Patent Description:
Use of minimally invasive procedures, such as catheter ablation, to treat a variety of heart conditions, such as supraventricular and ventricular arrhythmias, is becoming increasingly more prevalent. Such procedures involve the mapping of electrical activity in the heart (e.g., based on cardiac signals), such as at various locations on the endocardium surface ("cardiac mapping"), to identify the site of origin of the arrhythmia followed by a targeted ablation of the site. To perform such cardiac mapping a catheter with one or more electrodes can be inserted into the patient's heart chamber.

Conventional three-dimensional (3D) mapping techniques include contact mapping and non-contact mapping, and may employ a combination of contact and non-contact mapping. In both techniques, one or more catheters are advanced into the heart. With some catheters, once in the chamber, the catheter may be deployed to assume a 3D shape. In contact mapping, physiological signals resulting from the electrical activity of the heart are acquired with one or more electrodes located at the catheter distal tip after determining that the tip is in stable and steady contact with the endocardium surface of a particular heart chamber. In non-contact-based mapping systems, using the signals detected by the non-contact electrodes and information on chamber anatomy and relative electrode location, the system provides physiological information regarding the endocardium of the heart chamber. Location and electrical activity is usually measured sequentially on a point-by-point basis at about <NUM> to <NUM> points on the internal surface of the heart to construct an electro-anatomical depiction of the heart. The generated map may then serve as the basis for deciding on a therapeutic course of action, for example, tissue ablation, to alter the propagation of the heart's electrical activity and to restore normal heart rhythm.

In many conventional mapping systems, the clinician visually inspects or examines the captured electrograms (EGMs), which increases examination time and cost. During an automatic electro-anatomical mapping process, however, approximately <NUM>,<NUM> to <NUM>,<NUM> intracardiac electrograms (EGMs) may be captured, which does not lend itself to being manually inspected in full by a clinician (e.g., a physician) for a diagnostic assessment, EGM categorization, and/or the like. Typically mapping systems extract scalar values from each EGM to construct voltage, activation, or other map types to depict overall patterns of activity within the heart. While maps typically are generated for entire heart chambers, much of the clinical focus is often placed on specific, smaller, regions such as, for example, isthmi, scars, lines of block, and/or the like. User-driven focus is typically poorly facilitated by mapping systems, and context-preserving methods largely rely on mental imaging, which is heavily operator-dependent. Additionally, context-lossy methods typically are not well tolerated by users and often result in procedural nuisance and delay. Futhermore, data-driven (algorithm-supported) focus is largely absent from conventional mapping systems.

Document <CIT> discloses a non-contact cardiac mapping method that includes: (i) inserting a catheter into a heart cavity having an endocardium surface, the catheter including multiple, spatially distributed electrodes; (ii) measuring signals at the catheter electrodes in response to electrical activity in the heart cavity with the catheter spaced from the endocardium surface; and (iii) determining physiological information at multiple locations of the endocardium surface based on the measured signals and positions of the electrodes with respect to the endocardium surface.

While multiple embodiments are disclosed, still other embodiments of the presently disclosed subject matter will become apparent to those skilled in the art from the following detailed description, which shows and describes illustrative embodiments of the disclosed subject matter.

While the disclosed subject matter is amenable to various modifications and alternative forms, specific embodiments have been shown by way of example in the drawings and are described in detail below. The intention, however, is not to limit the disclosure to the particular embodiments described. On the contrary, the disclosure is intended to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.

As the terms are used herein with respect to measurements (e.g., dimensions, characteristics, attributes, components, etc.), and ranges thereof, of tangible things (e.g., products, inventory, etc.) and/or intangible things (e.g., data, electronic representations of currency, accounts, information, portions of things (e.g., percentages, fractions), calculations, data models, dynamic system models, algorithms, parameters, etc.), "about" and "approximately" may be used, interchangeably, to refer to a measurement that includes the stated measurement and that also includes any measurements that are reasonably close to the stated measurement, but that may differ by a reasonably small amount such as will be understood, and readily ascertained, by individuals having ordinary skill in the relevant arts to be attributable to measurement error; differences in measurement and/or manufacturing equipment calibration; human error in reading and/or setting measurements; adjustments made to optimize performance and/or structural parameters in view of other measurements (e.g., measurements associated with other things); particular implementation scenarios; imprecise adjustment and/or manipulation of things, settings, and/or measurements by a person, a computing device, and/or a machine; system tolerances; control loops; machine-learning; foreseeable variations (e.g., statistically insignificant variations, chaotic variations, system and/or model instabilities, etc.); preferences; and/or the like.

Although the term "block" may be used herein to connote different elements illustratively employed, the term should not be interpreted as implying any requirement of, or particular order among or between, various blocks disclosed herein. Similarly, although illustrative methods may be represented by one or more drawings (e.g., flow diagrams, communication flows, etc.), the drawings should not be interpreted as implying any requirement of, or particular order among or between, various steps disclosed herein. However, certain embodiments may require certain steps and/or certain orders between certain steps, as may be explicitly described herein and/or as may be understood from the nature of the steps themselves (e.g., the performance of some steps may depend on the outcome of a previous step). Additionally, a "set," "subset," or "group" of items (e.g., inputs, algorithms, data values, etc.) may include one or more items, and, similarly, a subset or subgroup of items may include one or more items. A "plurality" means more than one.

As used herein, the term "based on" is not meant to be restrictive, but rather indicates that a determination, identification, prediction, calculation, and/or the like, is performed by using, at least, the term following "based on" as an input. For example, predicting an outcome based on a particular piece of information may additionally, or alternatively, base the same determination on another piece of information.

Embodiments of systems and methods described herein facilitate processing sensed cardiac electrical signals to present a representation of a region of interest (ROI) on an electroanatomical map. In embodiments, representations of ROIs may facilitate clear visual distinction of the ROI while preserving the context of the annotations. Representations of ROIs may include highlighting effects applied to a map that are persistent, tolerant to view angles, tolerant to various zoom levels, and do not obstruct other information in the map. In embodiments, for example, a representation of an ROI may include a bordered, highlighted overlay of a corresponding portion of the surface of the map on top of a de-saturated map. In embodiments, rendering representations of ROIs with borders may facilitate clearly presenting multiple distinct ROIs (which may, in embodiments, be referred to as multiple portions of an ROI). Embodiments of the highlighting operations described herein may be user driven and/or algorithm driven.

According to embodiments, to perform aspects of embodiments of the methods described herein, cardiac electrical signals may be obtained from a mapping catheter (e.g., associated with a mapping system), a recording system, a coronary sinus (CS) catheter or other reference catheter, an ablation catheter, a memory device (e.g., a local memory, a cloud server, etc.), a communication component, a medical device (e.g., an implantable medical device, an external medical device, a telemetry device, etc.), and/or the like.

As the term is used herein, a sensed cardiac electrical signal may refer to one or more sensed signals. Each cardiac electrical signal may include a number of intracardiac electrograms (EGMs) sensed within a patient's heart, and may include any number of features that may be ascertained by aspects of the system <NUM>. Examples of cardiac electrical signal features include, but are not limited to, activation times, activations, activation waveforms, filtered activation waveforms, minimum voltage values, maximum voltages values, maximum negative time-derivatives of voltages, instantaneous potentials, voltage amplitudes, dominant frequencies, peak-to-peak voltages, and/or the like. A cardiac electrical signal feature may refer to one or more features extracted from one or more cardiac electrical signals, derived from one or more features that are extracted from one or more cardiac electrical signals, and/or the like. Additionally, a representation, on a cardiac and/or a surface map, of a cardiac electrical signal feature may represent one or more cardiac electrical signal features, an interpolation of a number of cardiac electrical signal features, and/or the like.

Each cardiac signal also may be associated with a set of respective position coordinates that corresponds to the location at which the cardiac electrical signal was sensed. Each of the respective position coordinates for the sensed cardiac signals may include three-dimensional Cartesian coordinates, polar coordinates, and/or the like. In embodiments, other coordinate systems can be used. In embodiments, an arbitrary origin is used and the respective position coordinates refer to positions in space relative to the arbitrary origin. Since, in embodiments, the cardiac signals may be sensed on the cardiac surfaces, the respective position coordinates may be on the endocardial surface, epicardial surface, in the mid-myocardium of the patient's heart, and/or in the vicinity of one of one of these.

<FIG> shows a schematic diagram of an exemplary embodiment of a cardiac mapping system <NUM>. As indicated above, embodiments of the subject matter disclosed herein may be implemented in a mapping system (e.g., the mapping system <NUM>), while other embodiments may be implemented in an ablation system, a recording system, a computer analysis system, and/or the like. The mapping system <NUM> includes a moveable catheter <NUM> having multiple spatially distributed electrodes. During a signal-acquisition stage of a cardiac mapping procedure, the catheter <NUM> is displaced to multiple locations within the heart chamber into which the catheter <NUM> is inserted. In some embodiments the distal end of the catheter <NUM> is fitted with multiple electrodes spread somewhat uniformly over the catheter. For example, the electrodes may be mounted on the catheter <NUM> following a 3D olive shape, a basket shape, and/or the like. The electrodes are mounted on a device capable of deploying the electrodes into the desired shape while inside the heart, and retracting the electrodes when the catheter is removed from the heart. To allow deployment into a 3D shape in the heart, electrodes may be mounted on a balloon, shape memory material such as Nitinol, actuable hinged structure, and/or the like. According to embodiments, the catheter <NUM> may be a mapping catheter, an ablation catheter, a diagnostic catheter, a CS catheter, and/or the like. For example, aspects of embodiments of the catheter <NUM>, the electrical signals obtained using the catheter <NUM>, and subsequent processing of the electrical signals, as described herein, may also be applicable in implementations having a recording system, ablation system, and/or any other system having a catheter with electrodes that may be configured to obtain cardiac electrical signals.

At each of the locations to which the catheter <NUM> is moved, the catheter's multiple electrodes acquire signals resulting from the electrical activity in the heart. Consequently, reconstructing and presenting to a user (such as a doctor and/or technician) physiological data pertaining to the heart's electrical activity may be based on information acquired at multiple locations, thereby providing a more accurate and faithful reconstruction of physiological behavior of the endocardium surface. The acquisition of signals at multiple catheter locations in the heart chamber enables the catheter to effectively act as a "mega-catheter" whose effective number of electrodes and electrode span is proportional to the product of the number of locations in which signal acquisition is performed and the number of electrodes the catheter has.

To enhance the quality of the reconstructed physiological information at the endocardium surface, in some embodiments the catheter <NUM> is moved to more than three locations (for example, more than <NUM>, <NUM>, or even <NUM> locations) within the heart chamber. Further, the spatial range over which the catheter is moved may be larger than one third (<NUM>/<NUM>) of the diameter of the heart cavity (for example, larger than <NUM>%, <NUM>%, <NUM>% or even <NUM>% of the diameter of the heart cavity). Additionally, in some embodiments the reconstructed physiological information is computed based on signals measured over several heart beats, either at a single catheter location within the heart chamber or over several locations. In circumstances where the reconstructed physiological information is based on multiple measurements over several heart beats, the measurements may be synchronized with one another so that the measurement are performed at approximately the same phase of the heart cycle. The signal measurements over multiple beats may be synchronized based on features detected from physiological data such as surface electrocardiograms (ECGs) and/or intracardiac electrograms (EGMs).

The cardiac mapping system <NUM> further includes a processing unit <NUM> which performs several of the operations pertaining to the mapping procedure, including the reconstruction procedure to determine the physiological information at the endocardium surface (e.g., as described above) and/or within a heart chamber. The processing unit <NUM> also may perform a catheter registration procedure. The processing unit <NUM> also may generate a 3D grid used to aggregate the information captured by the catheter <NUM> and to facilitate display of portions of that information.

The location of the catheter <NUM> inserted into the heart chamber can be determined using a conventional sensing and tracking system <NUM> that provides the 3D spatial coordinates of the catheter and/or its multiple electrodes with respect to the catheter's coordinate system as established by the sensing and tracking system. These 3D spatial locations may be used in building the 3D grid. Embodiments of the system <NUM> may use a hybrid location technology that combines impedance location with magnetic location technology. This combination may enable the system <NUM> to accurately track catheters that are connected to the system <NUM>. Magnetic location technology uses magnetic fields generated by a localization generator positioned under the patient table to track catheters with magnetic sensors. Impedance location technology may be used to track catheters that may not be equipped with a magnetic location sensor, and may utilize surface ECG patches.

In embodiments, to perform a mapping procedure and reconstruct physiological information on the endocardium surface, the processing unit <NUM> may align the coordinate system of the catheter <NUM> with the endocardium surface's coordinate system. The processing unit <NUM> (or some other processing component of the system <NUM>) may determine a coordinate system transformation function that transforms the 3D spatial coordinates of the catheter's locations into coordinates expressed in terms of the endocardium surface's coordinate system, and/or vice-versa. In embodiments, such a transformation may not be necessary, as embodiments of the 3D grid described herein may be used to capture contact and non-contact EGMs, and select mapping values based on statistical distributions associated with nodes of the 3D grid. The processing unit <NUM> also may perform post-processing operations on the physiological information to extract and display useful features of the information to the operator of the system <NUM> and/or other persons (e.g., a physician).

According to embodiments, the signals acquired by the multiple electrodes of catheter <NUM> are passed to the processing unit <NUM> via an electrical module <NUM>, which may include, for example, a signal conditioning component. The electrical module <NUM> may be configured to receive the signals communicated from the catheter <NUM> and perform signal enhancement operations on the signals before they are forwarded to the processing unit <NUM>. The electrical module <NUM> may include signal conditioning hardware, software, and/or firmware that may be used to amplify, filter and/or sample intracardiac potential measured by one or more electrodes. The intracardiac signals typically have a maximum amplitude of 60mV, with a mean of a few millivolts.

In some embodiments the signals are bandpass filtered in a frequency range (e.g., <NUM>-<NUM>) and sampled with analog to digital converters (e.g., with <NUM>-bit resolution at <NUM>). To avoid interference with electrical equipment in the room, the signal may be filtered to remove the frequency corresponding to the power supply (e.g., <NUM>). Other types of signal processing operations such as spectral equalization, automatic gain control, etc. may also take place. For example, in embodiments, the intracardiac signals may be unipolar signals, measured relative to a reference (which may be a virtual reference) such as, for example, a coronary sinus catheter or Wilson's Central Terminal (WCT), from which the signal processing operations may compute differences to generate multipolar signals (e.g., bipolar signals, tripolar signals, etc.). The signals may be otherwise processed (e.g., filtered, sampled, etc.) before and/or after generating the multipolar signals. The resultant processed signals are forwarded by the module <NUM> to the processing unit <NUM> for further processing.

In embodiments, the processing unit <NUM> may be configured to process the resultant processed signals. In embodiments, because the processing unit <NUM> may be configured to process any number of different types of electrical signals, whether they have been preprocessed or not, the terms "electrical signal(s)," "cardiac electrical signal(s)" and terms including one or more of the aforementioned, shall be understood to refer to electrical signals, processed (e.g., "pre-processed") electrical signals, raw signal data, interpolated electrical signals, estimated electrical signals, and/or any other type of information representing an electrical signal, as described herein.

Embodiments of the processing unit <NUM> may be configured to receive a number of electrical signals such as, for example, cardiac electrical signals. The processing unit <NUM> may receive the electrical signals from the electrical module <NUM>, from a memory device, from a catheter (e.g., the catheter <NUM>), from another computing device, from a user via a user input device, and/or the like. In embodiments, the processing unit <NUM> may receive an indication of a measurement location corresponding to each electrical signal. The processing unit <NUM> may be configured to generate, based on the electrical signals, a cardiac map, which may be presented via a display device <NUM>. In embodiments, the cardiac map includes a number of annotations representing a number of cardiac signal features, which may include, for example, one or more activation times, minimum voltage values, maximum voltage values, maximum negative time-derivatives of voltage, instantaneous potentials, voltage amplitudes, dominant frequencies, and/or peak-to-peak voltages.

The processing unit <NUM> may be further configured to determine, from the cardiac signal features, a set of interesting cardiac signal features. According to embodiments, an "interesting" cardiac signal feature is a cardiac signal feature that has been designated as such, such as, for example, via user input, an automatic algorithm, and/or the like. The processing unit <NUM> may also be configured to determine, based on the set of interesting cardiac signal features, a region of interest (ROI). In embodiments, an ROI refers to a set of information that is designated as interesting, and may, in embodiments be determined based on another set of information designated as interesting. That is, for example, the processing unit <NUM> may be configured to determine (e.g., based on user input, an algorithm, etc.) a set of interesting electrical signal features (e.g., a set of information that is designated as interesting) and, based on the set of interesting signal features, a region of interest (e.g., another set of information that is designated as interesting). In embodiments, a region of interest may refer to a set of mapped data points such as, for example, a set of data points that are mapped, using a mesh, to an electroanatomical shell surface (e.g., a cardiac model). A region of interest may include the set of interesting cardiac signal features, information associated with the set of interesting cardiac signal features, and/or the like.

According to embodiments, the processing unit <NUM> may be configured to facilitate display, via a display device <NUM>, of the cardiac map and a representation of the region of interest. The representation of the region of interest may include, for example, a first display parameter value that is different from a second display parameter value. In embodiments, the display parameter may include any number of different types of parameters, settings, and/or the like that may be configured to change one or more features of an appearance of a displayed representation. For example, in embodiments, display parameters may include brightness, contrast, color saturation, sharpness, and/or the like. Thus, in embodiments, the representation of the region of interest may include a first color saturation value that is different from a second color saturation value, where the second color saturation value is associated with at least one cardiac signal feature that is not included within the region of interest. Color saturation values, relative color saturation values, and/or the like, may be adjustable via user input, an algorithm, and/or the like.

As further shown in <FIG>, the cardiac mapping system <NUM> also may include peripheral devices such as a printer <NUM> and/or display device <NUM>, both of which may be interconnected to the processing unit <NUM>. Additionally, the mapping system <NUM> includes storage device <NUM> that may be used to store data acquired by the various interconnected modules, including the volumetric images, raw data measured by electrodes and/or the resultant endocardium representation computed therefrom, the partially computed transformations used to expedite the mapping procedures, the reconstructed physiological information corresponding to the endocardium surface, and/or the like.

In embodiments, the processing unit <NUM> may be configured to automatically improve the accuracy of its algorithms by using one or more artificial intelligence (i.e., machine-learning) techniques, classifiers, and/or the like. In embodiments, for example, the processing unit may use one or more supervised and/or unsupervised techniques such as, for example, support vector machines (SVMs), k-nearest neighbor techniques, artificial neural networks, and/or the like. In embodiments, classifiers may be trained and/or adapted using feedback information from a user, other metrics, and/or the like.

The illustrative cardiac mapping system <NUM> shown in <FIG> is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the present disclosure. Neither should the illustrative cardiac mapping system <NUM> be interpreted as having any dependency or requirement related to any single component or combination of components illustrated therein. Additionally, various components depicted in <FIG> may be, in embodiments, integrated with various ones of the other components depicted therein (and/or components not illustrated), all of which are considered to be within the ambit of the subject matter disclosed herein. For example, the electrical module <NUM> may be integrated with the processing unit <NUM>. Additionally, or alternatively, aspects of embodiments of the cardiac mapping system <NUM> may be implemented in a computer analysis system configured to receive cardiac electrical signals and/or other information from a memory device (e.g., a cloud server, a mapping system memory, etc.), and perform aspects of embodiments of the methods described herein for processing cardiac information (e.g., determining annotation waveforms, etc.). That is, for example, a computer analysis system may include a processing unit <NUM>, but not a mapping catheter.

<FIG> is a block diagram of an illustrative processing unit <NUM>, in accordance with embodiments of the disclosure. The processing unit <NUM> may be, be similar to, include, or be included in the processing unit <NUM> depicted in <FIG>. As shown in <FIG>, the processing unit <NUM> may be implemented on a computing device that includes a processor <NUM> and a memory <NUM>. Although the processing unit <NUM> is referred to herein in the singular, the processing unit <NUM> may be implemented in multiple instances (e.g., as a server cluster), distributed across multiple computing devices, instantiated within multiple virtual machines, and/or the like. One or more components for facilitating cardiac mapping may be stored in the memory <NUM>. In embodiments, the processor <NUM> may be configured to instantiate the one or more components to generate one or more electrical signal features <NUM> and a cardiac map <NUM>, either of which may be stored in the memory <NUM>.

As is further depicted in <FIG>, the processing unit <NUM> may include an acceptor <NUM> configured to receive electrical signals. The acceptor <NUM> may be configured to receive electrical signals from a mapping catheter (e.g., the mapping catheter <NUM> depicted in <FIG>), a memory device (e.g., the memory <NUM>), a server, and/or the like. The measured electrical signals may include a number of intracardiac electrograms (EGMs) sensed within a patient's heart. The acceptor <NUM> may also receive an indication of a measurement location corresponding to each of the electrical signals. In embodiments, the acceptor <NUM> may be configured to determine whether to accept the electrical signals that have been received. The acceptor <NUM> may utilize any number of different components and/or techniques to determine which electrical signals or beats to accept, such as filtering, beat matching, morphology analysis, positional information (e.g., catheter motion), respiration gating, and/or the like.

The accepted electrical signals are received by a feature extractor <NUM> that is configured to extract at least one electrical signal feature from each of the electrical signals. In embodiments, an extracted electrical signal feature may be used to annotate a cardiac map, in which case, the extracted electrical signal feature may be referred to, interchangeably, as an annotation feature. In embodiments in which the electrical signal is a cardiac electrical signal, an extracted signal feature may be referred to, interchangeably, as a cardiac electrical signal feature. In embodiments, the at least one electrical signal feature includes at least one value corresponding to at least one annotation metric. The at least one feature may include at least one event, where the at least one event includes the at least one value corresponding to the at least one metric and/or at least one corresponding time (a corresponding time does not necessarily exist for each annotation feature). According to embodiments, the at least one electrical signal feature may include, for example, an activation time, detected activation (e.g., a component of an activation waveform), activation waveform, activation histogram, minimum voltage value, maximum voltage value, maximum negative time-derivative of voltage, an instantaneous potential, a voltage amplitude, a dominant frequency, a peak-to-peak voltage, an activation duration, an annotation waveform (e.g., an activation waveform), and/or the like. A cardiac electrical signal feature may refer to one or more features extracted from one or more cardiac electrical signals, derived from one or more features that are extracted from one or more cardiac electrical signals, and/or the like. Additionally, a representation, on a cardiac and/or a surface map, of a cardiac electrical signal feature may represent one or more cardiac electrical signal features, an interpolation of a number of cardiac electrical signal features, and/or the like.

According to embodiments, feature extractor <NUM> may be configured to detect specified events (e.g., activations) and to generate an annotation waveform (a type of electrical signal feature <NUM>), which may be, for example, an activation waveform. An annotation waveform is a set of annotation waveform values and may include, for example, a set of discrete activation annotation values (e.g., a set of annotation waveform values, a set of time annotations, etc.), a function defining an annotation waveform curve, and/or the like. Accordingly, in embodiments, the term "annotation waveform" may include a "filtered annotation waveform. " An activation waveform is a set of activation waveform values and may include, for example, a set of discrete activation waveform values (e.g., a set of activation waveform values, a set of activation time annotations, etc.), a function defining an activation waveform curve, and/or the like. Accordingly, in embodiments, the term "activation waveform" may include a "filtered activation waveform.

According to embodiments, the feature extractor <NUM> may be, include, be similar to, or be included in, aspects of embodiments of the annotation waveform generator described in<CIT>, entitled "ANNOTATION WAVEFORM;" <CIT>, entitled "ELECTROANATOMICAL MAPPING TOOLS FACILITATED BY ACTIVATION WAVEFORMS;" and/or<CIT>, entitled "ANNOTATION HISTOGRAM;". In embodiments, the feature extractor <NUM> may be configured to generate an annotation histogram (another type of electrical signal feature <NUM>) having a number of bins within which annotations from electrograms (EGMs) are included. The feature extractor <NUM> may be configured to aggregate a set of annotation features by including each of the features and/or EGMs in a histogram. For example, the feature extractor <NUM> may be configured to aggregate the set of activation features by assigning a confidence level to each event corresponding to an activation feature; determining a weighted confidence level associated with each event; and including the weighted confidence levels in a histogram. According to embodiments, the feature extractor <NUM> may be, include, be similar to, or be included in, aspects of embodiments of the histogram generator described in <CIT>, entitled "ANNOTATION WAVEFORM;" <CIT>, entitled "ELECTROANATOMICAL MAPPING TOOLS FACILITATED BY ACTIVATION WAVEFORMS;" and/or<CIT>, entitled "ANNOTATION HISTOGRAM;".

As shown in <FIG>, the processing unit <NUM> includes a region of interest (ROI) component <NUM>. According to embodiments, the ROI component <NUM> is configured to determine a set of interesting cardiac signal features. According to embodiments, an "interesting" cardiac signal feature is a cardiac signal feature that has been designated as such, such as, for example, via user input, an automatic algorithm, and/or the like. In embodiments, for example, in embodiments, a user (e.g., a clinician) interacts with a graphical user interface (GUI) via a user input device to select a set of interesting cardiac signal features. In embodiments, the GUI may facilitate selection of one or more cardiac signal features, cardiac signal feature ranges, and/or the like, via interaction with a GUI. For example, in embodiments, a the GUI may include interactive representations of sliders, buttons, knobs, and/or the like, that enable user selection of various electrical signal features, device parameters, physiological parameters, environmental parameters, and/or the like. In embodiments, the GUI may allow the user to interact with the cardiac map directly (e.g., by utilizing a cursor to select points and/or regions of the map, hover over points and/or regions of the map, etc.) to facilitate identification of a set of interesting electrical signal features (and, thus, a region of interest). The processing unit <NUM> may be configured to determine a set of interesting electrical signal features based on the user interaction with the GUI.

In embodiments, the processing unit <NUM> may be configured to automatically determine a set of interesting electrical signal features such as, for example, by classifying electrical signal features as interesting based on one or more classification criteria. According to the invention, the classification criteria are user selectable and may be adjustable. In examples that are not part of the claimed invention, the criteria may be automatically selected and/or adjusted by the processing unit <NUM> in response to an indirectly related user input (e.g., a user input that facilitates display and/or adjustment of corresponding annotations. The set of interesting electrical signal features may be determined programmatically, to facilitate any number of different types of map functionality.

According to the invention, the ROI component <NUM> is configured to determine, based on the set of interesting cardiac signal features, an ROI. In embodiments, for example, the ROI includes the set of interesting cardiac signal features and/or the mapped information corresponding thereto. In embodiments, for example, the ROI component <NUM> may be configured to determine, for each cardiac signal feature of the set of cardiac signal features, a radius of influence. A radius of influence of an electrical signal feature is a metric (e.g., a scalar value, a vector, a combination of scalar values and/or vectors, etc.) that represents a spatial region within which the electrical signal feature has an effect and/or is likely to have an effect. For example, in embodiments, the radius of influence of a cardiac electrical signal feature may be a distance along the surface of the anatomical shell (e.g., a cardiac model) for which the cardiac signal feature has physiological significance - that is, for example, the radius of influence of a feature may correspond to a portion of the surface of the cardiac map that is annotated based at least in part on the feature.

In embodiments, the ROI component <NUM> may determine the radius of influence of an electrical signal feature in any number of ways such as, for example, to obtain (e.g. from a mapping engine) an indication of the portion of the cardiac map that was annotated at least partially based on the electrical signal feature. In embodiments, the ROI component <NUM> may determine the radius of influence of an electrical signal feature by determining a likelihood (e.g., probability) that the electrical signal feature (and/or other electrical signal features associated with the corresponding electrical signal) would have an influence (e.g., by contributing to a portion of operation of the heart, by contributing to an arrhythmia, by contributing to a signal measured within a certain distance, and/or the like. In embodiments, the radius of influence may refer to a surface distance (e.g., a cumulative distance along the contour of the surface of the map, rather than a Euclidean distance such as, e.g., the length of the radius of an imaginary sphere around the point) of a map.

According to embodiments, the ROI component <NUM> may be configured to determine the region of interest based on the determined radius of influence for each cardiac signal feature. That is, for example, the ROI component <NUM> may connect the map portions corresponding to the electrical signal features of the set of interesting electrical signal features to form the ROI. In embodiments, the ROI may be a continuous two-dimensional portion of the map, multiple disconnected two-dimensional portions of the map, and/or the like. In embodiments, an algorithm (e.g., aspects of embodiments of the methods described herein for vertex-based highlight generation, pixel-based highlight generation, etc.) may be configured to connect highlighted map portions (e.g., map portions corresponding to radii of influence) to form larger regions (e.g., ROIs, portions of ROls, etc.). The algorithm may be configured to determine whether to connect the larger portions, which portions corresponding to radii of influence to connect, and/or the like. In embodiments, the ROI component <NUM> may be configured to perform interpolation such that, for example, two areas that are within some specified distance of one another may be connected (e.g., assuming one or more criteria are satisfied such as, e.g., there are no uninteresting points - data points that are to be left unhighlighted - between the two regions).

Additionally, the processing unit <NUM> includes a mapping engine <NUM> that is configured to facilitate presentation of a map <NUM> corresponding to a cardiac surface based on the electrical signals. In embodiments, the map <NUM> may include a voltage map, an activation map, a fractionation map, velocity map, confidence map, and/or the like. In embodiments, the mapping engine <NUM> may be, include, be similar to, be included within, and/or be otherwise integrated with the ROI component <NUM>. In embodiments, the mapping engine <NUM> may be configured to facilitate display, via the display device, of the cardiac map and a representation of the region of interest. As shown, for example, a representation of a region of interest may include a first color saturation value that is different from a second color saturation value, where the second color saturation value is associated with at least one cardiac signal feature that is not included within the region of interest. In embodiments, more than one representation of a region of interest may be presented on the map.

In embodiments, a representation of a region of interest is presented as a highlighted area of a map. Mesh pixels (pixels associated with a mesh that is used to generate the map) within the highlighted regions may appear to have a lighting effect that distinguishes them from the mesh pixels that are not within the highlighted regions, while preserving all of the information presented on the map (e.g., the annotation colors, hues, brightness, and other attributes associated with a region of interest are preserved when the region is highlighted because only the relative saturation level is adjusted - e.g., as opposed to dimming the map, adjusting transparency, etc.). In embodiments, to present the representation of a region of interest, portions of the map that are not within the region of interest may be de-saturated (e.g., displayed with a lower saturation value than the saturation value with which those areas were displayed prior to presenting the representation), while portions of the map within the region of interest may be oversaturated or at least displayed with a saturation value that exceeds the saturation value with which the regions were displayed prior to presenting the representation of the region of interest. In embodiments, an amount of saturation of a highlighted area is greater than the amount of saturation of a non-highlighted area. According to embodiments, the saturation of highlighted areas and/or non-highlighted areas may be selected, controlled, and/or otherwise influenced (e.g., controlled within certain allowed parameters) by a user. An illustrative highlighting operation is depicted in <FIG>.

<FIG> depicts an illustrative screenshot from an interactive graphical user interface (GUI) presented using a display device associated with a cardiac mapping system, showing an illustrative cardiac map <NUM>, in accordance with embodiments of the subject matter disclosed herein. According to embodiments, the cardiac mapping system may be, be similar to, include similar features as, include, or be included within the mapping system <NUM> depicted in <FIG>. In embodiments, the GUI may be configured to present only one view of the cardiac map <NUM> at a time. In embodiments, the GUI may be configured to present, simultaneously, sequentially, and/or alternatively, any number of different views of any number of cardiac maps. In embodiments, for example, the GUI may be configured to present a first cardiac map having annotations representing activations and a second cardiac map having annotations representing electrical potential, current density, and/or the like.

As shown in <FIG>, the cardiac map <NUM> includes an anatomical shell <NUM> and annotations <NUM> displayed on the anatomical shell <NUM>. In embodiments, the map may be an activation map, on which activation locations are indicated by raised bumps <NUM>. In embodiments, raised bumps <NUM> (or other displayed features) may be used to indicate any number of different metrics, values, events, and/or the like. In embodiments, annotations (e.g., electrical signal features, quantities corresponding to - e.g., derived from - electrical signal features) may be represented using colors <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM>. Although six distinct colors are discussed herein, any number of colors may be used for such representations. In embodiments, in addition to, or in lieu of, colors, other representations may be used to represent activations such as, for example, textures, location markers, curves, vectors, and/or the like. In embodiments, the raised bumps <NUM> may be configured to represent a location associated with an acquired electrical signal (e.g., an EGM), a virtual location associated with an aggregation of acquired electrical signals, and/or the like. In embodiments, the GUI may also include a legend (not shown) configured to indicate the values represented by the annotation colors <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM>.

Embodiments facilitate presenting, on a cardiac map, a representation of a region of interest (ROI) by highlighting a corresponding portion of the cardiac map. <FIG> an illustrative screenshot from an interactive GUI, showing another view of the cardiac map <NUM> depicted in <FIG>, in accordance with embodiments of the subject matter disclosed herein. According to embodiments, the cardiac map <NUM> may be, or include, one or more selectable GUI elements such that, for example, a user can move a cursor over a portion of the cardiac map <NUM> and select the portion of the cardiac map <NUM> to which the cursor points, for example, by pressing a mouse button, tapping a touchscreen, and/or the like.

According to embodiments, for example, the GUI may be configured to receive, from a user input device, a selection of a region of the cardiac map <NUM>. The user input device used to make the selection may include a mouse, a touchscreen and/or the like, that is used to manipulate a selection tool that is provided on the GUI provided by the display device. The selection tool may include, for example, a brush, a cursor for enclosing the selected region by drawing a freeform shape around the region, an expandable polygon selection tool, a virtual probe, and/or the like, and may be, in embodiments, selected from a number of optional selection tools. In embodiments, the selection tool may have an adjustable size, behavior and/or other characteristics thereof. In this manner, for example, a user may select a desired selection tool and a size thereof. Selecting a region of the map <NUM> may include, for example, circling the region of the map using a mouse or touchscreen device to manipulate a cursor, brushing over the region of the map using an input device to manipulate a brush, and/or the like. According to embodiments, one or more portions of a map may be interactive such that a user may position a mouse cursor over a portion of the map, and interact with that portion (e.g., by clicking a right mouse button) to reveal additional information and/or functionality.

In embodiments, in response to receiving an indication of the user selection of a portion of the cardiac map <NUM>, the processing unit may cause a corresponding region (referred to herein as the "selected region") of the map <NUM> to be highlighted. Similarly, the GUI may include one or more selectable elements separate from the cardiac map <NUM> (e.g., selectable waveforms, histograms, EGMs, parameters, etc.) that may be selected using a user input device to cause the processing unit to highlight a corresponding portion <NUM> of the map <NUM>. In embodiments, information corresponding to the user selection may be, include, or be included in a region of interest (ROI), and the highlighted portion <NUM> of the map <NUM> may be, include, or be included in a representation of the ROI.

According to embodiments, for example, a user may interact with a mouse, and may manipulate the mouse to move a mouse cursor over a portion of the map. When the user presses and holds a mouse button, the processing unit may determine a ray extending from the location of the point of the mouse cursor to the mesh, e.g., in a direction that is normal to the mesh (or in a direction associated with movement of the mouse cursor, etc.). The processing unit may be configured to determine a location (e.g., a mesh element) at which the ray intersects the mesh, and may be configured to determine one or more pixels associated with the mesh element. The one or more pixels may be highlighted as a representation of a region of interest (ROI). In embodiments, the user may expand the region of interest by moving the mouse cursor, while holding down the mouse button, causing the process to additively generate a larger ROI.

The representation <NUM> of the ROI may be configured to emphasize the portion of the map <NUM> corresponding to the ROI. In embodiments, for example, the representation <NUM> of ROI may be distinguished from adjacent regions of the map <NUM> by being highlighted. That is, for example, the representation <NUM> of the ROI may be a highlighting of the corresponding portion of the map (e.g., by presenting the representations of the electrical signal features in the representation <NUM> using a color saturation different than the color saturation of other portions of the map <NUM>). In embodiments, as shown in <FIG>, the representation <NUM> of the ROI may include a border <NUM> outlining the region. The border <NUM> may presented in a color that is different than one or more of the colors used to annotate the map <NUM> (e.g., a color different than any color used in any pixel or group of pixels of a certain size disposed adjacent the border). For example, in embodiments, the border <NUM> may be white. The border <NUM> may be configured to help delineate the representation <NUM> of the ROI, create the feel of a discrete region, and/or assist in situations where some display devices and/or lighting conditions make the highlighting itself more difficult for a user to see. In embodiments, individual electrical signal features and/or locations may be indicated using representations <NUM> such as "Xs," raised bumps, and/or the like.

The illustrative processing unit <NUM> shown in <FIG> and the illustrative cardiac maps <NUM> are not intended to suggest any limitation as to the scope of use or functionality of embodiments of the present disclosure. Neither should the illustrative processing unit <NUM> and/or the cardiac map <NUM> be interpreted as having any dependency or requirement related to any single component or combination of components illustrated therein. Additionally, any one or more of the components and/or features depicted in <FIG>, <FIG> may be, in embodiments, integrated with various ones of the other components and/or features depicted therein (and/or components not illustrated), all of which are considered to be within the ambit of the subject matter disclosed herein. For example, the acceptor <NUM> may be integrated with the feature extractor <NUM>, the ROI component <NUM>, and/or the mapping engine <NUM>. In embodiments, the processing unit <NUM> may not include an acceptor <NUM>, while in other embodiments, the acceptor <NUM> may be configured to receive electrical signals from a memory device, a communication component, and/or the like.

Additionally, the processing unit <NUM> may (alone and/or in combination with other components of the system <NUM> depicted in <FIG>, and/or other components not illustrated) perform any number of different functions and/or processes associated with cardiac mapping (e.g., triggering, blanking, field mapping, etc.) such as, for example, those described in <CIT>, entitled "ELECTROANATOMICAL MAPPING;" <CIT>, entitled "ELECTROANATOMICAL MAPPING;" <CIT>, entitled "CATHETER TRACKING AND ENDOCARDIUM REPRESENTATION GENERATION;" <CIT>, entitled "ESTIMATING THE PREVALENCE OF ACTIVATION PATTERNS IN DATA SEGMENTS DURING ELECTROPHYSIOLOGY MAPPING;" <CIT>, entitled "SYSTEMS AND METHODS FOR GUIDING MOVABLE ELECTRODE ELEMENTS WITHIN MULTIPLE-ELECTRODE STRUCTURE;" <CIT>, entitled "CARDIAC MAPPING AND ABLATION SYSTEMS;" <CIT>, entitled "SYSTEMS AND PROCESSES FOR REFINING A REGISTERED MAP OF A BODY CAVITY;".

According to embodiments, various components of the mapping system <NUM>, illustrated in <FIG>, and/or the processing unit <NUM>, illustrated in <FIG>, may be implemented on one or more computing devices. A computing device may include any type of computing device suitable for implementing embodiments of the disclosure. Examples of computing devices include specialized computing devices or general-purpose computing devices such "workstations," "servers," "laptops," "desktops," "tablet computers," "hand-held devices," "general-purpose graphics processing units (GPGPUs)," and the like, all of which are contemplated within the scope of <FIG> and <FIG> with reference to various components of the system <NUM> and/or processing unit <NUM>.

In embodiments, a computing device includes a bus that, directly and/or indirectly, couples the following devices: a processor, a memory, an input/output (I/O) port, an I/O component, and a power supply. Any number of additional components, different components, and/or combinations of components may also be included in the computing device. The bus represents what may be one or more busses (such as, for example, an address bus, data bus, or combination thereof). Similarly, in embodiments, the computing device may include a number of processors, a number of memory components, a number of I/O ports, a number of I/O components, and/or a number of power supplies. Additionally any number of these components, or combinations thereof, may be distributed and/or duplicated across a number of computing devices.

In embodiments, memory (e.g., the storage device <NUM> depicted in <FIG>, and/or the memory <NUM> depicted in <FIG>) includes computer-readable media in the form of volatile and/or nonvolatile memory and may be removable, nonremovable, or a combination thereof. Media examples include Random Access Memory (RAM); Read Only Memory (ROM); Electronically Erasable Programmable Read Only Memory (EEPROM); flash memory; optical or holographic media; magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices; data transmissions; and/or any other medium that can be used to store information and can be accessed by a computing device such as, for example, quantum state memory, and/or the like. In embodiments, the memory <NUM> and/or <NUM> stores computer-executable instructions for causing a processor (e.g., the processing unit <NUM> depicted in <FIG> and/or the processor <NUM> depicted in <FIG>) to implement aspects of embodiments of system components discussed herein and/or to perform aspects of embodiments of methods and procedures discussed herein.

Computer-executable instructions may include, for example, computer code, machine-useable instructions, and the like such as, for example, program components capable of being executed by one or more processors associated with a computing device. Examples of such program components include the electrical signal feature <NUM>, the map <NUM>, the acceptor <NUM>, the feature extractor <NUM>, the ROI component <NUM>, and/or the mapping engine <NUM>. Program components may be programmed using any number of different programming environments, including various languages, development kits, frameworks, and/or the like. Some or all of the functionality contemplated herein may also, or alternatively, be implemented in hardware and/or firmware.

<FIG> is a flow diagram of an illustrative process <NUM> for automated electro-anatomical mapping, in accordance with embodiments of the disclosure. Aspects of embodiments of the method <NUM> may be performed, for example, by a processing unit (e.g., the processing unit <NUM> depicted in <FIG>, and/or the processing unit <NUM> depicted in <FIG>). A data stream <NUM> containing multiple signals is first input into the system (e.g., the cardiac mapping system <NUM> depicted in <FIG>). During the automated electro-anatomical mapping process, a data stream <NUM> provides a collection of physiological and non-physiological signals that serve as inputs to the mapping process. The signals may be collected directly by the mapping system, and/or obtained from another system using an analog or digital interface. The data stream <NUM> may include signals such as unipolar and/or bipolar intracardiac electrograms (EGMs), surface electrocardiograms (ECGs), electrode location information originating from one or more of a variety of methodologies (magnetic, impedance, ultrasound, real time MRI, etc.), tissue proximity information, catheter force and/or contact information obtained from one or more of a variety of methodologies (force spring sensing, piezo-electric sensing, optical sensing etc.), catheter tip and/or tissue temperature, acoustic information, catheter electrical coupling information, catheter deployment shape information, electrode properties, respiration phase, blood pressure, other physiological information, and/or the like.

For the generation of specific types of maps, one or more signals may be used as one or more references, during a triggering/alignment process <NUM>, to trigger and align the data stream <NUM> relative to the cardiac, other biological cycle and/or an asynchronous system clock resulting in beat datasets. Additionally, for each incoming beat dataset, a number of beat metrics are computed during a beat metric determination process <NUM>. Beat metrics may be computed using information from a single signal, spanning multiple signals within the same beat and/or from signals spanning multiple beats. The beat metrics provide multiple types of information on the quality of the specific beat dataset and/or likelihood that the beat data is good for inclusion in the map dataset. A beat acceptance process <NUM> aggregates the criteria and determines which beat datasets will make up the map dataset <NUM>. The map dataset <NUM> may be stored in association with a 3D grid that is dynamically generated during data acquisition.

Surface geometry data may be generated concurrently during the same data acquisition process using identical and/or different triggering and/or beat acceptance metrics employing a surface geometry construction process <NUM>. This process constructs surface geometry using data such as electrode locations and catheter shape contained in the data stream. Additionally, or alternatively, previously collected surface geometry <NUM> may be used as an input to surface geometry data <NUM>. Such geometry may have been collected previously in the same procedure using a different map dataset, and/or using a different modality such as CT, MRI, ultrasound, rotational angiography, and/or the like, and registered to the catheter locating system. The system performs a source selection process <NUM>, in which it selects the source of the surface geometry data and provides surface geometry data <NUM> to a surface map generation process <NUM>. The surface map generation process <NUM> is employed to generate surface map data <NUM> from the map dataset <NUM> and surface geometry data <NUM>.

The surface geometry construction algorithm generates the anatomical surface on which the electroanatomical map is displayed. Surface geometry can be constructed, for example, using aspects of a system as described <CIT>; and/or <CIT>.

Additionally, or alternatively, an anatomical shell can be constructed by the processing unit by fitting a surface on electrode locations that are determined either by the user or automatically to be on the surface of the chamber. In addition, a surface can be fit on the outermost electrode and/or catheter locations within the chamber.

As described, the map dataset <NUM> from which the surface is constructed can employ identical or different beat acceptance criteria from those used for electrical and other types of maps. The map dataset <NUM> for surface geometry construction can be collected concurrently with electrical data or separately. Surface geometry can be represented as a mesh containing a collection of vertices (points) and the connectivity between them (e.g. triangles). Alternatively, surface geometry can be represented by different functions such as higher order meshes, non-uniform rational basis splines (NURBS), and/or curvilinear shapes.

The generation process <NUM> generates surface map data <NUM>. The surface map data <NUM> may provide information on cardiac electrical excitation, cardiac motion, tissue proximity information, tissue impedance information, force information, and/or any other collected information desirable to the clinician. The combination of map dataset <NUM> and surface geometry data <NUM> allows for surface map generation. The surface map is a collection of values or waveforms (e.g., EGMs) on the surface of the chamber of interest, whereas the map dataset can contain data that is not on the cardiac surface. One approach for processing the map dataset <NUM> and surface geometry data <NUM> to obtain a surface map dataset <NUM> is described in <CIT>.

Alternatively, or in combination with the method above, an algorithm that applies acceptance criteria to individual electrodes can be employed. For example, electrode locations exceeding a set distance (e.g., <NUM>) from surface geometry can be rejected. Another algorithm can incorporate tissue proximity information using impedance for inclusion in the surface map data. In this case only electrode location whose proximity value is less than <NUM> might be included. Additional metrics of the underlying data can also be used for this purpose. For example, EGM properties similar to beat metrics can be assessed on a per electrode basis. In this case metrics such as far field overlap and/or EGM consistency can be used. It should be understood that variations on the method to project points from the map dataset <NUM> to the surface and/or to select appropriate points can exist.

Once obtained, the surface map data <NUM> may be further processed to annotate desired features from the underlying data, a process defined as surface map annotation <NUM>. Once data is collected into surface map data <NUM>, attributes relating to the collected data may be automatically presented to the user. These attributes can be automatically determined and applied to the data by the computer system and are referred to herein as annotations. Exemplary annotations include activation time, the presence of double activation or fractionation, voltage amplitude, spectral content, and/or the like. Due to the abundance of data available in automated mapping (e.g., mapping completed by the computer system with minimal human input related to the incoming data), it is not practical for the operator to review and annotate data manually. However, human input can be a valuable addition to the data, and so when user input is provided it is necessary for the computer system to automatically propagate and apply it to more than one data point at a time.

It may be possible to use the computer system to automatically annotate activation time, voltage, and other characteristics of individual EGMs. Activation time detection may use methods similar to those previously described to detect a trigger and can similarly benefit from the use of blanking and powered triggering operator. Desired annotations may include instantaneous potential, activation time, voltage amplitude, dominant frequency and/or other properties of the signal. Once computed, the annotations may be displayed superimposed on chamber geometry. In embodiments, a gap-filling surface map interpolation may be employed <NUM>. For example, in embodiments, a gap-filling interpolation may be employed where a distance between a point on the surface to a measured EGM exceeds a threshold, as this may indicate, for example, that grid-based interpolation, as described herein, may not be as effective in that situation. Displayed maps <NUM> can be computed and displayed separately, and/or overlaid on top of each other.

The illustrative method <NUM> shown in <FIG> is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the present disclosure. Neither should the illustrative method <NUM> be interpreted as having any dependency nor requirement related to any single aspect or combination of aspects illustrated therein. Additionally, any one or more of the aspects depicted in <FIG> may be, in embodiments, integrated with various ones of the other aspects depicted therein (and/or components not illustrated), all of which are considered to be within the ambit of the present disclosure.

<FIG> is a flow diagram depicting an illustrative method <NUM> of processing electrophysiological information, in accordance with embodiments of the disclosure. Aspects of embodiments of the method <NUM> may be performed, for example, by a processing unit (e.g., the processing unit <NUM> depicted in <FIG>, and/or the processing unit <NUM> depicted in <FIG>). Embodiments of the method <NUM> include receiving a plurality of electrical signals (block <NUM>). The electrical signals may be received from a catheter, a memory device, a computing device, and/or the like. The catheter may be any catheter having one or more electrodes configured to obtain electrical signals (e.g., the mapping catheter <NUM> depicted in <FIG>, a CS catheter, an ablation catheter, etc.). The processing unit also may receive an indication of a measurement location corresponding to each of the electrical signals. As explained above, with respect to <FIG>, the processing unit and/or other components (e.g., the electrical module <NUM> depicted in <FIG>) may be configured to determine whether to accept particular electrical signals (e.g., beats) based on one or more beat acceptance criteria.

According to embodiments, cardiac electric signal features may be extracted from the cardiac electrical signals (e.g., EGMs). Examples of features of the cardiac electrical signals include, but are not limited to, activation times, minimum voltage values, maximum voltages values, maximum negative time-derivatives of voltages, instantaneous potentials, voltage amplitudes, dominant frequencies, peak-to-peak voltages, and/or the like. Each of the respective points at which a cardiac electrical signal is sensed may have a corresponding set of three-dimensional position coordinates. For example, the position coordinates of the points may be represented in Cartesian coordinates. Other coordinate systems can be used, as well. In embodiments, an arbitrary origin is used and the respective position coordinates are defined with respect to the arbitrary origin. In some embodiments, the points have non-uniform spacing, while in other embodiments, the points have uniform spacing. In embodiments, the point corresponding to each sensed cardiac electrical signal may be located on the endocardial surface of the heart and/or below the endocardial surface of the heart.

As shown in <FIG>, embodiments of the method <NUM> include determining a set of interesting cardiac electrical signal features (block <NUM>). The set of interesting cardiac electrical signal features may be determined, e.g., via user input and/or an automatic algorithm. Embodiments of the method <NUM> include determining a radius of influence corresponding to each cardiac electrical signal feature of the set of interesting cardiac electrical signal features (block <NUM>); and determining a region of interest (ROI) based on the set of interesting cardiac electrical signals and the corresponding radii of influence (block <NUM>). Embodiments of the method <NUM> further include facilitating presentation of an electroanatomical map on a display device (block <NUM>) and facilitating presentation, on the map, of a representation of the ROI (block <NUM>).

In embodiments, a cardiac map may be generated and/or annotated based, at least in part, on the cardiac electrical signal features and/or the activation waveform (which may also be a cardiac electrical signal feature). In embodiments, the cardiac map may also be generated and/or annotated, at least in part, using any number of other signals, techniques, and/or the like. For example, embodiments may utilize impedance mapping techniques to generate and/or annotate one or more portions of the cardiac map such as, for example, an anatomical shell upon which electrical signal features are represented. In embodiments, a surface may be fitted on one or more of the points associated with the cardiac electrical signals to generate a shell representing the endocardial surface of the one or more cardiac structures. In embodiments, a surface may also be fitted on one or more of the points associated with the cardiac electrical signals to generate a shell representing an epicardium surface or other excitable cardiac tissue. In embodiments, one or more of the cardiac electrical signal features at the corresponding points can be included on the shell to generate a cardiac map of the one or more cardiac structures. For example, embodiments may include displaying annotations on the cardiac map that represent features, extracted from the cardiac electrical signals and/or derived from other features, such as, for example, activation times, minimum voltage values, maximum voltages values, maximum negative time-derivatives of voltages, instantaneous potentials, voltage amplitudes, dominant frequencies, peak-to-peak voltages, and/or the like.

Cardiac electrical signal features may be represented on the cardiac map and may be, or include, any features extracted from one or more corresponding sensed cardiac electrical signals and/or derived from one or more of such features. For example, a cardiac electrical signal feature may be represented by a color, such that if the cardiac electrical signal feature has an amplitude or other value within a first range then the cardiac electrical signal feature may be represented by a first color, whereas if the cardiac electrical signal feature has an amplitude or other value that is within a second range that is different than the first range, the cardiac electrical may be represented by a second color. As another example, the cardiac electrical signal feature may be represented by a number (e.g., a. <NUM> mV sensed cardiac electrical signal feature can be represented by a. <NUM> at its respective position on the surface map). Examples of a cardiac electrical signal feature that can be represented at the first surface point include, but are not limited to, an activation, an activation time, an activation duration, an activation waveform, a filtered activation waveform, an activation waveform characteristic, a filtered activation waveform characteristic, a minimum voltage value, a maximum voltages value, a maximum negative time-derivative of voltage, an instantaneous potential, a voltage amplitude, a dominant frequency, a peak-to-peak voltage, and/or the like.

In embodiments, other features such as, for example, non-electrical signal features, non-cardiac electrical signal features, and/or the like, can be represented on an anatomical map at respective locations. Examples of non-electrical signal features include, but are not limited to, features derived from magnetic resonance imaging, a computerized tomography scan, ultrasonic imaging, and/or the like.

According to embodiments, a GUI used for presenting the map may include any number of different input tools for manipulating the map. For example, the GUI may include a play/pause button, a tool configured to facilitate manual selection of the histogram bin or bins, tools configured to facilitate manual adjustment of parameters (e.g., signal baseline definitions, thresholds, EGM characteristics, filters, etc.), and/or the like. In embodiments, for example, the GUI may include a selection tool that can facilitate refining selections of highlighted EGMs, select particular EGMs and/or activations, and/or the like.

<FIG> is a flow diagram depicting an illustrative method <NUM> of facilitating presentation of cardiac information, in accordance with embodiments of the subject matter disclosed herein. Aspects of embodiments of the method <NUM> may be performed, for example, by a processing unit (e.g., the processing unit <NUM> depicted in <FIG>, and/or the processing unit <NUM> depicted in <FIG>). <FIG> is a conceptual schematic diagram depicting an illustrative ROI highlighting operation, as described in embodiments of the method <NUM> depicted in <FIG>, in accordance with embodiments of the subject matter disclosed herein. Embodiments of the method <NUM> include determining, from a plurality of cardiac electrical signal features extracted from a plurality of cardiac electrical signals, a set of interesting cardiac electrical signal features (block <NUM>); and determining a radius of influence of each interesting cardiac electrical signal feature (block <NUM>).

As shown in <FIG>, embodiments of the method <NUM> further include labeling each mesh vertex of a mesh element of a mesh with a first value (block <NUM>), and labeling (which may include, e.g., re-labeling) each mesh vertex of the mesh element of the mesh with a second value if a criterion is satisfied (block <NUM>). In embodiments, the method <NUM> includes facilitating display of the representation of the region of interest based on the mesh vertex labels. That is, for example, in embodiments, as shown in <FIG>, a triangular mesh <NUM> may be used for generating a cardiac map, and the first value may be <NUM>, while the second value is <NUM>. In embodiments, for example, all vertices of the mesh <NUM> may be initially labeled with a <NUM>. For each cardiac electrical feature in the set of interesting cardiac electrical features, each vertex within the feature's radius of influence may be labeled with a <NUM>. In embodiments, the subset of electrical signal features having radii of influence encompassing a vertex may be referred to as an influence subset. In embodiments, though some vertices may be labeled with a <NUM> multiple times (e.g., where the vertices fall within more than one radii of influence), those vertices may retain the label of <NUM>.

Embodiments of the method <NUM> may further include determining the number of mesh vertices of the mesh element that are labeled with the second value (block <NUM>), and apply presentation effects to the mesh based on the determined number. For example, as shown in <FIG>, embodiments of the method <NUM> may include applying a highlighting effect, but no border effect, to a mesh element if the number of mesh vertices of the mesh element that are labeled with the second value is <NUM> (block <NUM>). As shown in <FIG> and <FIG>, embodiments of the method <NUM> may include applying a border effect <NUM>, but no highlighting effect <NUM>, to the mesh element (e.g., <NUM>) if the number of mesh vertices of the mesh element that are labeled with the second value is <NUM> (block <NUM>); and applying no border effect <NUM> and no highlighting effect <NUM> to the mesh element if the number of mesh vertices of the mesh element that are labeled with the second value is less than <NUM> (block <NUM>). The resulting representation <NUM> of the ROI may be bounded within the applied border effect, which may be presented, for example, as a border, as described herein (e.g., a white border).

Embodiments of the method <NUM> described above, with reference to <FIG> and <FIG>, may result in highlighted regions that have a more "jagged" appearance, due to the finite resolution of the triangles. In embodiments, a highlighted region with a more "smooth" appearance may be generated using embodiments of other methods such as, for example, a method loosely based on the concept of metaballs. <FIG> is a flow diagram depicting an illustrative method <NUM> of facilitating presentation of cardiac information, in accordance with embodiments of the subject matter disclosed herein. <FIG> are conceptual schematic diagrams depicting aspects of an illustrative ROI highlighting operation, as described in embodiments of the method <NUM> depicted in <FIG>, in accordance with embodiments of the subject matter disclosed herein. Aspects of embodiments of the method <NUM> may be performed, for example, by a processing unit (e.g., the processing unit <NUM> depicted in <FIG>, and/or the processing unit <NUM> depicted in <FIG>).

Embodiments of the method <NUM> include determining, from a plurality of cardiac electrical signal features extracted from a plurality of cardiac electrical signals, a set of interesting cardiac electrical signal features (block <NUM>). Embodiments of the method <NUM> further include determining a radius of influence of each interesting cardiac electrical signal feature (block <NUM>). As shown, embodiments of the method <NUM> include determining a position (e.g., P, depicted in <FIG>) of each model pixel (block <NUM>) and determining, for each model pixel, an influence subset of the set of interesting cardiac electrical signal features (block <NUM>). An influence subset of the set of interesting cardiac electrical signal features may include, for example, each interesting cardiac electrical signal feature having a radius of influence that encompasses or otherwise affects a given pixel. In embodiments, for example, each electrical signal feature in the influence subset may be denoted as ei, wherein i=<NUM>,.

Embodiments of the method <NUM> further include determining, for each model pixel, an influence force, fi, associated with each cardiac electrical signal feature of the influence subset (block <NUM>). In embodiments, for example, the influence force, fi, may be a function of the electrical signal feature's position and P: fi = g(ei,P), where g is some function that is dependent upon a surface distance, surf_dist, between ei and P. For example, in embodiments, g=<NUM>/surf_dist(ei,P). Surface distance may be determined (e.g., approximated) using any number of different techniques. In embodiments, as depicted for example, in <FIG>, surface distance may be approximated by, based on normals <NUM>, <NUM>, and <NUM> to the mesh <NUM> corresponding to the positions associated with the features, ei, and P, drawing an arc <NUM> such that the slope of the arc <NUM> at the two endpoints is perpendicular to the respective normals <NUM> and <NUM>. The length of the arc <NUM> may be used as an approximation of the surface distance. In embodiments, this approximation of surface distance may be configured to be more accurate by using small radii of influence such that the curvature between the two endpoints is reduced.

According to embodiments, the method <NUM> may include determining, for each model pixel, a sum, F, of the influence forces (block <NUM>): F=sum(f(ei,P)) for each i. The method <NUM> may include comparing, for each model pixel, the sum, F, of the influence forces to a threshold, TH (block <NUM>); and applying a highlighting effect to each model pixel if the sum, F, of the influence forces exceeds the threshold, TH (block <NUM>) (F>TH); and not applying a highlighting effect if the sum, F, does not exceed the threshold, TH (block <NUM>) (F<=TH).

In embodiments, the method <NUM> may include creating a border (not shown in <FIG>, but conceptualized in <FIG>). A border may be created using any number of different techniques. According to embodiments, for example, the border may be created by generating a shape <NUM>, using the highlighted pixels <NUM>, where the shape <NUM> is expanded in size (e.g., by scaling, by a small factor, each highlighted pixel along the mesh's curvature). The shape may be rendered behind the highlighted pixels <NUM> (e.g., as a layered effect, beneath the highlighted pixels), thereby resulting in a border <NUM>. In embodiments, although the shape <NUM> and resulting border <NUM> are depicted, in <FIG>, for purposes of clarity of description, as being colored black, the shape <NUM> and resulting border <NUM> may be rendered in any number of different colors such as, for example, in white.

Claim 1:
A system (<NUM>) for facilitating display of cardiac information, the system (<NUM>) comprising:
a display device (<NUM>) configured to present a cardiac map; and
a processing unit (<NUM>, <NUM>) configured to:
receive a plurality of sensed cardiac electrical signals;
receive an indication of a measurement location corresponding to each sensed cardiac electrical signal of the plurality of sensed cardiac electrical signals;
generate, based on the plurality of sensed cardiac electrical signals, the cardiac map, the cardiac map comprising a plurality of annotations representing a plurality of cardiac signal features, the plurality of cardiac signal features comprising at least one of: an activation time, a detected activation, a minimum voltage value, a maximum voltages value, a maximum negative time-derivative of voltage, an instantaneous potential, a voltage amplitude, a dominant frequency, and a peak-to-peak voltage;
determine, from the plurality of cardiac signal features, a set of interesting cardiac signal features, the set of interesting cardiac signal features satisfying a classification criteria selected by a user;
determine, based on the set of interesting cardiac signal features, a region of interest by connecting cardiac map portions corresponding to the interesting cardiac electrical features of the set of interesting electrical signal features; and
facilitate display, via the display device (<NUM>), of the cardiac map and a representation of the region of interest, the representation of the region of interest comprising a first display parameter value that is different from a second display parameter value, wherein the second display parameter value is associated with at least one cardiac signal feature that is not included within the region of interest, the first display parameter and the second display parameter comprise at least one of: brightness, contrast, color saturation, and sharpness.