Device for processing spatiotemporal dispersion signals of cardiac electrograms

Abstract

A device for processing spatiotemporal dispersion signals of cardiac electrograms comprises a memory (4) designed to receive spatiotemporal dispersion signals of cardiac electrograms, cardiac cycle length values and voltage histogram uniformity values each associated, on the one hand, with a time marker and, on the other hand, with a cardiac electrogram trace identifier. The device comprises a monitor (6) which detects the presence of a relevant spatiotemporal dispersion signal on a trace and which, in response thereto, calls a computer (8) which calculates a first priority value from the spatiotemporal dispersion signal, a second priority value from the associated cardiac cycle length value or values, and a third priority value from the associated voltage histogram uniformity values and then draws a trace priority value from these three priority values.

Description

Description Title of the invention: Device for processing spatiotemporal dispersion signals of cardiac electrograms technical field

[0001] The invention relates to the field of signal analysis from cardiac electrograms. Technological background

[0002] The treatment of atrial fibrillation has seen significant progress in the last decade. To treat atrial fibrillation, practitioners operate by inserting catheters equipped with multiple electrodes. These electrodes are moved within the heart to measure the electrical signals that propagate through it. The signals obtained are called cardiac electrograms (ECGs). These ECGs are processed to help practitioners identify the area or areas of the heart that are causing the atrial fibrillation. Each electrode defines a "track" that corresponds to the ECG obtained from that electrode. Once these areas are identified, the practitioner cauterizes them to deactivate them, thereby restoring normal heart function and eliminating atrial fibrillation.

[0003] Most existing solutions are based on the analysis of CFAEs, or "Complex Fractionated Atrial Electrograms." The principle is to try to find locations in the atria where the electrograms lose their continuity, that is, become fractionated.

[0004] The Applicant has developed an electrogram treatment that has piqued the interest of the scientific community since the publication of very positive clinical studies. These have led to the publication of several articles, including that of Seitz et al. "AF Ablation Guided by Spatiotemporal Electrogram Dispersion Without Pulmonary Vein Isolation: A Wholly Patient-Tailored Approach", Journal of the American College of Cardiology, Volume 69, Issue 3, 24 January 2017, pages 303-321.

[0005] This treatment relies on the detection of a quantity in cardiac electrogram signals called dispersion by the Applicant. More specifically, the Applicant has discovered that measuring the spatiotemporal dispersion of cardiac electrograms—that is, based both on the temporal evolution of the cardiac electrogram signals from each electrode and also taking into account the cardiac electrogram signals from neighboring electrodes—is particularly effective in determining the areas of the heart that are the source of fi- atrial brilliance. The measurement of this quantity has been the subject of a patent granted in many countries, and published in Europe under number EP 3 236 843.

[0006] By extending its work, the Applicant integrated dispersion into a machine learning tool to determine, in near real-time, the presence of dispersion within cardiac electrograms during a procedure. This allows the practitioner to be alerted, accelerates the ablation procedure, and improves the quality of the results obtained while reducing surgical risks. Furthermore, the reliability of the procedure is increased, limiting the number of patients requiring repeat procedures for the same reasons. The patent published under number FR 3 119 537 describes an example of a machine learning tool for determining, in near real-time, the presence of dispersion within cardiac electrograms during a procedure.

[0007] This work has been integrated into software called VX1, which has received FDA (Food and Drug Administration) approval and CE marking. While not providing a diagnosis itself, VX1 assists the practitioner in making a diagnosis: based on the dispersion measurements presented in the software, the practitioner can choose to mark areas of the heart requiring catheter ablation.

[0008] In its current version, the VX1 software uses a database of annotated cardiac electrograms to train a machine learning engine that returns a value indicating the probability that an area for which a cardiac electrogram signal has been analyzed is experiencing atrial fibrillation. Therefore, this is not a measure of dispersion per se, nor information constituting a medical diagnosis, but rather an indication of the greater or lesser chance that a cardiac electrogram reflects the occurrence of atrial fibrillation. Thus, the value returned by the VX1 software is a value between 0 and 1 (0 indicating that there is only a near-zero probability that the area being measured is involved in fibrillation, and 1 indicating that this probability is near certainty).The software is configured so that a value of 0.5 is used as the threshold from which the practitioner's attention is drawn to the potential presence of a dispersion.

[0009] During the development of the VX1 software, the Applicant observed that, in some cases, numerous areas of the heart return a value greater than 0.5, complicating the practitioner's work, as they must perform as few ablations as possible. Furthermore, when too many areas of dispersion are identified, the practitioner tends to lose confidence in the software's measurement accuracy, since it returns highly noisy information. Consequently, devices and processes capable of processing dispersion signals are needed. Spatiotemporal analysis of cardiac electrograms in a way that allows for the prioritization of cardiac zones for ablation treatment would be useful.

[0010] The devices and methods for processing spatiotemporal dispersion signals from cardiac electrograms described here can help determine the priority of heart areas for ablation in various ways. For example, the devices and methods can determine priority based on one or more factors, including signal stability, cardiac activation cycle length, and a voltage map. Subsequently, at least one of the identified priority areas can be ablated using a device (e.g., an RF electrode device) to treat a cardiac arrhythmia, such as atrial fibrillation.

[0011] The spationtemporal dispersion signal processing devices described here can generally include a monitor, a memory, and a computer.For example, in some variants, the device may include a monitor configured to receive spatiotemporal dispersion signals from one or more cardiac electrograms and identify a relevant dispersion signal, a computer configured to, in response to the identification of a relevant dispersion signal by the monitor: receive the relevant dispersion signal, extract a data set from the received dispersion signal, analyze the extracted data set, determine a flatness value based on the extracted data set, determine a duration value based on the extracted data set, and calculate a track priority value based on the determined flatness and duration values, and a memory configured to store a set of instructions for the operation of the monitor and the computer.

[0012] Methods for processing spatiotemporal dispersion signals are also described in this document. With regard to signal stability, the methods may include receiving spatiotemporal dispersion data from cardiac electrograms, extracting a dataset from the dispersion data, determining a flatness value based on the extracted dataset, determining a duration value based on the extracted dataset, and calculating a track priority value based on the determined flatness and duration values. In this way, the track priority value can provide information that allows the practitioner to classify cardiac areas for ablation.

[0013] Thus, the invention proposes a device for processing spatiotemporal dispersion signals of cardiac electrograms, comprising a memory arranged to receive spatiotemporal dispersion signals of cardiac electrograms associated on the one hand with a time marker and on the other hand with a track identifier of cardiac electrogram, a calculator arranged to receive as input an electrogram track identifier and a time marker, to analyze the spatiotemporal dispersion signal of cardiac electrograms associated with this electrogram track identifier, to analyze a signal extract between the time marker and the first preceding time marker whose spatiotemporal dispersion signal value of cardiac electrograms indicates an absence of dispersion, to derive from this signal extract, on the one hand, a signal flatness value, and on the other hand, a duration value derived from the duration of the signal extract, and to return a track priority value calculated from the flatness value and the duration value, and a monitor arranged to receive the spatiotemporal dispersion signals of cardiac electrograms associated with each cardiac electrogram track, and,When the value of a spatiotemporal dispersion signal from cardiac electrograms indicates a relevant dispersion, to call the calculator with the corresponding time marker and electrogram track identifier.

[0014] The invention also relates to a device for processing spatiotemporal dispersion signals of cardiac electrograms comprising a memory arranged to receive spatiotemporal dispersion signals of cardiac electrograms, cardiac cycle length values ​​and voltage histogram uniformity values ​​each time associated on the one hand with a time marker and on the other hand with a cardiac electrogram track identifier, a computer arranged to receive as input an electrogram track identifier and a time marker, for analyzing the spatiotemporal dispersion signal of cardiac electrograms associated with this electrogram track identifier and this time marker,analyze an extract of this signal between the time marker and the first preceding time marker whose spatiotemporal dispersion signal value of cardiac electrograms indicates an absence of dispersion in order to derive on the one hand a signal flatness value, and on the other hand a duration value derived from the duration of the signal extract, and calculate a first priority value calculated from the flatness value and the duration value, the calculator being further arranged to calculate a second priority value from the cardiac cycle length value(s) associated with the electrogram track identifier and the time marker received at the input,a third priority value derived from the voltage histogram uniformity value associated with the received input electrogram track identifier and time marker, and to calculate and return a track priority value for the received input electrogram track identifier determined from the first priority value, the second priority value, and the third priority value, and a monitor arranged to receive the spatiotemporal dispersion signals of cardiac electrograms associated with each cardiac electrogram track, and, when the value of a spatiotemporal dispersion signal of cardiac electrograms indicates a relevant dispersion, to call the calculator with the corresponding time marker and electrogram track identifier.

[0015] In both variants, the device is particularly advantageous because it provides additional information beyond the dispersion value, indicating to the practitioner the priority level of the cardiac area responsible for the returned dispersion value in terms of its involvement in fibrillation. Thus, the track priority value allows the practitioner to classify cardiac areas for ablation.

[0016] Furthermore, the trail priority value tends to increase when a practitioner stops in a given area and that area contains a dispersion. Thus, the trail priority value allows the practitioner to perform their procedure more effectively: when a dispersion is detected, they know it is advisable to stop in the affected area and wait to see if the trail priority value increases. If it does not, they can be confident that it is advisable to continue their examination.

[0017] According to various embodiments, the invention may have one or more of the following characteristics: - Cardiac electrogram spatiotemporal dispersion signals are sequences of values ​​taken from electrogram signals, each indicating a degree of confidence that dispersion is occurring for the relevant electrogram track and time marker, and in which the monitor and / or calculator are arranged to determine whether a cardiac electrogram spatiotemporal dispersion signal indicates relevant dispersion by comparing the value of the cardiac electrogram spatiotemporal dispersion signal to a threshold value, - the calculator is configured to calculate the flatness value from at least one value among the standard deviation of the signal extract, the total variation of the signal extract, the entropy of the signal extract, or a value derived from one or more derivatives of order greater than or equal to one of the signal extract, - The calculator is configured to calculate the duration value by comparing the duration of the signal extract to a minimum and / or a maximum value, and returning the value 0 if the duration of the signal extract is less than the minimum value, returning the value 1 if the duration of the signal extract is greater than the maximum value, and returning a value between 0 and 1 otherwise. - The calculator is configured to determine the value between 0 and 1 by applying to the duration of the signal extract a projection function from the interval between the minimum and maximum values ​​to the interval between 0 and 1, which projection function is chosen from the group comprising the affine functions, exponential functions, polynomials, and threshold functions, - The calculator is designed to calculate the first priority value by performing a weighted harmonic, harmonic, weighted or arithmetic mean of the flatness value and the duration value, - the memory receives cardiac cycle length values ​​which include cardiac activation cycle length values ​​and overall cycle length values, and the calculator is arranged to calculate the second priority value by comparing the cardiac activation cycle length value associated with the received input electrogram track identifier and time marker to a threshold and / or by comparing the cardiac activation cycle length value and the overall cycle length value associated with the received input electrogram track identifier and time marker, - the memory is configured to receive voltage histogram uniformity values ​​obtained by performing a G-test or chi-square test between a uniform histogram and a histogram of voltage values ​​associated with a cardiac electrogram track identifier and a period of 6 to 10 seconds including the time marker to which each voltage histogram uniformity value is associated, and the calculator is configured to calculate the third priority value from the voltage histogram uniformity values ​​associated with the received electrogram track identifier and time marker and a threshold value, and - the calculator, when the first priority value, the second priority value and the third priority value are boolean values, is arranged to determine a track priority value according to the following hierarchy: 1) The first priority value, the second priority value, and the third priority value are all set to 1. 2) The first priority value and the second priority value are both 1 3) The first priority value and the third priority value are both 1 4) The second priority value and the third priority value are both 1 5) The first priority value is 1 6) the second priority value is 1 and 7) The third priority value is 1.

[0018] The invention also relates to a method comprising the following operations: a) receiving spatiotemporal dispersion signals from cardiac electrograms associated on the one hand with a time marker and on the other hand with a cardiac electrogram track, b) determining whether a value of a spatiotemporal dispersion signal from cardiac electrograms indicates dispersion, c) if operation b) is negative, repeat it with a dispersion value presenting a later time marker, d) if operation b) is positive, analyze the spatiotemporal dispersion signal of cardiac electrograms associated with the corresponding electrogram track identifier by analyzing a signal extract between the time marker and the first preceding time marker whose spatiotemporal dispersion signal value of cardiac electrograms indicates an absence of dispersion, and by deriving from this signal extract a signal flatness value and a duration value derived from the duration of the signal extract, and e) return a track priority value calculated from the flatness value and the duration value of operation d).

[0019] The invention also relates to another method for determining a priority track value of spatiotemporal dispersion signals from cardiac electrograms, comprising the following steps: a) receiving spatiotemporal dispersion signals from cardiac electrograms, cardiac cycle length values, and voltage histogram uniformity values, each associated on the one hand with a time marker and on the other hand with a cardiac electrogram track identifier; b) determining whether a value of a spatiotemporal dispersion signal from cardiac electrograms indicates dispersion; c) if step b) is negative, repeating it with a dispersion value exhibiting a subsequent time marker; d) if step b) is positive,d1) analyze the spatiotemporal dispersion signal of cardiac electrograms associated with the corresponding electrogram track identifier by analyzing a signal extract between the time marker and the first preceding time marker whose spatiotemporal dispersion signal value of cardiac electrograms indicates an absence of dispersion, and by extracting from this signal extract, on the one hand, a signal flatness value, and on the other hand, a duration value derived from the duration of the signal extract, and calculate a first priority value from the flatness value and the duration value, d2) calculate a second priority value from the cardiac cycle length value(s) associated with the electrogram track identifier and the time marker received as input,d3) calculate a third priority value from the voltage histogram uniformity value associated with the received input electrogram track identifier and time marker, and d4) calculate a track priority value for the track identifier, of electrogram received at input determined from the first priority value, the second priority value and the third priority value e) return the priority value of track of operation d).

[0020] Depending on various variations, the process may exhibit one or more of the following characteristics: - spatiotemporal dispersion signals of cardiac electrograms are sequences of values ​​taken from electrogram signals, each indicating a degree of confidence that dispersion is occurring for the electrogram track and time marker concerned, and wherein operation b) comprises comparing a value of the spatiotemporal dispersion signal of cardiac electrograms to a threshold value, - operation d) includes calculating the flatness value from at least one value among the standard deviation of the signal extract, the total variation of the signal extract, the entropy of the signal extract, or a value derived from one or more derivatives of order greater than or equal to one of the signal extract, - the dl operation) includes calculating the duration value by comparing the duration of the signal extract to a minimum and / or a maximum value, and returning the value 0 if the duration of the signal extract is less than the minimum value, returning the value 1 if the duration of the signal extract is greater than the maximum value, and returning a value between 0 and 1 otherwise, - the operation dl) includes determining the value between 0 and 1 by applying to the duration of the signal extract a projection function from the interval between the minimum and maximum values ​​to the interval between 0 and 1, which projection function being chosen from the group comprising affine functions, exponential functions, polynomials and threshold functions, and - operation e) includes calculating the track priority value by performing a weighted harmonic, harmonic, weighted or arithmetic mean of the flatness value and the duration value.

[0021] The invention also relates to a computer program comprising instructions for executing the process according to the invention, a data storage medium on which such a computer program is recorded, and a computer system comprising a processor coupled to a memory, the memory having recorded such a computer program. Brief description of the drawings

[0022] Other features and advantages of the invention will become clearer upon reading the following description, drawn from illustrative and non-limiting examples taken from the drawings shown: - Figure [1] represents a schematic diagram of a device processing spatiotemporal dispersion signals to enable the detection of cardiac areas requiring priority ablation, - [Fig.2] represents an example of the implementation of an operating loop of the device of [Fig.1], - Figure [3] represents an example of a dispersion signal processed by the device in Figure [1], with 10 distinct tracks, and

[0023] - [Fig.4] represents an example of the implementation of an interface allowing a practitioner to be informed of the detection or not of a priority track by the device of [Fig.1].

[0024] The drawings and description below contain, for the most part, elements of a definite nature. They can therefore not only serve to better explain the present invention, but also contribute to its definition, if necessary. Detailed description

[0025] Figure 1 represents a schematic example of a device 2 according to the invention. As stated in the introduction, the signals used by the device are based on cardiac electrograms measured by pairs of electrodes on a catheter in a patient's heart.

[0026] However, in the specific case of the invention, it is not these signals that are processed, but the dispersion measurement derived from them. As mentioned in the introduction, the article by Seitz et al., "AF Ablation Guided by Spatiotemporal Electrogram Dispersion Without Pulmonary Vein Isolation: A Wholly Patient-Tailored Approach," Journal of the American College of Cardiology, Volume 69, Issue 3, 24 January 2017, pages 303-321, and the patent published under number EP 3 236 843, provide a better understanding of what dispersion is, both in terms of its similarities and differences with CFAE. In general, spatiotemporal dispersion is defined as a group of electrograms, fractional or unfractionated, that exhibit inter-electrode temporal and spatial dispersion at the level of at least three adjacent bipoles, such that activation extends over the entire duration of the atrial fibrillation cycle.

[0027] Given the scope of this study and the fact that dispersion and CFAEs are quite distinct phenomena, since CFAEs are spatially inconsistent, the latter are not of major interest within the context of this invention. Indeed, as will be seen below, the invention aims generally to characterize the stability of the signal formed by the dispersion values. This same analysis would be of little or no relevance in the case of CFAEs.

[0028] Device 2 includes a memory 4, a monitor 6 and a calculator 8.

[0029] The devices described here can provide additional information from a spatiotemporal dispersion value (also called a "dispersion value") that can be useful in determining the priority level of areas of the heart exhibiting arrhythmic activity, such as atrial fibrillation, that are the source of a measured dispersion value. In other words, the devices can qualify a measured dispersion value to help a physician determine whether the area from which it originates should be ablated. As previously mentioned, the devices typically include a monitor, memory, and a calculator, and can determine priority based on one or more factors, including signal stability, cardiac cycle length, and voltage histogram uniformity.

[0030] The devices described here may or may not be coupled to a cardiac mapping catheter 10. For example, in some variants, the devices may be separate from a cardiac mapping catheter 10 but connected to it in a communicating manner. In other variants, the software used in the devices may be integrated into the cardiac mapping system. A display 12 and a user interface 14 may also be coupled to the device and / or the mapping catheter 10.

[0031] An ablation catheter can also be coupled to device 2 to provide a method of treating cardiac arrhythmia using device 2 to map the areas to be ablated, and ablating these areas, for example by means of the ablation catheter. Memory

[0032] Memory 4 is configured to receive all data from device 2, whether input or output, global or local. Memory 4 can be any type of data storage suitable for receiving digital data: hard drive, flash memory hard drive, flash memory of any kind, RAM, magnetic disk, locally distributed or cloud-based storage, etc.

[0033] In the example described here, memory 4 receives all the data pertaining to device 2, namely the programs and software instantiating monitor 6 and computer 8, the parameters and any hyperparameters of any neural networks, the weights of any neural networks, the outputs and intermediate data of any neural networks, the spatiotemporal dispersion signal data of cardiac electrograms received as input (if applicable), signal flatness and duration values, cardiac cycle length values, voltage histogram uniformity values, buffered data, and output track priority value data. The data computed by the device can be stored on any type of memory similar to memory 4, or on memory 4 itself. This data can be erased after Device 2 has performed its tasks or retained them.

[0034] As will be seen below, the signal flatness value and the duration value are two values ​​used to determine whether the signal of dispersion values ​​is associated with a cardiac area for which ablation is a priority. These values ​​are combined to produce a priority value for the stability criterion, which indicates whether the determined dispersion value is associated with a dispersion that has a significant potential to be associated with an area that is the source of atrial fibrillation. Similarly, cardiac cycle length data and / or voltage histogram uniformity data can also be used to determine a priority value for the cardiac cycle length and voltage histogram uniformity criteria, respectively. These priority values ​​can be combined to produce a track priority value when they pertain to the same track.

[0035] As in the other patent applications filed by the Applicant, the track priority value does not constitute a medical diagnosis but an indication that allows a doctor to make a decision, as blood pressure would in another context.

[0036] Monitor 6 and calculator 8 access memory 4 directly or indirectly. They can be implemented as suitable computer code running on one or more processors. "Processors" should be understood to mean any processor suitable for the calculations described below. Such a processor can be implemented in any known form, such as a microprocessor for a personal computer, laptop, tablet, or smartphone; a dedicated chip such as an FPGA or SoC; a computing resource on a grid or in the cloud; a graphics processing unit (GPU); a microcontroller; or any other form capable of providing the computing power necessary for the implementation described below. One or more of these elements can also be implemented as specialized electronic circuits such as an ASIC. A combination of processor and electronic circuits can also be considered.Processors dedicated to machine learning and the implementation of neural networks could also be considered. Monitor

[0037] Monitor 6's function is to analyze the input spatiotemporal dispersion signal data stream of cardiac electrograms and detect when a dispersion value indicates that processing is necessary. In a particular implementation, for example, when using VX1 software, a dispersion value greater than or equal to 0.5 is significant. Of course, detecting this value will depend on the values ​​of the input dispersion signal. For example, this value could be generated inversely to the VX1 software (e.g., 1 - Value from VX1), in which case a value less than or equal to 0.5 would be significant. This determination could also be made differently, based on a value derived from the derivative of the dispersion value signal, or in any other relevant way.

[0038] Due to the continuous nature of the processing by device 2, which will become clearer below, once a dispersion value has been detected by monitor 6, the detection for subsequent values ​​(but concerning the same track, of course) can be different or simplified. Thus, in the case described above, rather than comparing the current dispersion value to a threshold, monitor 6 could, for example, measure the derivative of the input dispersion value signal and consider a detection positive if the derivative is positive, and so on. In general, monitor 6 could rely on several tests to qualify the detection of a relevant dispersion value.

[0039] The role of monitor 6 is therefore "interruptive." Indeed, in the absence of a relevant dispersion value, it is pointless to calculate a track priority value, since no dispersion is detected. Conversely, as soon as a relevant dispersion value is detected, monitor 6 calls calculator 8 to calculate the track priority value. Thus, the operation of device 2 can be seen as a detection loop by monitor 6 for each track, with calculator 8 executing each time a relevant dispersion value is detected. Of course, other implementations could be considered. Calculator

[0040] Calculator 8 calculates the track priority value for a track whose dispersion value has been deemed relevant by monitor 6. As a reminder, the dispersion signal is a signal that associates a time marker with a dispersion value. This dispersion value is itself derived from an analysis of several cardiac electrogram signal values. Dispersion values ​​are updated approximately every 300 ms, based on extracts of cardiac electrogram signals lasting approximately 1.5 seconds. Alternatively, this update can occur every 100 ms, every 500 ms, or other intervals.

[0041] As we will see below, the determination of a track priority value is based on an extract of dispersion values ​​which can have a continuous duration of 1.5s, i.e. about 5 dispersion values, up to several tens of seconds, i.e. about a hundred dispersion values.

[0042] More specifically, at each operating loop, the calculator 8 analyzes a signal extract of dispersion values ​​which ends with a dispersion value that has just been determined by the monitor 6 as relevant, and which contains excluded- itively dispersion values ​​whose time markers are successive, associated with the same track, and which have been considered relevant.

[0043] It will become apparent that this extract can be obtained in many ways: - Monitor 6 can generate extracts during its operation, by adding a current dispersion value detected as relevant to a current extract if the immediately preceding dispersion value was also detected as relevant, or creating a new extract otherwise. - Calculator 8, upon receiving a dispersion value associated with a given time marker, can analyze a buffer of past dispersion values ​​and stop at the oldest value considered relevant by monitor 6, or alternatively, - Calculator 8 can retrieve a buffer of past dispersion values ​​from the time marker associated with an input received dispersion value, and properly determine an extract from this buffer that it considers relevant. Signal stability

[0044] The Applicant's work has demonstrated that the temporal continuity of relevant dispersion values ​​is all the more useful when the dispersion value signal is precise. Indeed, with a dispersion considered "noisy," one might be tempted to ignore an irrelevant dispersion value in order to obtain more data for calculating the track priority value. The Applicant's work has demonstrated that combining the signal flatness value and the duration value avoids artificially increasing the size of the extracts and yields better results.

[0045] Calculator 8 operates by performing two measurements on the extract defined above: a measurement of the signal's flatness value and a measurement of its duration value. In both cases, the aim is to determine whether the dispersion value exhibits some form of stability over time. Indeed, the Applicant's work has revealed that signals with stable dispersion values ​​are associated with priority areas for ablation in order to eliminate atrial fibrillation.

[0046] In the example described here, the signal flatness value is derived from the standard deviation of the extract data. In the Applicant's work, the standard deviation was the measure that provided the best results. Nevertheless, the Applicant identified and tested other types of measures that can also be used, such as variance, total variation of the extract, entropy of the extract, a value derived from one or more derivatives of order one or higher of the extract, range, interquartile range, or another similar measure.

[0047] In parallel, calculator 8 also determines a duration value that indicates how long the current extract is relative to a time interval, which is considered to indicate the cardiac zone associated with this dispersion. is a priority in terms of ablation. In the example described here, calculator 8 projects the duration of the extraction onto a standard interval between a minimum and a maximum duration. These two values, estimated empirically by the Applicant, indicate respectively the minimum duration an extraction must have to designate a priority cardiac zone, and the maximum duration, taking into account that the practitioner cannot afford to remain too long on each zone if they wish to perform the procedure within reasonable timeframes and minimize the operative risk.

[0048] In the example described here, calculator 8 determines the duration of the extract and projects its value onto the interval [minimum duration; maximum duration] to determine a value between 0 and 1. The projection can be of any type: linear, polynomial, exponential, threshold, etc. The aim here is to indicate, for a given extract duration, whether this duration is characteristic of a priority cardiac zone or not.

[0049] The minimum duration serves an obvious purpose as a floor value. The maximum duration has a significant operational purpose: when the first dispersion value of an extract longer than the maximum duration is detected, the output priority value will necessarily be low because the duration value will be small. As the extract grows, the associated priority value, and therefore the lane priority value, will increase with the duration value. When an operator observes that the lane priority value is no longer changing, they can determine that this is because the duration value can no longer increase, and that it is time to move the catheter.

[0050] Alternatively, calculator 8 could determine the duration value differently, independently of the range [minimum duration; maximum duration]. Also alternatively, the minimum and maximum durations could vary during the procedure or be customized for each patient.

[0051] The signal flatness value and the duration value can be determined in parallel. Alternatively, one can be calculated before the other.

[0052] The duration and flatness values ​​are constructed to be between 0 and 1. This is due to the way Calculator 8 determines the priority value from the signal flatness and duration values. Specifically, in the case of signal stability, Calculator 8 determines the priority value in the described example by performing a weighted harmonic average. Alternatively, this average can be harmonic, weighted, or arithmetic of the flatness and duration values.

[0053] In the event that the signal flatness value and the duration value are not within identical ranges, a relative rectification may be performed, or another formula may be used to calculate the priority value.

[0054] A Boolean value can also be determined from the priority value, for example by defining the value as 1 if the weighted harmonic mean is greater than 0.5 and 0 otherwise. Cardiac cycle length

[0055] Local cycle length (LCL), or cardiac activation cycle length, is the time interval between successive activations of electrical signals at a specific location during cardiac mapping procedures. Global cycle length (GCL) is calculated from the coronary sinus and corresponds to the time interval between two successive cardiac cycles. It represents the average duration of a complete atrial activity.

[0056] Several methods are known for determining LCL. The Applicant has also proposed an invention in application FR 2206690 for optimally estimating this quantity.

[0057] The Applicant's work has revealed that an LCL of less than 100 ms and / or an LCL that is 20% less than the GCL is characteristic of a cardiac region of interest.

[0058] The priority value for the cardiac cycle length criterion can be determined in two ways by Calculator 8. In the first scenario, it is a Boolean value (yes / no or 0 / 1), in which case the priority value is the result of the two tests mentioned above. In the second scenario, it is a value between 0 and 1. In this case, Calculator 8 can calculate the track priority value using the following formula: if LCL < 20% GCL, the value is V = scaling constant * (GCL - LCL) / GCL; otherwise, V = 0. The scaling constant then defines a threshold above which the track priority value is considered to indicate a priority zone. Thus, with a constant of 2.5, any priority value greater than 0.5 indicates a priority zone. Other formulas may be apparent to those skilled in the art, such as an inverse exponential function (exp ~ (GLC ~ LCLY ) or other. Voltage histogram uniformity

[0059] Retrospective analysis of the regions responsible for atrial fibrillation shows that some of them exhibit a patchy pattern in voltage on the voltage map.

[0060] Upon further study of these regions, the Applicant discovered that these patterns can be quantified by the uniformity of the mapping catheter tension histograms calculated over a time window. Uniformity is statistically tested using likelihood ratio tests such as the g-test or the chi-square test. The g-test is proportional to the Kullback-Leibler divergence (a dissimilarity metric) between a uniform histogram and the analyzed histogram. The chi-square test calculates Pearson's chi-square, that is, the sum of the root mean square deviations between a uniform histogram and the analyzed histogram. In practice, the values ​​are very close. In the first variant, only the G test is used. In the second variant, only the chi-square test is used. In the third variant, a combination of the G test and chi-square test values ​​is used. In this case, this combination can be chosen from the group comprising the minimum of these values, the maximum of these values, a harmonic mean, a weighted mean, a weighted harmonic mean, or an arithmetic mean of these values.

[0061] In all cases, the voltage histogram uniformity value resulting from one of these variants is used. The Applicant's work revealed that regions with a voltage histogram uniformity value of less than 0.05 calculated over 10 seconds are considered responsible for atrial fibrillation. Generally, the threshold can be up to 0.06 or less than 0.05, and the calculation time can be between 6 and 15 seconds.

[0062] The priority value for the voltage histogram uniformity criterion can be determined in two ways by calculator 8.

[0063] According to one variant, it is a boolean value (yes / no or 0 / 1), in which case the priority value is the result of the test mentioned above (value 1 if voltage histogram uniformity value less than 0.05 and value 0 otherwise).

[0064] According to a second variant, it is a value between 0 and 1. In this case, calculator 8 can calculate the priority value using an inverse exponential, for example, the constant being chosen to be equal to 0.05 / ln(2). This ensures that any voltage histogram uniformity value less than 0.05 will induce a priority value greater than 0.5. Calculating the track priority value

[0065] When multiple criteria are used, calculator 8 can determine a track priority value that depends on the priority value calculated for each criterion.

[0066] Where priority values ​​are Boolean, a runway priority value is determined based on the Boolean value of each criterion. The Applicant's work revealed the following runway priority hierarchy: 1) 3 criteria at 1 2) Signal stability criterion and cardiac activation cycle length at 1 3) Signal stability criterion and voltage map at 1 4) criterion: cardiac activation cycle length and tension map at 1 5) Signal stability criterion at 1 6) criterion: cardiac activation cycle length set to 1, and 7) Voltage card criterion at 1.

[0067] In cases where the priority values ​​are between 0 and 1, the calculator 8 must combine the priority values ​​into a single track priority value. One possible approach is to use a weighted average, where the weights reflect the relative importance of the three criteria. The weights should be determined based on the importance of each criterion in the overall prioritization process. For example, 0.5 x priority value (signal stability) + 0.33 x priority value (cardiac activation cycle length) + 0.17 x priority value (tension map).

[0068] Besides using a weighted average, there are other approaches to combining priority values: - Maximum score: Select the highest value among the individual criteria as the overall score for ranking - Decision tree: Use a decision tree (e.g., a set of if / else conditions) to determine priority based on the scores of the different criteria. The value of each criterion can be used as a branching condition to navigate the decision tree and arrive at the final track priority value. Process

[0069] An example of the operating loop of device 2 will now be described. In operation 200, monitor 6 is called with the current dispersion value for a given track. When monitor 6 determines that a dispersion value is relevant, operation 210 is initiated in which the extract is determined from the dispersion value's time marker in operation 200, the associated track ID, and any dispersion value signals already received for that track ID. Once the extract is determined, computer 8 can determine the flatness and duration values ​​to extract the track priority value in operation 220, and return this value in operation 230.

[0070] In an alternative embodiment, operation 220 also includes the calculation of the LCL and GCL values, and / or the voltage histogram uniformity value. In another embodiment, the LCL and GCL values ​​and / or the voltage histogram uniformity value are calculated continuously during operation 200, and operation 220 accesses these values ​​based on the time determined as relevant by operation 200.

[0071] It therefore appears that the track priority value can be linked to two criteria in addition to signal stability: heart cycle length and voltage histogram uniformity. When these additional criteria are used, operation 220 is configured to return a priority value for each criterion, namely a signal stability priority value, a heart cycle length priority value, and a voltage histogram uniformity priority value.

[0072] As described above in the section "Calculating the track priority value", Operation 230 can return, depending on the variant, the highest priority value, or a value combining the three track priority values, such as a harmonic, weighted, harmonic-weighted, or arithmetic mean of these values. Alternatively, the track priority value returned by operation 230 can also be binary information, such as "relevant track" or "irrelevant track," or the same information indicating a degree of importance.

[0073] Based on the feedback of track priority value and other clinical elements, a practitioner can then decide on a map of areas to ablate in the heart, and treat the heart with an ablation catheter to ablate these areas.

[0074] Figure 3 shows an example of spatiotemporal dispersion signals received by a 10-channel device. Figure 4 shows an image displayed on the user interface 14, providing the practitioner with the calculated track priority value. As can be seen in this figure, electrodes 7-8 and 13-14 have a priority track detection, indicated by an electrical spark symbol, while electrodes 1-2 have a relevant dispersion detection, but without a priority track detection.

[0075] It appears that, where applicable, device 2 will determine a track priority value for each track for which a dispersion value signal is received as input. This enriches the information transmitted to the practitioner, enabling them to make the diagnosis that determines whether an area associated with a given track should be ablated or not.

Claims

Claims

1. Device for processing spatiotemporal dispersion signals of cardiac electrograms comprising a memory (4) arranged to receive spatiotemporal dispersion signals of cardiac electrograms, cardiac cycle length values ​​and voltage histogram uniformity values ​​each time associated on the one hand with a time marker and on the other hand with a cardiac electrogram track identifier, a calculator (8) arranged to receive as input an electrogram track identifier and a time marker, to analyze the spatiotemporal dispersion signal of cardiac electrograms associated with this electrogram track identifier and this time marker,analyzing an extract of this signal between the time marker and the first preceding time marker whose cardiac electrogram spatiotemporal dispersion signal value indicates an absence of dispersion to derive therefrom on the one hand a signal flatness value, and on the other hand a duration value derived from the duration of the signal extract, and calculating a first priority value calculated from the flatness value and the duration value, the calculator (8) being further arranged to calculate a second priority value from the cardiac cycle length value(s) associated with the electrogram track identifier and the time marker received as input,a third priority value from the voltage histogram uniformity value associated with the input electrogram track identifier and time marker and to calculate and return a track priority value for the input electrogram track identifier determined from the first priority value, the second priority value and the third priority value, and a monitor (6) arranged to receive the cardiac electrogram spatio-temporal dispersion signals associated with each cardiac electrogram track, and, when the value of a cardiac electrogram spatio-temporal dispersion signal indicates a relevant dispersion, to call the calculator (8) with the corresponding time marker and electrogram track identifier.,

2. The device of claim 1, wherein the cardiac electrogram spatiotemporal dispersion signals are sequences of values ​​derived from electrogram signals each indicating a degree of confidence that dispersion occurs for the relevant electrogram track and time marker, and wherein the monitor (6) and / or the calculator (8) are arranged to determine whether a cardiac electrogram spatiotemporal dispersion signal indicates relevant dispersion by comparing the value of the cardiac electrogram spatiotemporal dispersion signal to a threshold value.

3. Device according to claim 1 or 2, wherein the calculator (8) is arranged to calculate the flatness value from at least one value among F standard deviation of the signal extract, the total variation of the signal extract, the entropy of the signal extract or a value taken from one or more derivatives of order greater than or equal to one of the signal extract.

4. Device according to one of the preceding claims, in which the calculator (8) is arranged to calculate the duration value by comparing the duration of the signal extract to a minimum value and / or to a maximum value, and returning the value 0 if the duration of the signal extract is less than the minimum value, returning the value 1 if the duration of the signal extract is greater than the maximum value, and returning a value between 0 and 1 otherwise.

5. Device according to claim 4, in which the calculator (8) is arranged to determine the value between 0 and 1 by applying to the duration of the signal extract a projection function of the interval between the minimum value and the maximum value towards the interval between 0 and 1, which projection function is chosen from the group comprising affine functions, exponential functions, polynomials and threshold functions.

6. Device according to one of the preceding claims, in which the calculator (8) is arranged to calculate the first priority value by performing a weighted harmonic, harmonic, weighted or arithmetic mean of the flatness value and the duration value.

7. Device according to one of the preceding claims, wherein the memory (4) receives cardiac cycle length values ​​which comprise cardiac activation cycle length values ​​and global cycle length values, and the calculator is arranged to calculate the second priority value by comparing the cardiac activation cycle length value associated with the electrogram track identifier and the time marker received as input to a threshold and / or or by comparing the cardiac activation cycle length value and the global cycle length value associated with the electrogram track identifier and time marker received as input.

8. Device according to one of the preceding claims, wherein the memory (4) is arranged to receive voltage histogram uniformity values ​​which are obtained by performing a test of the G-test or chi-square test type between a uniform histogram and a histogram of the voltage values ​​associated with a cardiac electrogram track identifier and a period of 6 to 10 seconds including the time marker with which each voltage histogram uniformity value is associated, and the calculator (8) is arranged to calculate the third priority value from the voltage histogram uniformity values ​​associated with the electrogram track identifier and the time marker received as input and a threshold value.

9. Device according to one of the preceding claims, in which the calculator (8), when the first priority value, the second priority value and the third priority value are Boolean values, to determine a track priority value according to the following hierarchy: 1) the first priority value, the second priority value and the third priority value are 1 2) the first priority value and the second priority value are 1 3) the first priority value and the third priority value are at 1 4) the second priority value and the third priority value are 1 5) the first priority value is 1 6) the second priority value is 1 and 7) the third priority value is 1.

10. A method for determining a track priority value of cardiac electrogram spatiotemporal dispersion signals comprising the following operations: a) receiving cardiac electrogram spatiotemporal dispersion signals, cardiac cycle length values ​​and voltage histogram uniformity values ​​each time associated on the one hand with a time marker and on the other hand with a cardiac electrogram track identifier, b) determining whether a value of a cardiac electrogram spatiotemporal dispersion signal indicates dispersion, c) if operation b) is negative, repeating it with a dispersion value having a later time marker, d) if operation b) is positive, dl) analyzing the cardiac electrogram spatiotemporal dispersion signal associated with the corresponding electrogram track identifier by analyzing a signal extract between the time marker and the first preceding time marker whose cardiac electrogram spatiotemporal dispersion signal value indicates an absence of dispersion, and by deriving from this signal extract on the one hand a signal flatness value, and on the other hand a duration value derived from the duration of the signal extract, and calculating a first priority value from the flatness value and the duration value,d2) calculating a second priority value from the cardiac cycle length value(s) associated with the input electrogram track identifier and time marker, d3) calculating a third priority value from the voltage histogram uniformity value associated with the input electrogram track identifier and time marker, and d4) calculating a track priority value for the input electrogram track identifier determined from the first priority value, the second priority value, and the third priority value e) returning the track priority value from operation d).,

11. The method of claim 10, wherein the cardiac electrogram spatiotemporal dispersion signals are sequences of values ​​derived from electrogram signals each indicating a degree of confidence that dispersion is occurring for the electrogram track and time marker concerned, and wherein step b) comprises comparing a value of the cardiac electrogram spatiotemporal dispersion signal to a threshold value.

12. The method of claim 10 or 11, wherein operation dl) comprises calculating the flatness value from at least one of the standard deviation of the signal extract, the total variation of the signal extract, the entropy of the signal extract, or a value derived from a or more derivatives of order greater than or equal to one of the signal extract.

13. Method according to one of claims 10 to 12, in which the operation dl) comprises calculating the duration value by comparing the duration of the signal extract to a minimum value and / or a maximum value, and returning the value 0 if the duration of the signal extract is less than the minimum value, returning the value 1 if the duration of the signal extract is greater than the maximum value, and returning a value between 0 and 1 otherwise.

14. A computer program comprising instructions for executing the method according to one of claims 10 to 13 when executed by computer.

15. Data storage medium on which the computer program according to claim 14 is recorded.

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