially elastic so that it can twist, bend, and / or otherwise change its shape based on received signals and / or the action of external forces (e.g., cardiac tissue) on the linear catheter. The balloon catheter can be designed to hold its electrodes in intimate contact with the endocardial surface when deployed within a 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 deflated state, so that the balloon catheter does not occupy its maximum volume while inserted into the PV. The balloon catheter can be expanded while inside the PV so 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, allows for efficient imaging and / or ablation.

[0023] According to other embodiments, body patches and / or body surface electrodes may also be positioned on or adjacent to the body of the patient 125. A catheter 110 having one or more electrodes 111 may be positioned within the body (e.g., within the heart 120), and the position of the catheter 110 may be determined by the system 100 based on signals transmitted and received between the one or more electrodes 111 of the catheter 110 and the body patches and / or body surface electrodes. Additionally, the electrodes 111 may sense biometric data (e.g., LAT values) from within the body of the patient 125 (e.g., within the heart 120). The biometric data may be correlated with the determined position of the catheter 110, such that a rendering of the patient's body part (e.g., the heart 120) may be displayed, showing the biometric data superimposed on the shape of the body part.

[0024] The probe 105 and other items of the system 100 can be connected to a console 160. The console 160 can include any computing device that employs machine learning and / or artificial intelligence algorithms (represented as a decision engine 101). According to one embodiment, the console 160 includes one or more processors 161 (any computing hardware) and memory 162 (any non-transitory tangible medium), where the one or more processors 161 execute computer instructions for the decision engine 101 and the memory 162 stores these instructions for execution by the one or more processors 161. For example, the console 160 can be configured to receive and process biometric data to determine whether a given tissue region conducts electricity. In some embodiments, the console 160 can be further programmed by the decision engine 101 to perform the functions of obtaining medical procedure information, examining the medical procedure information using machine learning tools to discover catheter configuration criteria, and using the machine learning tools to optimize a catheter configuration for the procedure based on the data and catheter configuration criteria. According to one or more embodiments, the decision engine 101 may be external to the console 160, for example, located in the catheter 110, in an external device, in a mobile device, in a cloud-based device, or may be a stand-alone processor. In this regard, the decision engine 101 may be transferable / downloadable in electronic form over a network.

[0025] According to one or more embodiments, the decision engine 1010 can incorporate information from different procedures / sites, apply artificial intelligence to build an artificial intelligence model, and use the artificial intelligence model to build a recommendation map based on parameters of the different procedures / sites (e.g., electroanatomy, the specific procedure, and at least some of the physician's experience) to recommend a desired catheter to be used in a particular case, or a catheter with specific parameters and dimensions. According to one or more embodiments, the decision engine 101 can incorporate information from different procedures / sites, apply artificial intelligence to build an artificial intelligence model, and use the artificial intelligence model to analyze parameters of the different procedures / sites that contribute to a better procedure for a particular catheter (e.g., to guide the physician 115 on how to improve the use of the catheter 110). Additionally, the artificial intelligence model can be an iterative process that (effectively) changes the catheter configuration to determine an optimal catheter configuration.

[0026] In one embodiment, the console 160 can be any computing device including software (e.g., the decision engine 101) and / or hardware (e.g., the processor 161 and memory 162), such as a general-purpose computer, with suitable front-end and interface circuitry for transmitting and receiving signals to and from the probe 105, as well as for controlling other components of the system 100, as described herein. For example, the front-end and interface circuitry can include an input / output (I / O) communication interface that allows the console 160 to receive signals from and / or transfer signals to at least one electrode 111. The console 160 can include real-time noise reduction circuitry, typically configured as a field programmable gate array (FPGA) followed by an analog-to-digital (A / D) ECG or electrocardiogram / electromyogram (EMG) signal conversion integrated circuit. The console 160 may communicate signals from the A / D ECG or EMG circuitry to a separate processor and / or may 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 may facilitate the presentation of a rendering of the body part to the physician 115 on the display 165 and store data representing the rendering of the body part in the memory 162. For example, a map indicative of motion characteristics may 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 touch screen that, in addition to presenting the rendering of the body part, may be configured to receive input from the medical professional 115.

[0028] In some embodiments, the physician 115 can use one or more input devices, such as a touchpad, mouse, keyboard, gesture recognizer, etc., to manipulate the renderings of elements of the system 100 and / or body parts. For example, the input device can be used to change the position of the catheter 110 so that the renderings are updated. The display 165 can be located at the same location or at a remote location, such as a separate hospital or within a separate 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 equipment. For example, the system 100 can obtain ECG data and / or electroanatomical 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, for example, by cables, to BS electrodes including adhesive skin patches affixed to the patient 125. The BS electrodes can acquire / generate biometric data in the form of BS ECG data. For example, the processor 161 can determine position coordinates of the catheter 110 within a body part (e.g., the heart 120) of the patient 125. The position coordinates may be based on impedance or electromagnetic fields measured between body surface electrodes and electrodes 111 of the catheter 110 or other electromagnetic components. Additionally or alternatively, the location pad may be placed on the surface of the bed 130 or may be separate from the bed 130. The biometric data may be transmitted to the console 160 and stored in memory 162. Additionally or alternatively, the 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, catheter 110 can be configured to ablate a tissue region of a chamber of heart 120. Inset 150 shows an enlarged view of catheter 110 within a chamber of heart 120. For example, an ablation electrode, such as at least one electrode 111, can be configured to apply energy to a tissue region of a body organ (e.g., heart 120). This energy can be thermal energy and can cause a lesion in the tissue region starting from the surface of the tissue region and extending through the thickness of the tissue region. Biometric data related to the ablation procedure (e.g., ablated tissue, ablation location, etc.) can be considered ablation data.

[0031] According to one embodiment, for obtaining biometric data, a multi-electrode catheter (e.g., catheter 110) can be advanced into a chamber of heart 120. Anteroposterior (AP) and lateral fluoroscopic photographs can be acquired to establish the position and orientation of each of the electrodes. An ECG can be recorded from each of the electrodes 111 in contact with the cardiac surface relative to a temporal reference, such as the occurrence of a P wave in sinus rhythm from a BS ECG. Systems further disclosed herein can distinguish between electrodes that record electrical activity and those that do not due to their lack of proximity to the endocardial wall. After the initial ECG is recorded, the catheter can be repositioned, and fluoroscopic photographs and an ECG can be recorded again. An electrical map can then be constructed from an iteration of the above process (e.g., via cardiac mapping).

[0032] Cardiac mapping can be performed using one or more techniques. Generally, mapping of cardiac regions, such as the cardiac regions, tissues, veins, arteries, and / or electrical pathways of the heart 120, may lead to the identification of problem areas, such as scar tissue, arrhythmia sources (e.g., electrical rotors), healthy regions, etc. The cardiac regions can be mapped such that a visual rendering of the mapped cardiac regions is provided using the display 165, as further disclosed herein. Additionally, cardiac mapping (an example of cardiac imaging) may include mapping based on one or more modalities, such as, but not limited to, local activation time (LAT), electrical activity, topology, bipolar mapping, dominant frequency, or impedance. Data (e.g., biometric data) corresponding to multiple modalities may be acquired using a catheter (e.g., catheter 110) inserted into the patient's body and provided for rendering simultaneously or at different times based on corresponding settings and / or physician 115 preferences.

[0033] As an example of the first technique, cardiac mapping may be performed by sensing electrical properties of cardiac tissue, e.g., LAT, as a function of precise location within the heart 120. Corresponding data (e.g., biometric data) may be acquired by one or more catheters (e.g., catheter 110) advanced into the heart 120 and having electrical and position sensors (e.g., electrodes 111) at their distal tips. As a specific example, position and electrical activity may be initially measured at about 10 to about 20 points on the inner surface of the heart 120. These data points may generally be sufficient to generate a preliminary reconstruction or map of the cardiac surface with satisfactory quality. The preliminary map may be combined with data measured at additional points to generate a more comprehensive map of the cardiac electrical activity. In clinical situations, it is not uncommon to collect data at 100 or more sites to generate a detailed and comprehensive map of the electrical activity of the heart chambers. The detailed maps generated can serve as the basis for determining therapeutic action courses, such as tissue ablation as described herein, to alter the propagation of electrical activity in the heart and restore normal cardiac rhythm.

[0034] Furthermore, cardiac mapping can be generated based on detection of intracardiac potential fields (e.g., IC ECG data and / or bipolar intracardiac reference signals). Non-contact techniques can be implemented to simultaneously acquire large amounts of cardiac electrical information. For example, a catheter type having a distal end portion may include a series of sensor electrodes distributed over its surface and connected to insulated conductors for connection to signal sensing and processing means. The size and shape of the end portion may be such that the electrodes are significantly spaced from the walls of the cardiac chamber. The intracardiac potential fields may be detected during a single cardiac beat. According to one embodiment, the sensor electrodes may be distributed on a series of circumferentially spaced apart planes. These planes may be perpendicular to the longitudinal axis of the catheter end portion. At least two additional electrodes may be provided adjacent each end of the longitudinal axis of the end portion. As a more specific example, the catheter may include four circumferences with eight electrodes equiangularly spaced along each circumference. Thus, in this particular implementation, the catheter may include at least 34 electrodes (32 circumferential electrodes and two end electrodes).

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

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

[0037] According to one or more embodiments, the electrodes may be deployed in a substantially spherical array, which may be spatially referenced to points on the endocardial surface by a reference electrode or by a reference catheter brought into contact with the endocardial surface. The electrode array catheter may carry several individual electrode sites (e.g., at least 24). Additionally, this exemplary technique may be implemented with knowledge of the location of each of the electrode sites on the array and knowledge of the cardiac geometry. These locations are determined by the technique of impedance plethysmography.

[0038] From an electrical or cardiac mapping perspective, and according to another embodiment, the catheter 110 can be a cardiac mapping catheter assembly that may include an electrode array defining several electrode sites. The cardiac mapping catheter assembly can also include a lumen for receiving a reference catheter having a distal tip electrode assembly that can be used to probe the heart wall. The cardiac mapping catheter assembly can include a braid of insulated wires (e.g., having 24-64 wires within the braid), each of which may be used to form an electrode site. The cardiac mapping catheter assembly can be easily positionable within 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] According to another example, a catheter 110 capable of mapping EP activity within the heart can include a distal tip adapted to deliver stimulation pulses for pacing the heart or an ablation electrode for ablating tissue in contact with the tip, and can further include at least one pair of orthogonal electrodes for generating a differential signal indicative of local cardiac electrical activity adjacent the orthogonal electrodes.

[0040] As described herein, system 100 can be utilized to detect, diagnose, and / or treat cardiac conditions. In an exemplary operation, system 100 may perform a process for measuring EP data within a heart chamber. This process may include, in part, positioning a set of active and passive electrodes within heart 120, applying current to the active electrodes to thereby generate an electric field within the heart chamber, and measuring the electric field at the passive electrode sites. The passive electrodes are included in an array positioned on an inflatable balloon of a balloon catheter. In an embodiment, the array is said to have 60-64 electrodes.

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

[0042] In consideration of system 100, it should be noted that cardiac arrhythmias, including atrial arrhythmias, may be multiwavelet reentrant, characterized by multiple asynchronous loops of electrical impulses that scatter and often self-propagate around the atria (e.g., another example of IC ECG data). In addition to or instead of multiwavelet reentrant, cardiac arrhythmias may also have focal sources of excitation, such as when isolated regions of atrial tissue undergo spontaneous excitation in a rapid and repetitive manner (e.g., another example of IC ECG data). Ventricular tachycardia (V-tach or VT) is a tachycardia or fast heart rhythm that originates in one of the ventricles. It may be a fatal arrhythmia because it can lead to ventricular fibrillation and sudden death.

[0043] For example, aFib occurs when normal electrical impulses generated by the sinoatrial node (e.g., another example of IC ECG data) are overwhelmed by chaotic electrical impulses (e.g., signal interference) originating in the atrial veins and PVs, causing irregular impulses to be conducted to the ventricles. This results in an irregular heartbeat that may persist for minutes to weeks, or even years. In many cases, aFib is a chronic condition that slightly increases the risk of death from a heart attack. The first choice of treatment for aFib is drug therapy to slow the heart rate or restore normal heart rhythm. Additionally, patients with aFib are often given anticoagulants to protect against the risk of heart attack. The use of such anticoagulants carries its own risks of internal bleeding. In some patients, drug therapy is insufficient, and aFib is deemed drug-refractory, i.e., untreatable with standard pharmacological interventions. Synchronized cardioversion can be used to convert aFib to a normal heart rhythm. Additionally or alternatively, aFib patients are treated with catheter ablation.

[0044] Catheter ablation-based therapy may involve mapping the electrical properties of cardiac tissue, particularly the endocardium and cardiac volumes, and selectively ablating the cardiac tissue through the application of energy. Electrical or cardiac mapping (e.g., implemented by any of the EP cardiac mapping systems and techniques described herein) involves creating an electrical potential map (e.g., a voltage map) of wave propagation along the cardiac tissue or a map of arrival times (e.g., a LAT map) to points located within various tissues. Electrical or cardiac mapping (e.g., a cardiac map) may be used to detect localized cardiac tissue dysfunction. Ablation, such as cardiac mapping-based ablation, can stop or alter the propagation of unwanted electrical signals from one portion of the heart 120 to another.

[0045] The ablation process lesions unwanted electrical pathways by creating non-conducting lesions. Various energy delivery modalities have been disclosed for creating lesions, including the use of microwave, laser, and more generally, radiofrequency energy to create conduction blocks along cardiac tissue walls. In a two-stage procedure (mapping followed by ablation), electrical activity at points within the heart 120 is typically sensed and measured by advancing a catheter 110 containing one or more electrical sensors (e.g., electrodes 111) into the heart 120 and acquiring / capturing data (e.g., biometric data generally or ECG data specifically) at multiple points. This ECG data is then used to select a target region of the endocardium where ablation will be performed.

[0046] Cardiac ablation and other cardiac EP procedures are becoming increasingly complex as clinicians treat challenging conditions such as atrial fibrillation and ventricular tachycardia. Treatment of refractory arrhythmias may currently rely on the use of three-dimensional (3D) mapping systems to reconstruct the anatomy of the target heart chamber. In this regard, the decision engine 101 employed by the system 100 manipulates and evaluates biometric data in general, or ECG data in particular, to generate improved tissue data that enables more accurate diagnosis, imaging, scanning, and / or maps for treating abnormal heart rhythms or arrhythmias. For example, cardiologists 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 decision engine 101 of the system 100 enhances this software to generate and analyze improved biometric data, thereby providing additional information regarding the EP characteristics of the heart 120 (including scar tissue) that are representative of the cardiac substrate (electroanatomical and functional) of the aFib.

[0047] Therefore, system 100 can implement a 3D mapping system, such as the CARTO® 3 3D mapping system, to identify potential arrhythmogenic substrates for cardiomyopathies in terms of detecting abnormal ECGs. Substrates associated with these cardiac conditions have been associated with the presence of fragmented and delayed ECG activity in the endocardial and / or epicardial layers of the ventricular chambers (right and left). Abnormal tissue is generally characterized by low-voltage ECG activity. However, early clinical experience with endocardial-epicardial mapping has shown that areas of low voltage are not always present as the sole arrhythmogenic mechanism in such patients. Indeed, areas of low or medium voltage may exhibit fragmented and delayed ECG activity during sinus rhythm, corresponding to critical isthmuses identified during sustained, coherent ventricular arrhythmias (e.g., only applicable to nonpermissive ventricular tachycardias). Furthermore, fragmented and delayed ECG activity is often observed in areas exhibiting normal or near-normal voltage amplitudes (>1-1.5 mV). The latter regions can be assessed according to voltage amplitude but are not considered normal according to the intracardiac signal and therefore represent true arrhythmogenic substrates. 3D mapping may be able to localize arrhythmogenic substrates on the endocardial and / or epicardial layers of the right / left ventricle, which may vary in distribution depending on the primary disease evolution.

[0048] As another exemplary operation, cardiac mapping may be performed by the system 100 using one or more multi-electrode catheters (e.g., catheter 110). The multi-electrode catheters are used to stimulate and map electrical activity within the heart 120 and to ablate sites of abnormal electrical activity. In use, the multi-electrode catheter is inserted into a major vein or artery, such as the femoral artery, and then guided into a chamber of the heart 120. A typical ablation procedure involves inserting the catheter 110, which has at least one electrode 111 at its distal end, into the heart chamber. A reference electrode is provided by taping to the patient's skin, by a second catheter positioned in or near the heart, or by selecting one or other of the electrodes 111 on the catheter 110. Radio frequency (RF) current is applied to the tip electrode 111 of the ablation catheter 110, and the current flows through the medium surrounding the tip electrode (e.g., blood and tissue) toward the reference electrode. The current distribution is determined by the amount of electrode surface in contact with the tissue compared to the blood, which has a higher conductivity than the tissue. Tissue heating occurs due to its electrical resistance. Sufficient tissue heating induces cell destruction in the cardiac tissue, resulting in the formation of electrically non-conductive lesions within the cardiac tissue. This process also heats the tip electrode 111 as a result of conduction from the heated tissue to the electrode itself. If the electrode temperature becomes high enough, potentially exceeding 60°C, a thin, transparent film of dehydrated blood proteins can form on the surface of the electrode 111. As the temperature continues to rise, this dehydrated layer can gradually thicken, causing blood to coagulate on the electrode surface. Because dehydrated biological materials have a higher electrical resistance than endocardial tissue, the impedance to the flow of electrical energy into the tissue also increases. If the impedance increases sufficiently, the catheter 110 must be removed from the body and the tip electrode 111 must be cleaned.

[0049] Information about the catheter may be recorded, which may include, in addition to the elements described herein, for example, tissue contact information, proximity contact information, catheter maneuverability, and catheter deflection count.

[0050] 2 is a diagram of a system 200 capable of implementing one or more features of the subject matter of this disclosure, according to one or more embodiments. The system 200 includes an apparatus 204, a local computing device 206, a remote computing system 208, a first network 210, and a second network 211 associated with a patient 202 (e.g., an example of the patient 125 of FIG. 1 ). Additionally, the apparatus 204 can include a biometric sensor 221 (e.g., an example of the catheter 110 of FIG. 1 ), a processor 222, a user input (UI) sensor 223, a memory 224, and a transceiver 225. For ease of explanation and brevity, the decision engine 101 of FIG. 1 is shown again in FIG. 2.

[0051] According to one embodiment, device 204 may be an example of system 100 of FIG. 1 , and device 204 may include both patient-internal and patient-external components. According to one embodiment, device 204 may be an external device to patient 202, including an attachable patch (e.g., attached to the patient's skin). According to another embodiment, device 204 may be internal to the body of patient 202 (e.g., subcutaneously implantable), and device 204 may be inserted into the body of patient 202 via any applicable method, including oral infusion, surgical insertion via a vein or artery, endoscopic surgery, or laparoscopic surgery. According to one embodiment, although a single device 204 is shown in FIG. 2 , an exemplary system may include multiple devices.

[0052] Thus, the apparatus 204, the local computing device 206, and / or the remote computing system 208 can be programmed to execute computer instructions for the decision engine 101. As an example, the memory 223 stores these instructions for execution by the processor 222 so that the apparatus 204 can receive and process biometric data via the biometric sensor 201. In this manner, the processor 222 and memory 223 are representative of the processor and memory of the local computing device 206 and / or the remote computing system 208.

[0053] 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 stores, executes, and implements 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, extensible, and modular, with the ability to be tailored for different services or to reconfigure some functions independently of others.

[0054] 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 over network 210 between apparatus 204 and local computing device 206 using any one of a variety of 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 an intranet, a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a direct connection or series of connections, a cellular telephone network, or any other network or medium capable of facilitating communication between local computing device 206 and remote computing system 208. Information can be transmitted over network 211 using any one of a variety of long-range wireless communication protocols (e.g., TCP / IP, HTTP, 3G, 4G / LTE, or 5G / New Radio). In both networks 210 and 211, wired connections can be implemented using Ethernet, Universal Serial Bus (USB), RJ-11, or any other wired connection, and wireless connections can be implemented using Wi-Fi, WiMAX, Bluetooth, infrared, cellular networks, satellite communications, or any other wireless connection method.

[0055] During operation, device 204 can continuously or periodically acquire, monitor, store, process, and communicate biometric data associated with patient 202 via network 210. Additionally, device 204, local computing device 206, and / or remote computing system 208 communicate through networks 210 and 211 (e.g., local computing device 206 can be configured as a gateway between device 204 and remote computing system 208). For example, device 204 can be an example of system 100 of FIG. 1 configured to communicate with local computing device 206 via network 210. 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 any other device configured to communicate with other devices via networks 211 and 210. A remote computing system 208, implemented as a physical server on or connected to the network 211 or as a virtual server within a public cloud computing provider of the network 211 (e.g., Amazon Web Services (AWS)®), can be configured to communicate with the local computing device 206 over the network 211. Thus, biometric data associated with the patient 202 can be communicated throughout the system 200.

[0056] The elements of device 204 are now described. Biometric sensor 221 may include, for example, one or more transducers configured to convert one or more environmental conditions into electrical signals so that different types of biometric data may be observed / obtained / acquired. For example, biometric sensor 221 may include one or more of an electrode (e.g., electrode 111 of FIG. 1 ), a temperature sensor (e.g., a thermocouple), a blood pressure sensor, a blood glucose sensor, a blood oxygen sensor, a pH sensor, an accelerometer, and a microphone.

[0057] The processor 222 executing the decision engine 101 may be configured to receive, process, and manage biometric data acquired by the biometric sensor 221 and communicate the biometric data to the memory 224 for storage and / or across the network 210 via the transceiver 225. Biometric data from one or more other devices 204 may also be received by the processor 222 through the transceiver 225. Additionally, as described in more detail herein, 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 such that different tasks of the patch (e.g., data acquisition, storage, or transmission) can be initiated based on the detected pattern. In some embodiments, the processor 222 may generate audible feedback regarding the detection of a gesture.

[0058] The UI sensor 223 may include, 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 implement capacitive coupling in response to the patient 202 tapping or touching the surface of the device 204. Gesture recognition may be performed via any one of a variety of capacitive types, such as resistive capacitive, surface capacitive, projected capacitive, surface acoustic wave, piezoelectric, and infrared touch. The capacitive sensor may be disposed over a small area or length of the surface, such that a tap or touch on the surface activates the monitoring device.

[0059] The memory 224 is any non-transitory, 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). The memory 224 stores computer instructions that are executed by the processor 222.

[0060] The transceiver 225 may include a separate transmitter and a separate receiver, or alternatively, the transceiver 225 may include a transmitter and receiver integrated into a single device.

[0061] In operation, the device 204 utilizes the decision engine 101 to observe / acquire biometric data of the patient 202 via the biometric sensor 221, store the biometric data in memory, and share this biometric data throughout the system 200 via the transceiver 225. The decision engine 101 may utilize models, neural networks, machine learning, and / or artificial intelligence to measure the effectiveness of any catheter structure (e.g., once constructed) and to provide quantitative, statistical, and / or similar feedback of the effectiveness of a particular diagnostic catheter to improve the design of the catheter structure.

[0062] The biometric and / or test or measurement data may include, for example, the outcome of the procedure, the software used during the procedure plus any variables or options included in or used within the software, such as physician and / or patient authorization, the serial number of the catheter used, the location of the catheter, the catheter contact force, patient demographics including BMI, and the abnormality being treated. The biometric and / or test or measurement data may include the location within the patient's body where the procedure was performed, including environmental data, and also the location within the patient's body, such as the atrium or ventricle. Electrode placement and which electrodes were used in the procedure may be included. The biometric and / or test or measurement data may include follow-up information received after the procedure.

[0063] Multi-parameter and / or single-parameter regression of the applied PFA parameter(s) with PFA lesion depth and width may be used to determine the zone of irreversible electroporation and reversible ablation lesion zone (width or depth) projected onto a 3D electroanatomical map. This regression correlates the applied PFA parameter(s) with lesion depth, width, and spatial location based on distance from the PFA catheter, providing the physician with information about the PFA lesion. Other parameters include tissue wall thickness, nearby tissue type (e.g., myocardium, smooth muscle), and myocardial fiber orientation.

[0064] After application of PFA, the PFA "realistic" lesion may be projected onto an electroanatomical map to provide a visual representation of the PFA lesion, including lesion width, lesion depth, and cardiac tissue in the zones of irreversible and reversible electroporation. The visual representation may be color-coded.

[0065] Lesions projected onto the cardiac anatomy (3D electroanatomical map) from the application of PFA can be color-coded as irreversible (i.e., red) and reversible (i.e., yellow) according to the zone in which they are located, and sized based on the parameters of the application of PFA. The size and spatial projection of the resulting lesion can be determined by multiparametric regression developed and validated from preclinical work relating PFA parameters to lesion size and width.

[0066] A model can be created for each catheter design, and this model can be specific to the created electric field and the particular geometry of the electrodes on the catheter. This provides a general model specification for use with other PFA catheter technologies, where the initial model is represented by the electric field (voltage) and other parameters are measured based on preclinical and in vivo data. This data can include distance morphology endocardium, including information collected from other data collection sources (i.e., Carto, ICE, etc.). In other applications with PFA, the parameter boundaries may be different and the number of electrodes may be different, but the general equations retain the key parameters adjusted accordingly.

[0067] As presented in the paper "Fundamental Study on the Effects of Irreversible Electroporation Pulses on Blood Vessels with Application to Medical Treatment" by Elad Maor, lesions and modeling can be accurately predicted. As shown in the paper, there is a three-dimensional simulation showing the cross section of two needles and the electric field around the needles across the underlying tissue. As shown, the plot provides an electric field greater than 900 V / cm due to a potential difference of 800 V. The voltage threshold reached based on calculations in the model, with a threshold of 900 V / cm, represents the region where cell death occurs.

[0068] Additionally, the paper presents a two-dimensional simulation of two circular electrodes with a potential difference of 800 V. The plot shows an electric field greater than 900 V / cm. The blue 2D region represents the region of cell death in the experiment. The region closest to the electrodes in the electric field has a voltage / cm greater than 900 V / cm, representing the region of irreversible electroporation.

[0069] Furthermore, two-dimensional ablation of adherent vascular smooth muscle cells (VSMCs) is demonstrated. A region of dead cells surrounds both needles, correlating with experimental results. The accuracy of the modeling is demonstrated by demonstrating electroporation modeling and bench testing. Both methods show the same region of cell death around the electrode where the electric field was created, supporting this as a predictive tool for identifying cells due to electroporation.

[0070] FIG. 3 illustrates a lasso-style ablation catheter 300 that can be used in an exemplary system capable of implementing one or more features of the presently disclosed subject matter, according to one or more embodiments. FIG. 3 illustrates an example of a loop catheter 300 (also referred to as a lasso catheter) including multiple electrodes 330, 340, and 350 that can be used to map a cardiac region. The loop catheter 300 can be fully or partially elastic so that it can twist, bend, and / or otherwise change its shape based on received signals and / or the action of an external force (e.g., cardiac tissue) on the loop catheter 300. The loop catheter 300 can include a shaft 320 having electrodes 330, 340, 350 attached to the end of the shaft 320. The shaft 320 can be fully or partially flexible. A handle 310 can be used to manipulate the catheter 300. The electrodes can include, for example, ablation electrodes, voltage-sensing electrodes, and / or any other suitable electrode type. The electrodes 330, 340, 350 may have a width of 1 mm to 4 mm and are spaced 1 mm to 10 mm apart. The electrodes 330, 340, 350 are connected to a connector at the proximal end of the catheter 24 by wires (not shown) that pass through the catheter. Alternatively, other electrode configurations may be used. For example, the end may include only a ring electrode and no tip electrode.

[0071] FIG. 4 illustrates a basket-type ablation catheter that can be used in an exemplary system capable of implementing one or more features of the presently disclosed subject matter, according to one or more embodiments. Experiments were conducted using a basket-type ablation catheter substantially similar to the catheter end effector assembly 438 of FIG. 4 . The basket assembly 438 includes multiple flexible spines 414 formed at the end of a tubular shaft 484 and connected at both ends. During a medical procedure, the medical professional 115 can deploy the basket assembly 438 by extending the tubular shaft 484 from an insertion tube 430 (which is part of the sheath 113) and transitioning the basket assembly 438 out of the insertion tube 430 to its expanded configuration. The spines 414 may have an elliptical, e.g., circular, or rectangular cross-section that may appear flat, and may include a flexible, resilient material forming struts, e.g., a shape-memory alloy such as nickel-titanium, also known as nitinol, as described in more detail herein. As shown in FIG. 4 , the basket assembly 438 has a proximal portion 436 with a distal end 439. The medical probe 105 can include a spine-retaining hub 490 that extends longitudinally from the distal end of the tubular shaft 484 toward the distal end 439 of the basket assembly 438. As described above, the control console 160 includes an irrigation module that delivers irrigation fluid through the tubular shaft 484 to the basket assembly 438.

[0072] Figure 5 shows a large electrode 500 that can be implemented with the basket-style ablation catheter of Figure 4. Figure 6 shows a barrel electrode that can be implemented with the lasso-style ablation catheter of Figure 3. Two types of electrodes are used in the experiments: a large electrode 500 as shown in Figure 5, and a small barrel-style electrode 600 as shown in Figure 6.

[0073] Ablation was performed using these two types of electrodes (500, 600) with two different applications of ablation pulses: (1) three applications of predefined ablation pulses, and (2) six applications of predefined ablation pulses. Statistical data for these electrodes is shown in Figure 7. A summary of the lesion depths and their deviations in the samples is summarized in Table 1.

[0074] [Table 1]

[0075] From Table 1, (a) increasing lesion depth correlates with increasing number of repetitions regardless of electrode size, and (b) small electrodes appear to be slightly larger than large electrodes in lesion depth, although the difference is not significant (p=0.67).

[0076] FIG. 8 illustrates a lesion visualization 800 created by an exemplary system capable of implementing one or more features of the presently disclosed subject matter, according to one or more embodiments. For example, a CARTO3 system may be used to visualize the lesions to determine which lesion is better. As shown, lesion LZ1 is not as good as lesion LZ2. Lesion LZ2 is the better lesion. By way of example, using feedback, lesion LZ2 is better because a deeper lesion in the appropriate anatomical location provides better durability for better efficacy over time.

[0077] Figure 9 shows a representation of sample tissue 900 containing a lesion 910 of measured depth. Figure 9 provides an example of creating a lesion 910 using PFA, with the maximum depth and width of the PFA lesion. Figure 9 shows an example of a lesion depth used for a 3x application of PFA to inform and determine Equation 1 provided below.

[0078] Based in part on experiments, a model for the lesion size (LS) curve can be expressed as Equation 1: LS=6 * (1-e-0.538x2 -1.92) Equation 1

[0079] This equation for LS provides a specific formula related to a particular catheter and design. The generated electric field is specific to the catheter design and PFA formulation. The curve provided by this equation can be shifted up or down based on the parameters mentioned above. While this equation provides a specific example, it also represents a general model for use with other catheters. As an example, the same pulse sequence can be applied to other catheter designs. The asymptotically increasing plateau curves for other catheter designs will be very similar. Therefore, the model may be based on an exponential plateau equation regardless of the number of variables used.

[0080] Figure 10 shows a graphical representation 1000 of data collected from the Omnypulse catheter 400 of Figure 4. The data in graph 1000 can be used to create a regression equation relating lesion depth (y-axis) to the number of PFAs (x-axis).

[0081] FIG. 11 shows a representation 1100 of the electric field associated with measuring lesion depth. As shown, there is a spacing 1110 between the electrodes. In the illustration, this is provided as 4 mm. Adjacent electrodes provide an associated electric field 1120 between the pair, as shown via the two smaller ellipses (e.g., 1120 between electrodes 5 and 6). 56 , and 1120 between electrodes 6 and 7 67 (shown as a sphere). Generally, a larger electric field 1130 is generated surrounding the electrode. This electric field 1130 is shown as a larger ellipse surrounding the electrode. As shown, the electric field 1130 penetrates approximately 1-3 mm into the tissue, allowing for measurement of tissue-related lesions.

[0082] Measurements may be taken using the Varipulse or Lasso system of Figure 3, and the inter-electrode spacing 1110 may be modified to be 1.5 mm. Additionally, the Omnypulse of Figure 4 or other catheter designs may be used to provide a spherical electric field 1130.

[0083] Parameters of measurement, including boundaries, could be PFA danger zone 0-10 mm (specific to catheter geometry and design and defined by the electric field from COMSOL modeling), distance offset (median / zone) from endocardium 0-10 mm (constructed with contact in mind, then have a statistical model where lesion depth is not achieved and therefore predicts a lower coefficient, or could be binary), temperature / conductivity 35-90 °C (max per, max +) (representing velocity, depth, and thermal effect), tissue dynamic homogeneity 0-1 (based on tissue type and number of applications), number of applications 1-infinity, number of pulses / trains 5, 7, 10 (min, mode, max), max + (2200 V), number of electrodes 1-10 (zones 1-3, 4-7, 8-10) (incorporation in the model of distance), and impedance range (90-190 ohms). A bipolar impedance measurement (160-190 ohms, then the model works) is taken, extrapolating to other electrode geometries to determine impedance. Electrode contact with the tissue may be used as the number of electrodes in contact, ranging from 0 to Max electrodes. Contact force (CF) may be binary or quantitative, ranging from 0 to 50 grams of force. Another variable that may be weighted in the formula is the orientation of the catheter relative to the tissue or the angle of orientation relative to the tissue. This may include parallel, perpendicular, and oblique / diagonal. Another parameter may include the number of pulse applications or deliveries and / or the total number of ablations performed at a single x, y, and z coordinate location on the tissue. Figure 11 also provides a visual schematic of certain parameters for determining the electric field range and lesion depth.

[0084] FIG. 12 shows a graph 1200 of a parametric curve based on varied variables. The curve shows lesion depth 1210 in mm as a function of score or parameter k 1220. k is a parametric weighting function of Ax+Bx1+Cx2+Dx3+...+Gx6... In one example, x1 equals number of applications 1230, x2 equals distance 1240, x3 equals tissue conductivity 1250, x4 equals tissue thickness (not shown), x5 equals generating impedance (not shown), x6 equals number of electrodes (not shown), etc. Curves 1230-1250, as well as curves discussed but not shown, may be combined and weighted in different ways.

[0085] Various parameters may be used, including those discussed throughout this specification. Parameters include the number of applications ranging from 1 to 12, contact force ranging from 5 to 80 g (after which there is no effect on the equation as it plateaus), and distance from the anatomical structure ranging from 0 to 12 mm. Additionally or alternatively, the following parameters may be used, individually or in any combination: These parameters may include, by way of non-limiting example, voltage, current, impedance, conductivity, temperature, number of electrodes, resistance, number of pulses, pulse width, time between applications, number of applications, tissue permeability, tissue heterogeneity, electric field density, IRE frequency, electrode geometry, and tissue mobility (cellular properties). These parameters may be included in the combination and weighting of curves 1230-1250, and some discussed but not shown may be combined and weighted in different ways.

[0086] For example, temperature and distance to tissue may be correlated to the burn and directly correlated to the burn zone. ECG attenuation over time differs based on the IRE and RE zones. Tissue contact, current delivered, and number of applications may be correlated to lesion depth and provide initial electric field values.

[0087] Single and / or multi-parameter regressions (any nonlinear, linear, or parametric) using combinations of PFA parameters, including but not limited to voltage, current, number of pulses or pulse trains, number of PFA applications, time between pulses, spatial electric field, and electrode-to-tissue distance, can be used to correlate PFA lesions, and the correlations can be used to highlight zones of irreversible and reversible electroporation following the application of PFA lesions. Identification of IRE and RE zones on cardiac tissue, as well as the relationship of the above parameters to lesion depth, width, and location, can be determined and validated from COMSOL simulations and preclinical studies to provide physicians with an assessment of the zones of cardiac tissue affected by the application of PFA. These parametric regressions are developed so that the aforementioned parameters are tested and validated in controlled preclinical models, where one or more of the above-listed parameters (voltage, current, number of pulses, pulse length, number of PFA applications, spatial electric field based on the number of electrodes, and electrode-to-tissue distance) are characterized and correlated to the created lesions (lesion width, depth, and 3D spatial location). Any or all other parameters used / manipulated within the PFA ablation system can also be used in a regression model to predict the location and depth of the lesion, which can then be displayed on a 3D electroanatomical map as irreversibly or reversibly electroporated tissue, where irreversibly electroporated cardiac tissue is colored red and reversibly electroporated cardiac tissue is colored yellow on the 3D electroanatomical map (CARTO).

[0088] Preclinical data, based on several types of serial imaging (i.e., MRI), helps indicate irreversible and reversible ablation zones. The model provides the ability to identify irreversible and reversible ablation zones on tissue. Furthermore, the mathematical model can be used to predict lesion size and then predict IRE and RE zones. The model may consider the specific catheter, voltage, number of electrodes and pulses, application times and location relative to the endocardium, as well as tissue type and other cellular effects such as changes in conductivity after each pulse. The model may include any nonlinear regression including the parameters listed in the parameter bounds, which can be used to generate lesion scores and support claims regarding predictive modeling of PFA lesions. The model can be any nonlinear regression including all listed parameters and parameter bounds, as well as any model using fewer parameters. Additional parameters can be added based on catheter type.

[0089] The model is aided by the use of ECG response curves between the RE and IRE zones to determine lesion depth. The ECG can be utilized to correlate with preclinical work. When predicting which curve will result in IRE given PFA, there is a correlation to the different curves of RE versus IRE tissue.

[0090] Modifications that can be made are to essentially change the type of parameters used (i.e., voltage, current, etc.) and use all or any of the PFA parameters to create correlations with PFA lesions, lesion depth, width, and spatial location on the cardiac tissue.

[0091] The model follows an exponential plateau regression, where D = distance to the myocardium, Max = maximum lesion depth, and k is a dynamic cellular parameter. Equation 2 is as follows: LS=(Max-(Max-initial size) * e(-kx))-Dist formula 2 where x is the number of applications or pulses and Dist is the distance from the endocardium.

[0092] The model considers the voltage field based on COMSOL modeling to generate LSmax. Distance is generated from CARTO or ICE data, or any form of data that can provide distance from the endocardium, including impedance. The initial lesion size is typically 0, but other values ​​can be used. k is a score or parameter that represents cell-related changes that cause IRE as more pulses are delivered. Changes in tissue structure, such as decreasing the time between pulses or applications, can result in slightly increased lesion depth and potentially create lesions more quickly than pulses with a longer time span. k depends on several parameter bounds, including tissue homogeneity, time between pulses or applications, and electric field homogeneity, which changes as more pulses are delivered.

[0093] Intracardiac ECGs can verify the durability and depth of the correlation between acute and chronic lesion measurements, and bench temperature data demonstrated this type of exponential plateau curve, with the temperature reaching a plateau as 60°C at a depth of 3 mm based on specific PFA parameters (number of applications, time delay between pulses, maximum voltage of the electric field, and current density).

[0094] An exponential plateau curve is realistic when modeling the data from the PFA lesion creation model. This is shown with increasing contact with PFA, and the lesion growth curve is achieved where the lesion depth plateaus at some point due to the depth limitation of the electric field.

[0095] The particularities of PFA lesion prediction are shown to account for differences in catheter design from company to company, as well as the numerous parameters that influence lesion generation, not only at the catheter and generator level, but also in vivo cellular effects during PFA ablation, such as distance and surrounding tissue.

[0096] 13 illustrates a method 1300 according to one embodiment of the present invention. A method 1300 is provided for determining an ablation lesion zone (width or depth) projected onto an electroanatomical map.

[0097] The method 1300 includes, at 1310, collecting at least one ablation application parameter and at least ablation lesion depth, width, and spatial location. The ablation may be pulsed field ablation (PFA). The ablation application parameters may include tissue wall thickness, nearby tissue type, and myocardial fiber orientation. The nearby tissue type may include, for example, myocardium and / or smooth muscle.

[0098] The method 1300 includes, at 1320, performing a regression of at least one ablation application parameter to correlate the at least one ablation application parameter with ablation lesion depth, width, and spatial location based on distances from the at least two electrodes to the biological tissue. The regression may include multi-parameter regression. The regression may include single-parameter regression. The regression performed may include preclinical work relating the ablation parameter to lesion depth and width.

[0099] The method 1300 includes determining one or more ablation zones, at 1330. The electroporation may be irreversible. The electroporation may be reversible.

[0100] The method 1300 includes, at 1340, projecting the determined one or more ablation zones onto an electroanatomical map. The electroanatomical map may be three-dimensional. The projecting may provide a viewer of the map with a visual representation of the ablation lesion, including lesion width, lesion depth, and cardiac tissue within the zone of electroporation. The projecting may include color-coding the ablation lesion with color-coding indicative of at least one of irreversible electroporation and reversible electroporation. The size of the visual representation of the ablation lesion may correlate with the size of the lesion.

[0101] Method 1300 may also include outputting information regarding the ablation lesion, at 1350. Method 1300 may also include validating, at 1360, performed regression preclinical work relating the ablation parameters to at least one known lesion depth and width.

[0102] When measuring PFA ablation, several PFA applications were performed from x3, x6, x9, and x12, with CF ranging from 5 to 80 g. CF is placed into three strata, including low (5-25 g), high (26-50 g), and very high (51-80 g). The definition of PFAI may be based on the CF value and the number of PFA applications performed for each lesion. Equation 3 relates PFAI and lesion depth to the pulsed field ablation parameter of CF (contact force), and the number of applications, as provided below. Expected lesion depth = PFAI / 100 Equation 3

[0103] Targeted ablations within the ventricles can be performed through pre-specified PFAI ranges (300, 450, and 600) and CF parameters (low, i.e., 5-25 g; high, i.e., 26-50 g; and finally very high CF, i.e., 51-80 g). Each ventricle can receive an average of six PFA ablations according to the ablation protocol, as shown in Table 2, which shows the study-validated ablation parameters.

[0104] [Table 2]

[0105] Lower PFAI values ​​and CF thresholds can be used in the right ventricle to reduce transmural lesions that prevent accurate measurement of lesion depth at higher PFAI values.

[0106] Figure 14 shows four graphs 1400 of CF ranges per PFA dose. The majority of CF values ​​range from 10 to 50 g across all PFA energy doses and are generally evenly distributed between the x3 PFA doses shown in Figure 14A, x6 PFA doses shown in Figure 14B, x9 PFA doses shown in Figure 14C, and x12 PFA doses shown in Figure 14D. The number of PFA applications or PFA doses, x3, x6, x9, and x12 pulses, are equally distributed across the studies examined. PFA applications are performed with a mean CF value of 32 ± 17 g. As shown (collectively) in Figure 14, similar CF values ​​are maintained across the spectrum of different PFA doses. More specifically, CF values ​​are maintained within the low CF (5-25 g), high CF (26-50 g), and very high CF (51-80 g) ranges, representing 40%, 41%, and 15% of animals, respectively.

[0107] Lesion depth results are shown in Table 3 Study Characterization: Correlation with PFA Dose, Contact Force, and Ventricular Lesion Depth.

[0108] [Table 3]

[0109] The lesion width results are also shown in Table 4. Study Characterization: Correlation with PFA Dose, Contact Force, and Ventricular Lesion Width.

[0110] [Table 4]

[0111] The mean lesion depth and width were 3.5 ± 1.2 mm and 12.0 ± 3.5 mm, respectively. Lesion depths ranging from 0.90 to 6.4 mm and depths of ≥ 5 mm were achieved in 17% of lesions, the majority of which (58%) were performed with the highest PFA dose (x12). None of the lesions performed were transmural.

[0112] Lesion size is clearly affected by both the number of PFA applications (i.e., PFA dose) and the CF value (catheter-tissue contact). Indeed, considering the spectrum of PFA doses, the mean lesion depth nearly doubled from 2.48 ± 0.90 to 4.52 ± 1.09 mm when x3 and x12 PFA doses were applied, respectively, i.e., p < .005 in Table 3. Slightly wider lesions are generally expected for higher PFA doses, as illustrated in Table 4. CF affected lesion size at a fixed number of applications, regardless of application frequency; mean lesion depth exceeded 1 mm for CFs between 10 g and 60 g, increasing consistently across application frequencies. In this regard, applications performed within the low CF range (5-25 g) are associated with significantly shallower ventricular lesions (2.98 ± 0.98 mm) compared to applications performed within the high CF range (26-50 g, 3.82 ± 1.21 mm), as well as very high CF values ​​(51-80 g, 4.23 ± 1.30 mm) (p < 0.05), as shown in Table 3. A similar observation applied to lesion width in Table 4.

[0113] Figure 15 shows several plots 1500 of the effects of CF and PFA on lesion depth (Panel A) and lesion width (Panel B). For each PFA application, lesion depth (shown in Figure 15A) and lesion width (shown in Figure 15B) are linearly related to the CF value. An increase in lesion size is achieved when switching from a very low x3 dose to a high dose PFA x12, provided that a CF > 5g is guaranteed. The increase in lesion depth is shown in Figure 15C, and the increase in lesion width is shown in Figure 15D. The interaction of CF and PFA, which exponentially increases lesion depth, is shown in Figure 15C. The effect on lesion width, shown in Figure 15D, is less clear.

[0114] Therefore, regression analysis may rule out any potentially confounding effects of CF and PFA dose on lesion size, as shown in Figures 15A-15D. The relationships between CF and lesion depth in Figure 15A (y = 2.882 + 0.0209x, r² = 0.08, p = 0.0024) and between CF and lesion width in Figure 15B (y = 10.633 + 0.0422x, r² = 0.04, p = 0.0043) were best fitted to linear regression curves across the spectrum of PFA applications, whereas the interaction between CF and PFA dose affected ventricular lesion depth through a logarithmic relationship, as shown in Figure 15C. It was the combination of PFA energy and CF > 5 g that produced significantly deeper lesions than either CF or PFA dose alone. The role of CF and PFA dose on lesion width appeared less predictable, as shown in Figure 15D.

[0115] Figure 16 shows several representations 1600 of the effect of CF > 5g and PFA dose on lesion size. After achieving good catheter contact (CF > 5g), progressively higher PFA doses are associated with deeper lesions, as shown in Figure 16A, but with overlapping widths, as shown in Figure 16B. Histological sections, as shown in Figures 16C, 16D, 16E, and 16F, are consistent with the data in Figures 16A and 16B. Figure 16C shows three applications with 2.5 x 13.2 mm lesions. Figure 16D represents six applications with 3.3 x 14.9 mm lesions. Figure 16E represents nine applications with 4.2 x 13.2 mm lesions. Figure 16F represents 12 applications with 5.6 x 13.6 mm lesions. When the system was switched from a x3 to a x12 PFA dose, a slight increase in lesion width occurred, and the average lesion depth doubled. Specifically, the average lesion width was 9.739889 mm after three applications, 11.19132 mm after six applications, 13.97311 mm after nine applications, and 13.77438 mm after 12 applications. The average lesion depth was 2.5 mm after three applications, 3.3 mm after six applications, 4.2 mm after nine applications, and 5.6 mm after 12 applications. As can be seen from the data, lesion depth changed, but lesion width did not change significantly after nine applications. The effect on lesion width and depth indicates that the dynamic range of lesion width is smaller than that of lesion depth, and therefore the relationship between lesion width and the regression equation is weaker than that of lesion depth.

[0116] Unlike the lesion depth shown in Figure 16A, progressively larger applications of PFA applied at CF > 5 g resulted in overlapping lesion widths, as shown in Figure 16B. As demonstrated on the tissue sections shown in Figures 16C-16F, the depth nearly doubled when the system was switched from the low dose ×3 PFA shown in Figure 16C to the high dose ×12 pulses of PFA shown in Figure 16F.

[0117] Right and left ventricular PFA lesions were analyzed to demonstrate whether the PFAI (ranges of 300, 450, and 600) could predict actual lesion depth. Following the ablation protocol in Table 2, 6.8 ± 1.2 and 5.3 ± 0.8 applications were evaluated in the right and left ventricles, respectively, with 29 (34%) falling within the 300 PFAI range (307 ± 21, range: 268-343), 23 (31%) falling within the 450 PFAI range (460 ± 24, range: 424-554), and finally, 21 (29%) falling within the 600 PFAI range (547 ± 34, range: 475-590). Regarding CF values, 29 (40%), 30 (41%), and 14 (19%) lesions were performed within the low (5-25 g), high (26-50 g), and very high (51-80 g) CF strata, respectively. In this dataset, the mean lesion depth was 3.6 ± 1.0 mm (3.2 ± 0.9 mm and 4.2 ± 0.9 mm for the right and left ventricles, respectively), ranging from 1.7 to 6.6 mm, achieved with a mean PFAI of 424 ± 105. Table 5 displays the mean lesion depths associated with each achieved PFAI range (i.e., 300, 450, and 600) and stratified according to the low, high, and very high CF datasets. Table 5 shows the correlation between study validation: PFA dose, contact force, and ventricular lesion depth.

[0118] [Table 5]

[0119] Figure 17 graphically illustrates the relationship between CF and PFAI. PFAI and CF are linearly related to each resulting PFAI value. PFAI and CF are linearly related with higher PFAI values ​​(300, 450, and 600), resulting in progressively deeper lesions (2.86±0.67, 3.92±0.73, and 4.41±0.94 mm, respectively, p<0.001).

[0120] Figure 18 shows the correlation 1800 between lesion depth and PFAI. Figure 18A shows the obtained PFAI values ​​plotted against the histology of the observed lesion depth. Figure 18B shows the prediction accuracy of lesion depth compared to the expected lesion depth. Lesion depth and PFAI are linearly related (r² - 0.6644), with more than 60% of the variability in lesion depth defined by the variability of the PFAI parameter. Actual lesion depth can be plotted against the expected lesion depth (PFAI / 1000). Actual lesion depth is predicted by the PFAI values ​​obtained during ablation with a prediction accuracy of ±2 mm. The association between PFAI and lesion depth can be described using a linear regression model (y = 0.923 + 0.640x, r² = 0.66, p < 0.001) as shown in Figure 18A. Actual ventricular lesion depth can be predicted for each lesion with an accuracy of ±2 mm by dividing the obtained PFAI by a factor of 100, as shown in Figure 18B.

[0121] Figure 19 shows two histological structures 1900 that provide a correlation between PFAI and ventricular lesion depth. PFAI correlates with average ventricular lesion depth through the formula described above (lesion depth = PFAI / 100), regardless of the contact force applied during ablation. A PFAI of 298, as shown in Figure 19A, and a PFAI of 527, as shown in Figure 19B, provide insight into the prediction of lesion depth through PFAI values. Specifically, in Figure 19A, a force of 55 g and a PFI of 299 provide a measured depth of 2.98 mm, while in Figure 19B, a force of 30 g and a PFI of 527 provide a measured depth of 4.92 mm. Deeper lesions can be achieved by switching from a low dose to a high dose of PFA, regardless of the CF value.

[0122] The effects of CF and PFA dose on lesion size in ventricles undergoing PFA using a CF-sensing OMNYPULSE catheter are presented. While both variables proved more relevant to adequate lesion formation than either CF or PFA application rate alone, it was their interaction that acted synergistically on lesion formation. Indeed, once adequate catheter-tissue contact was achieved (CF > 5 g), switching from a low dose to a high dose of PFA resulted in significantly deeper lesions without any apparent effect on lesion width. Validation of these parameters through an entirely new equation, the PFAI, utilized to guide PFA ablation further aided in understanding the effects of CF and PFA application rate on lesion size by predicting actual ventricular lesion depth.

[0123] These results are even more significant considering the lack of data regarding the optimal ablation parameters necessary to achieve adequate lesion formation during VT ablation. Indeed, unlike the field of AF ablation, where ablation index (AI) algorithms have been widely studied, experience with the implementation of AI during VT ablation is very limited, and comparable indicators of lesion quality for PFA have not previously been studied in this setting.

[0124] A new index, PFAI, is provided to guide intraventricular PFA and accurately predict actual ventricular lesion depth.

[0125] Catheter-tissue contact is paramount to achieving adequately deep lesions, and PFA application is performed at a CF >5 g. Recent evidence has shown that without good catheter-tissue contact, PFA produces no or minimal detectable lesions, and that a 1-2 mm increase in the distance between the catheter tip and myocardial tissue can double the energy required to create a 3 mm deep lesion.

[0126] The combined effect of PFA dose and CF during PFA synergistically influences ventricular lesion size as assessed by histology. A new parameter, PFAI, representing the lesion quality of performing PFA dose and CF makes it possible to predict actual lesion size. For a given lesion width, the next point in ablation can be calculated based on actual data, and the location of the next point can be determined by the system.

[0127] We use depth and width regression as shown in Equation 4. V=Vm-(Vm-V0) * exp(-(b0 * log(n) * x) Equation 4 where V is the dependent variable (depth or width), x is the independent variable (force), n is the number of applications, Vm is the maximum value (plateau value) of V, V0 is the initial value of V, and b0 is a parameter.

[0128] 20 shows a chart 2000 of the depth regression. The number of regression applications and b0 are provided in relation to Table 6 below.

[0129] [Table 6]

[0130] 21 shows a chart 2100 of the depth interpolation regression. The number of applications of the regression and b0 are provided in relation to Table 7 below.

[0131] [Table 7]

[0132] 22 shows a chart 2200 of the width regression. The number of applications of the regression and b0 are provided in relation to Table 8 below.

[0133] [Table 8]

[0134] 23 shows a chart 2300 of the width interpolation regression. The number of applications of the regression and b0 are provided in relation to Table 9 below.

[0135] [Table 9]

[0136] The distance equation is given as shown in Equation 5 below. Log_Result=-ln((distance-x) / apply {distance≧6, distance≦12 Formula 5 where saturation_func=1 / (1+exp(-(log_result-ln(max_value)))) and Y=max_value * saturation_func, max_value=1, max_value scales the output to the desired maximum value (1 mm), distance=distance from the surface to the center of the basket, x=recorded depth or width of the lesion, and applies=number of applications.

[0137] Figure 24A shows the pre-ablation electroanatomical map, with color indicating functional areas, e.g., red indicates abnormal signal generation, while blue and green indicate zones of ablation.

[0138] Figure 24B shows red ablation zones, including pulmonary vein isolation and spot ablation of the posterior wall and roof of the left atrium, which were previously purple on the pre-ablation map (Figure 24A). The purple in Figure 24B represents areas unaffected by the ablation. Note that the ablation zones may indicate either or both lesion depth and width in either alphanumeric or pictographic form. The predicted lesion width may be 13 mm for each ablation dot.

[0139] 25 illustrates a method 2500 according to one embodiment of the present invention. At 2505, method 2500 includes selecting a target PFA index value. At 2510, method 2500 includes initiating IRE treatment. At 2520, method 2500 includes measuring an average contact force and number of current applications during ablation. At 2530, method 2500 includes calculating a predicted depth using a logarithmic function using the number of current applications and contact force.

[0140] At 2540, method 2500 includes measuring the distance from the surface to the center of the basket. If the distance is greater than 6 mm and less than 12 mm, the distance may be used to calculate depth and width measurements using a natural logarithm function and a saturation function, as shown by Equation 5.

[0141] At 2550, method 2500 includes subtracting the measured depth and width from the predicted depth and width. This may include, for example, adding the final predicted depth and width to the total depth and width.

[0142] At 2560, method 2500 includes determining whether the current application is equal to the final number of applications. If the determination at 2560 is no, then the Ire treatment is continued at 2565 and method 2500 returns to 2520. If the determination at 2560 is yes, then method 2500 includes determining at 2570 whether the PF index value is >= the selected target PF index value. At 2580, method 2500 includes terminating the IRE treatment.

[0143] Any of the examples or embodiments described herein may include various other features in addition to or in place of those described above. The teachings, representations, embodiments, examples, etc. described herein should not be considered in isolation from one another. Various suitable ways in which the teachings herein can be combined should be apparent to those of ordinary skill in the art in view of the teachings herein.

[0144] While exemplary embodiments of the subject matter contained herein have been shown and described, further adaptations of the methods and systems described herein may be achieved by appropriate modifications without departing from the scope of the claims. Additionally, while the methods and steps described above indicate particular events occurring in a particular order, it is intended that the particular steps need not be performed in the order described, but rather that the steps may be performed in any order so long as they enable the embodiment to function for its intended purpose. Accordingly, to the extent there are variations of the invention that are within the spirit of the disclosure or equivalent to the invention found in the claims, this patent is intended to cover those variations as well. Some such modifications should be apparent to those skilled in the art. For example, the examples, embodiments, geometries, materials, dimensions, proportions, steps, etc. discussed above are exemplary. Therefore, the claims should not be limited to the specific details of structure and operation set forth in the specification and drawings.

[0145] [Embodiment] (1) A method for determining an ablation lesion zone (width or depth) projected onto an electroanatomical map, said method comprising: delivering pulsed energy between at least two electrodes in contact with the biological tissue; storing a magnitude of a contact force when applied by the at least two electrodes to the biological tissue; calculating one or more ablation zones from the delivering step based on the magnitude of the contact force; and projecting the one or more ablation zones onto an electroanatomical map. (2) The ablation zone includes a depth or width of the ablated region, and the depth or width is V=Vm-(Vm-V0) * exp(-(b0 * log(n) * x) and wherein V is the depth or width of the lesion, x is the measured contact force, n is the number of ablation applications applied by the electrode, Vm is the maximum value of V (of the depth or width) of a possible lesion, V0 is the initial value of the depth or width of the lesion, and b0 is a parameter selectable via a lookup table based on the number n. (3) The method of embodiment 1, wherein determining the ablation comprises multi-parameter regression. (4) The method of embodiment 1, wherein determining the ablation comprises single parameter regression. (5) The method of embodiment 1, wherein the electroporation includes irreversible electroporation.

[0146] (6) The method of embodiment 1, wherein the electroanatomical map comprises a three-dimensional representation of the heart on a display screen. (7) The method of embodiment 1, further comprising presenting information regarding the ablation lesion. (8) The method described in embodiment 1, wherein the ablation application parameters include tissue wall thickness, nearby tissue type, and myocardial fiber orientation. (9) The method of embodiment 8, wherein the nearby tissue types include at least cardiac muscle and smooth muscle. (10) The method of embodiment 1, wherein the projecting provides a viewer of the map with a visual representation of the ablation lesion, including lesion width, lesion depth, and cardiac tissue within the zone of electroporation.

[0147] (11) The method of embodiment 10, wherein the projecting further includes color-coding the ablation lesion. (12) The method of embodiment 11, wherein the color coding indicates at least one of irreversible electroporation and reversible electroporation. (13) The method of embodiment 10, wherein the size of the visual representation of the ablation lesion correlates with the size of the lesion. (14) The method of embodiment 1, wherein the regression performed includes preclinical work relating the ablation parameters to the lesion depth and the lesion width. (15) The method of embodiment 1, further comprising validating the regression preclinical work performed relating the ablation parameters to at least one of known lesion depth and width.

[0148] (16) A system for determining an ablation lesion zone (width or depth) projected on an electroanatomical map, the system comprising: an ablation catheter; at least one sensor operatively associated with the ablation catheter and communicatively coupled via hardware including at least one processor; a monitor communicatively coupled to a controller that operates the ablation catheter and the at least one sensor; a memory device for storing information representing a contact force when applied to the biological tissue by the at least two electrodes and a number of times energy is delivered; a controller for calculating one or more zones of electroporation based on the magnitude of the contact force and the number of times energy is delivered; The monitor projects the determined one or more ablation zones onto an electroanatomical map. (17) The system of embodiment 16, wherein the processor performs multiparameter regression from predetermined preclinical data. (18) The system of embodiment 16, wherein the processor performs single-parameter regression from predetermined preclinical data. (19) The system of embodiment 16, wherein the projecting provides a viewer of the map with a visual representation of the ablation lesion, including lesion width, lesion depth, and cardiac tissue within the zone of electroporation. (20) The system described in embodiment 19, wherein the projecting further includes color coding the ablation lesion.

[0149] (21) The system of embodiment 19, wherein the size of the visual representation of the ablation lesion correlates with the size of the lesion. (22) The system of embodiment 16, wherein the regression performed includes preclinical work relating the ablation parameters to the lesion depth and the lesion width.

Claims

1. 1. A system for determining an ablation lesion zone (width or depth) projected onto an electroanatomical map, the system comprising: an ablation catheter; at least one sensor operatively associated with the ablation catheter and communicatively coupled via hardware including at least one processor; a monitor communicatively coupled to a controller that operates the ablation catheter and the at least one sensor; a memory device for storing information representing a contact force when applied to the biological tissue by the at least two electrodes and a number of times energy is delivered; a controller for calculating one or more zones of electroporation based on the magnitude of the contact force and the number of times energy is delivered; The monitor projects the determined one or more ablation zones onto an electroanatomical map.

2. The system of claim 1 , wherein the processor performs multi-parameter regression from predetermined preclinical data.

3. The system of claim 1 , wherein the processor performs a single parameter regression from predetermined preclinical data.

4. 10. The system of claim 1, wherein the projecting provides a viewer of the map with a visual representation of the ablation lesion, including lesion width, lesion depth, and cardiac tissue within the zone of electroporation.

5. The system of claim 4 , wherein the projecting further comprises color coding the ablation lesion.

6. The system of claim 4 , wherein the size of the visual representation of the ablation lesion correlates with the size of the lesion.

7. The system of claim 1 , wherein the regression performed includes preclinical work relating the ablation parameters to the lesion depth and the lesion width.

8. 1. A method for determining an ablation lesion zone (width or depth) projected onto an electroanatomical map, the method comprising: delivering pulsed energy between at least two electrodes in contact with the biological tissue; storing a magnitude of a contact force when applied by the at least two electrodes to the biological tissue; calculating one or more ablation zones from the delivering step based on the magnitude of the contact force; and projecting the one or more ablation zones onto an electroanatomical map.

9. The ablation zone comprises a depth or width of the ablated region, the depth or width being: V=Vm-(Vm-V0) ＊ exp(-(b0 ＊ log(n) ＊ x) is calculated from 9. The method of claim 8, wherein V is the depth or width of the lesion, x is the measured contact force, n is the number of ablation applications applied by the electrode, V is the maximum value of V (of the depth or the width) of a possible lesion, V is an initial value of the depth or the width of the lesion, and b is a parameter selectable via a lookup table based on the number n.

10. The method of claim 8 , wherein determining the ablation comprises multi-parameter regression.

11. The method of claim 8 , wherein determining the ablation comprises single parameter regression.

12. The method of claim 8 , wherein the electroporation comprises irreversible electroporation.

13. The method of claim 8 , wherein the electroanatomical map comprises a three-dimensional representation of the heart on a display screen.

14. The method of claim 8 , further comprising presenting information about the ablation lesion.

15. The method of claim 8 , wherein the ablation application parameters include tissue wall thickness, nearby tissue type, and myocardial fiber orientation.

16. The method of claim 15 , wherein the nearby tissue types include at least cardiac muscle and smooth muscle.

17. 10. The method of claim 8, wherein the projecting provides a viewer of the map with a visual representation of the ablation lesion, including lesion width, lesion depth, and cardiac tissue within the zone of electroporation.

18. The method of claim 17 , wherein the projecting further comprises color coding the ablation lesions.

19. 20. The method of claim 18, wherein the color coding indicates at least one of irreversible electroporation and reversible electroporation.

20. 18. The method of claim 17, wherein the size of the visual representation of the ablation lesion correlates with the size of the lesion.

21. The method of claim 8 , wherein the regression performed includes pre-clinical work relating the ablation parameters to the lesion depth and the lesion width.

22. 10. The method of claim 8, further comprising validating the regression preclinical work performed relating the ablation parameters to at least one of known lesion depth and width.

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