Device for processing spatiotemporally distributed signals of an electrocardiogram

Abstract

A device for processing spatiotemporal dispersion signals of an electrocardiogram comprises a memory (4) designed to receive the spatiotemporal dispersion signals of the electrocardiogram, cardiac cycle length values ​​and voltage histogram uniformity values, each associated with a time marker on the one hand and an electrocardiogram trace identifier on the other hand, and a monitor (6) for detecting the presence of an associated spatiotemporal dispersion signal on the trace and, in response, for calling 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, and a third priority value from the associated voltage histogram uniformity value, and derives a trace priority value from these three priority values.

Description

[Technical Field]

[0001] The present invention relates to the field of analyzing signals obtained from an electrocardiogram. [Background technology]

[0002] The field of treating atrial fibrillation has made considerable progress over the past decade. To treat atrial fibrillation, clinicians operate by inserting a catheter equipped with multiple electrodes. These electrodes travel through the heart and measure the electrical signals passing through it. The resulting signals are called electrocardiograms. These electrocardiograms are processed to help clinicians detect the areas of the heart that are the source of atrial fibrillation. Thus, each electrode defines a "trace" that corresponds to the electrocardiogram obtained from that electrode. Once these areas are identified, clinicians can inactivate them by burning them, thereby restoring normal heart function and eliminating atrial fibrillation.

[0003] Most existing solutions are based on the analysis of CFAEs, which stand for "Complex Fractionated Atrial Electrograms." The principle is to find the locations of the atria where the ECG loses continuity, i.e., splits.

[0004] Applicant has developed methods for processing electrograms that have attracted the interest of the scientific community since the publication of highly corroborating clinical studies, which have led to the publication of several papers, including the publication 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, Vol. 69, No. 3, January 24, 2017, pp. 303-321.

[0005] This process is based on the detection of a large amount of the electrocardiogram signal, which the applicant calls variance. More specifically, the applicant has discovered that measuring the spatiotemporal variance of the electrocardiogram, based both on the temporal evolution of the electrocardiogram signal at each electrode, as well as taking into account the electrocardiogram signals at adjacent electrodes, is particularly effective for determining the location of the heart from which atrial fibrillation originates. The measurement of this variable has been patented in many countries and is published in Europe under EP 3,236,843.

[0006] Applicant extends that work by incorporating variance into a machine learning tool to determine in near real time the presence or absence of variance in an electrocardiogram during a procedure, thereby alerting clinicians, speeding up the ablation procedure, and improving the quality of the results obtained while reducing surgical risk. It also increases the reliability of the procedure and reduces the number of patients who must undergo another procedure for the same cause. Patent published under number FR3119537 describes an exemplary machine learning tool that allows for near real time determination of the presence or absence of variance in an electrocardiogram during a procedure.

[0007] This work has been incorporated into software called VX1, which has received FDA ("Food and Drug Administration") clearance and CE marking. The VX1 software does not provide a diagnosis, but rather assists the clinician in making a diagnosis based on dispersion measurements presented in the software, and the clinician can choose to mark the area of ​​the heart to undergo catheter ablation.

[0008] In its current version, the VX1 software uses a database of annotated ECGs to train a machine learning engine that returns a value indicating the likelihood that the region analyzed for the ECG signal is subject to atrial fibrillation. Therefore, this is not a measure of variance in the strict sense, nor does it constitute a medical diagnosis, but rather an indication that the ECG is more or less likely to indicate the occurrence of atrial fibrillation. The value returned by the VX1 software is therefore a value between 0 and 1 (0 indicating a near-zero probability that the region being measured is subject to fibrillation, and 1 indicating that this probability is almost certain). The software is configured to use a value of 0.5 as the threshold above which the possibility of the presence of variance is brought to the clinician's attention.

[0009] During the development of the VX1 software, applicants noticed that in some cases many areas of the heart returned values ​​greater than 0.5, which complicated the clinician's task because they wanted to proceed with as few ablations as possible. Also, when too many areas of dispersion were identified, clinicians tended to lose confidence in the software's measurement quality because the software returned very noisy information. Thus, devices and methods capable of processing the spatiotemporal dispersion signals of an electrocardiogram in a way that allowed them to prioritize cardiac areas for ablation therapy would be useful. Summary of the Invention

[0010] The devices and methods described herein for processing spatiotemporally distributed electrocardiogram signals can assist in prioritizing cardiac sites for ablation in various ways. For example, the devices and methods may determine priority based on one or more of signal stability, cardiac activation cycle length, and voltage maps. At least one of the identified prioritized sites can then be ablated using a device (e.g., an RF electrode device) to treat cardiac arrhythmias, such as atrial fibrillation.

[0011] A device for processing spatiotemporal scattered signals as described herein may generally include a monitor, a memory, and a computer. For example, in some variations, the device may include a monitor configured to receive one or more electrocardiogram spatiotemporal scattered signals and identify relevant scattered signals, a computer configured to, in response to the monitor's identification of the relevant scattered signals, receive the relevant scattered signals, extract data sets from the received scattered signals, analyze the extracted data sets, determine a flatness value based on the extracted data sets, determine a duration value based on the extracted data sets, and calculate a trace priority value based on the determined flatness value and duration value, and a memory configured to store instruction sets for operation of the monitor and the computer.

[0012] Also described herein is a method for processing spatiotemporal variance signals. For signal stability, the method may include receiving spatiotemporal variance data of an electrocardiogram, extracting a data set from the variance data, determining a flatness value based on the extracted data set, determining a duration value based on the extracted data set, and calculating a trace priority value based on the determined flatness value and duration value. In this manner, the trace priority value may provide information that enables a clinician to classify cardiac sites for ablation.

[0013] The invention therefore proposes a device for processing an electrocardiogram spatiotemporal variance signal, comprising: a memory designed to receive, on the one hand, an electrocardiogram spatiotemporal variance signal associated with a time marker and, on the other hand, an electrocardiogram trace identifier; a computer designed to receive an electrocardiogram trace identifier and a time marker as input, to analyze the electrocardiogram spatiotemporal variance signal associated with this electrocardiogram trace identifier, to analyze a signal extraction between the time marker and the first preceding time marker for which the value of the electrocardiogram spatiotemporal variance signal indicates no variance, to derive from this signal extraction, on the one hand, a signal flatness value and, on the other hand, a duration value derived from the duration of the signal extraction, and to return a trace priority value calculated from the flatness value and the duration value; and a monitor designed to receive the electrocardiogram spatiotemporal variance signal associated with each electrocardiogram trace and, if the value of the electrocardiogram spatiotemporal variance signal indicates relevant variance, to call the computer with the corresponding time marker and electrocardiogram trace identifier.

[0014] The present invention also provides a device for processing an electrocardiogram spatiotemporal variance signal, comprising a memory designed to receive an electrocardiogram spatiotemporal variance signal, a cardiac cycle length value and a voltage histogram uniformity value, each associated with a time marker on the one hand and an electrocardiogram trace identifier on the other hand; and a device designed to receive an electrocardiogram trace identifier and a time marker as input, to analyze the electrocardiogram spatiotemporal variance signal associated with said electrocardiogram trace identifier and said time marker, to analyze an extraction of this signal between the time marker and a first preceding time marker for which the value of the electrocardiogram spatiotemporal variance signal indicates no variance, 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 extraction, and to calculate a first priority value calculated from the flatness value and the duration value. a computer further designed to calculate a second priority value from cardiac cycle length values ​​associated with the electrogram trace identifiers and time markers received as input, and a third priority value from voltage histogram uniformity values ​​associated with the electrogram trace identifiers and time markers received as input, and to calculate and return a trace priority value determined from the first priority value, the second priority value, and the third priority value for the electrocardiogram trace identifier received as input; and a monitor designed to receive an electrocardiogram spatiotemporal variance signal associated with each electrocardiogram trace, and to call the computer with the corresponding time marker and electrocardiogram trace identifier if the value of the electrocardiogram spatiotemporal variance signal indicates a relevant variance.

[0015] In both variations, the device is particularly advantageous because it can provide additional information about the variance values ​​that can be used to indicate to the clinician the priority of fibrillation involvement at the cardiac site from which the returned variance value originated. Thus, the trace priority value is information that allows the clinician to classify cardiac sites for ablation.

[0016] Also, the trace priority value tends to increase if the clinician stops at a given site and this is the location of variance. Thus, the trace priority value allows the clinician to perform treatment more efficiently, i.e., when variance is detected, it is known that it is wise to stop at the site in question and wait to see if the trace priority value increases. If not, it can be assured that it is better to continue searching.

[0017] According to various embodiments, the invention may have one or more of the following features: the electrocardiogram spatiotemporal variance signal is a sequence of values ​​derived from the electrocardiogram signal, each of which indicates a confidence in the fact that variance has occurred for a considered electrocardiogram trace and time marker, and the monitor and / or computer is designed to determine whether the electrocardiogram spatiotemporal variance signal indicates relevant variance by comparing the value of the electrocardiogram spatiotemporal variance signal with a threshold value; the computer is configured to calculate the flatness value from at least one of the standard deviation of the signal extraction, the total variation of the signal extraction, the entropy of the signal extraction, or a value derived from one or more first or higher order derivatives of the signal extraction; the computer is designed to calculate the duration value by comparing the duration of the signal extraction with a minimum and / or maximum value, and by returning a value of 0 if the duration of the signal extraction is less than the minimum value, a value of 1 if the duration of the signal extraction is greater than the maximum value, and a value between 0 and 1 otherwise; the computer is designed to determine a value between 0 and 1 by applying a projection function of the interval between the minimum and maximum values ​​onto the interval between 0 and 1 for the duration of the signal extraction, the projection function being selected from the group comprising affine functions, exponential functions, polynomials, and threshold functions; the computer is configured to calculate the first priority value by performing a weighted harmonic mean, harmonic mean, weighted or arithmetic mean of the flatness value and the duration value; the memory is configured to receive cardiac cycle length values ​​including cardiac activation cycle length values ​​and total cycle length values, and the computer is configured to calculate a second priority value by comparing the cardiac activation cycle length values ​​associated with the electrogram trace identifiers and time markers received as input to a threshold value and / or by comparing the cardiac activation cycle length values ​​and total cycle length values ​​associated with the electrogram trace identifiers and time markers received as input to each other; the memory is designed to receive voltage histogram uniformity values ​​obtained by performing a G-test or a chi-squared test between the uniformity histogram and a histogram of voltage values ​​associated with a 6 to 10 second period including an electrocardiogram trace identifier and a time marker with which each voltage histogram uniformity value is associated; the computer is designed to calculate a third priority value from the voltage histogram uniformity values ​​associated with the electrocardiogram trace identifier and the time marker received as input and a threshold value; and the computer, when the first priority value, the second priority value, and the third priority value are Boolean values, selects 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 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; The trace priority value is determined according to the

[0018] The present invention also provides a method for detecting a cardiogram comprising the steps of: a) receiving a spatiotemporal dispersion signal of an electrocardiogram, the signal being associated with a time marker on the one hand and with an electrocardiogram tracing on the other hand; b) determining whether the values ​​of the spatiotemporal dispersion signal of the electrocardiogram indicate dispersion; c) if operation b) is negative, repeating with a variance value having a later time marker; d) if operation b) is possible, analyzing the spatiotemporal dispersion signal of the electrocardiogram associated with the corresponding electrocardiogram trace identifier by analyzing a signal extraction between the time marker and the first preceding time marker for which the value of the spatiotemporal dispersion signal of the electrocardiogram indicates no dispersion, and by deriving from this signal extraction, on the one hand, a signal flatness value and, on the other hand, a duration value derived from the duration of the signal extraction; and e) returning a trace priority value calculated from the flatness value and duration value of operation d); The present invention relates to a method comprising:

[0019] The present invention also provides another method for determining trace priority values ​​for spatiotemporal dispersion signals of an electrocardiogram, comprising the following operations: a) receiving a spatiotemporal variance signal of an electrocardiogram, a cardiac cycle length value and a voltage histogram uniformity value each time associated with a time marker on the one hand and an electrocardiogram trace identifier on the other hand; b) determining whether the values ​​of the spatiotemporal dispersion signal of the electrocardiogram indicate dispersion; c) if operation b) is false, repeating with a variance value having a later time marker; d) If operation b) is possible, d1) analyzing the spatiotemporal variance signal of the electrocardiogram associated with the corresponding electrogram trace identifier by analyzing a signal extraction between the time marker and a first preceding time marker for which the value of the spatiotemporal variance signal of the electrocardiogram indicates no variance, and by deriving from this signal extraction, on the one hand, a signal flatness value and, on the other hand, a duration value derived from the duration of the signal extraction, and calculating a first priority value from the flatness value and the duration value; d2) calculating a second priority value from the electrogram trace identifier and cardiac cycle length value associated with the time marker received as input; d3) calculating a third priority value from the voltage histogram uniformity values ​​associated with the electrogram trace identifiers and time markers received as input; and d4) calculating a trace priority value determined from the first priority value, the second priority value, and the third priority value of the electrogram trace identifier received as input; e) returning the trace priority value of operation d); The present invention relates to a method comprising:

[0020] According to various embodiments, the method comprises the following features: the electrocardiogram spatiotemporal variance signal is a sequence of values ​​derived from the electrocardiogram signal, each of which indicates a confidence level in the fact that variance has occurred for a considered electrocardiogram trace and time marker, and operation b) comprises comparing a value of the electrocardiogram spatiotemporal variance signal with a threshold value; operation d) includes calculating the flatness value from at least one of the standard deviation of the signal extraction, the total variation of the signal extraction, the entropy of the signal extraction, or a value derived from one or more first or higher order derivatives of the signal extraction; the operation d1) comprising calculating the duration value by comparing the duration of the signal extraction with a minimum and / or a maximum value and by returning a value of 0 if the duration of the signal extraction is smaller than the minimum value, a value of 1 if the duration of the signal extraction is larger than the maximum value and a value between 0 and 1 otherwise; operation d1) comprises determining a value between 0 and 1 by applying a projection function of the interval between the minimum and maximum values ​​onto the interval between 0 and 1 for the duration of the signal extraction, the projection function being selected from the group comprising an affine function, an exponential function, a polynomial, and a threshold function; and and operation e) includes calculating the trace priority value by performing a weighted harmonic mean, a harmonic mean, a weighted or arithmetic mean of the flatness value and the duration value. may have one or more of the following:

[0021] The invention also relates to a computer program comprising instructions for carrying out the method according to the invention, a data storage medium on which such a computer program is stored, and a computer system comprising a processor coupled to a memory storing such a computer program. [Brief explanation of the drawings]

[0022] Other characteristics and advantages of the invention will become apparent from the following description, with reference to examples given by way of illustration and not of limitation, and with reference to the drawings, in which:

[0023] [Figure 1] 1 shows a schematic diagram of a device that processes spatiotemporally distributed signals to enable detection of cardiac regions requiring preferential ablation. [Figure 2] 2 illustrates an exemplary embodiment of an operating loop for the device shown in FIG. 1; [Figure 3] 2 shows an exemplary dispersed signal processed by the device shown in FIG. 1, including 10 separate traces. [Figure 4] 2 illustrates an exemplary embodiment of an interface that can inform a clinician whether a priority trace is detected by the device shown in FIG. 1 .

[0024] The drawings and the following description contain elements that are primarily of a definitive nature and, as such, may not only serve to enhance the understanding of the invention but also, where appropriate, contribute to its definition. DETAILED DESCRIPTION OF THE INVENTION

[0025] Figure 1 shows a schematic example of a device 2 according to the invention. As specified in the introduction, the signals used by the device are based on the electrocardiogram measured by a pair of electrodes on a catheter in the patient's heart.

[0026] However, in the specific case of the present invention, it is not these signals that are processed, but rather the dispersion measurements derived from the signals. As indicated 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, Vol. 69, No. 3, January 24, 2017, pp. 303-321) and the patent published under the number EP 3 236 843, allow for a better understanding of what dispersion is, both in terms of what it shares with CFAE and how it differs. In general, spatiotemporal dispersion is defined as a group of electrograms, split or unsplit, with at least three adjacent dipoles that have inter-electrode temporal and spatial dispersion, resulting in activation spanning the entire duration of the atrial fibrillation cycle.

[0027] Considering the field under consideration and the fact that dispersion and CFAE represent completely different phenomena insofar as CFAE ignores spatial aspects, the latter is not of great concern in the context of the present invention. Indeed, as will be seen below, the general purpose of the present invention is to evaluate the stability of the signal formed by the dispersion value. This same analysis makes little or no sense in the case of CFAE.

[0028] The device 2 comprises a memory 4 , a monitor 6 and a computer 8 .

[0029] The devices described herein may provide additional information from spatiotemporal variance values ​​(also referred to as "variance values") that may be useful in prioritizing cardiac regions that are sources of measured variance values ​​and exhibit arrhythmia activity, e.g., atrial fibrillation. In other words, the devices may evaluate the measured variance values ​​to assist clinicians in determining whether or not to ablate the source region. As described above, the devices may generally include a monitor, memory, and computer, and may determine priority based on one or more of signal stability, cardiac cycle length, and voltage histogram uniformity.

[0030] The devices described herein may or may not be coupled to the cardiac mapping catheter 10. For example, in some variations, the devices may be separate from but communicatively coupled to the cardiac mapping catheter 10. In other variations, the software used by the devices may be integrated into the cardiac mapping system. A display 12 and user interface 14 may also be coupled to the devices and / or the mapping catheter 10.

[0031] An ablation catheter may be coupled to device 2 to provide a method for using device 2 to treat cardiac arrhythmias, map sites to be ablated, and ablate these sites using, for example, an ablation catheter.

[0032] memory The memory 4 is designed to receive all data of the device 2, whether input or output, of a global or local nature. The memory 4 may consist of any data storage type capable of receiving digital data, i.e. hard disk, solid state drive, any form of flash memory, random access memory, magnetic disk, locally distributed or cloud-based storage, etc.

[0033] In the example described herein, memory 4 receives all data related to device 2, i.e., programs and software instantiating monitor 6 and computer 8, parameters and any hyperparameters of any neural networks, weights of any neural networks, outputs and intermediate data of any neural networks, spatiotemporal distribution signal data of electrocardiograms received as input (where appropriate), signal flatness and duration values, cardiac cycle length values, voltage histogram uniformity values, data stored in buffer memory, and output trace priority value data. Data calculated by the device may be stored in any type of memory similar to memory 4 or the latter. This data may be erased or retained after device 2 has performed its task.

[0034] As outlined below, the signal flatness value and duration value are two values ​​used to determine whether a variance signal is associated with a cardiac region for which ablation is a priority. These values ​​are summed to generate a stability criterion priority value that indicates whether the determined variance is associated with a variance that is likely associated with a region that is the source of atrial fibrillation. Similarly, cardiac cycle length data and / or voltage histogram uniformity data may be used to determine priority values ​​for the cardiac cycle length criterion and the voltage histogram uniformity criterion, respectively. These priority values ​​may be summed to generate a trace priority value when they relate to the same trace.

[0035] As in other patent applications filed by the applicant, the trace priority value is not a medical diagnosis, but rather constitutes an indicator that enables a clinician to make a decision, much like blood pressure does in other contexts.

[0036] The monitor 6 and the computer 8 directly or indirectly access the memory 4, which may be in the form of suitable computer code executed by one or more processors. By processor, any processor suitable for the calculations described below should be understood. Such a processor may be made in any known manner in the form of a personal computer, laptop, tablet or smartphone, a dedicated chip of FPGA or SoC type, a computing resource on the network or in the cloud, a cluster of graphics processing units (GPUs), a microprocessor of a microcontroller, or any other form capable of providing the computing power required to complete the processes described below. One or more of these elements may also be made in the form of specialized electronic circuits, such as ASICs. A combination of processor and electronic circuit may also be envisaged. A processor specialized for machine learning and implementations of neural networks may also be envisaged.

[0037] Monitor The function of the monitor 6 is to analyze the data stream of the spatiotemporal dispersion signal of the electrocardiogram received as input and to detect therein facts where the dispersion value indicates the need for treatment. In a particular implementation, for example, when the VX1 software is used, a dispersion value of 0.5 or greater is significant. Naturally, the detection of this value will depend on the value taken by the dispersion signal received as input. For example, it may be generated inversely to the software VX1 (e.g., a value derived from 1-VX1), in which case a value of 0.5 or less would be significant. This determination may also be performed differently, based on a value derived from the derivative of the dispersion signal, or in other related ways.

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

[0039] The role of the monitor 6 is therefore of an "interruptive" nature. Indeed, if there is no relevant variance value, there is no variance detected, and therefore it is useless to calculate a trace priority value. On the other hand, as soon as a relevant variance value is detected, the monitor 6 commands the computer 8 to calculate a trace priority value. The operation of the device 2 can therefore appear as a loop of the detection of each trace by the monitor 6, which the computer 8 executes each time a relevant variance value is detected. Naturally, other embodiments can be envisaged.

[0040] computer The role of the computer 8 is to calculate trace priority values ​​for traces whose variance values ​​are deemed relevant by the monitor 6. As a reminder, the variance signal is a signal that associates a time marker with a variance value. This variance value itself is derived from an analysis of several ECG signal values. The variance value is updated approximately every 300 milliseconds, based on an extraction of an ECG signal lasting approximately 1.5 seconds. Alternatively, this update could occur every 100 milliseconds, 500 milliseconds, etc.

[0041] As will be seen below, the determination of the trace priority value is based on the extraction of variance values ​​that can have a continuous duration of 1.5 seconds, i.e., about 5 variance values, up to several tens of seconds, i.e., about 100 variance values.

[0042] More specifically, in each operating loop, the computer 8 analyzes the signal extraction of variance values, ending with the variance value that was just determined to be relevant by the monitor 6, and including only those variance values ​​that have consecutive time markers, are associated with the same trace, and that were deemed relevant.

[0043] This extraction can be done in many ways, namely: the monitor 6 is capable of generating extracts during its operation by adding a current variance value detected as relevant to the current extract if the immediately preceding variance value is also detected as relevant, or creating a new extract otherwise; the computer 8, when it receives a variance value associated with a given time marker, can analyze a buffer of past variance values ​​and stop at the oldest value deemed relevant by the monitor 6; or the computer 8 is able to obtain a buffer of past variance values ​​from time markers associated with the variance values ​​received as input and determine in an appropriate manner from this buffer the extractions it considers relevant; It is thought that it can be obtained by

[0044] signal stability Applicant's research has shown that the time continuity of relevant variance values ​​is more useful the more accurate the variance value signal. Indeed, if the variance is considered "noisy", it may be possible to ignore irrelevant variance values ​​in order to obtain more data that will allow for the calculation of trace priority values. Applicant's research has shown that a combination of signal flatness and duration values ​​means that the size of the extraction is not artificially expanded, and better results are obtained.

[0045] The computer 8 operates by performing two measurements on the extractions defined above: a signal flatness measurement and a duration measurement. In both cases, the objective is to determine whether the variance values ​​have some form of stability over time. Indeed, applicant's research has shown that stable variance signals have been associated with preferred sites of ablation to eliminate atrial fibrillation.

[0046] In the examples described herein, the signal flatness value is derived from the standard deviation of the sampled data. In Applicant's research, standard deviation is the measure that has produced the best results. Nevertheless, Applicant has defined and tested other types of measures that may be used as well, such as variance, total variation of the sample, entropy of the sample, values ​​derived from one or more first or higher derivatives of the sample, range, interquartile range, or another similar measure.

[0047] In parallel, computer 8 also determines a duration value that allows indicating how long the current extraction is relative to the time interval that is considered to indicate that the cardiac site associated with this variance has priority for ablation. In the example described herein, computer 8 projects the duration of the extraction onto a standard interval between a minimum duration and a maximum duration. These two values, empirically estimated by the applicant, indicate, respectively, the minimum duration that an extraction must have to designate a priority cardiac site, and the maximum duration that the clinician cannot afford to spend too much time on each site if he wants to perform the procedure within a reasonable time and minimize surgical risks.

[0048] In the example described herein, computer 8 determines the duration of the sampling and projects that value over an 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. This involves indicating for a given sampling duration whether this duration is characteristic of a preferred cardiac region.

[0049] The minimum duration is clearly useful as a floor value. The maximum duration has important operational utility: when the first variance value of an extraction longer than the maximum duration is detected, the output priority value will necessarily be lower due to the lower duration value. As the extraction gets larger, the associated priority value, and therefore the trace priority value, will increase with the duration value. When the operator notices that the trace priority value is no longer moving, because the duration value cannot increase any further, he can decide that it is time to move the catheter.

[0050] Alternatively, computer 8 can determine the duration values ​​differently, independent of the range [minimum duration; maximum duration]. Alternatively, the minimum and maximum durations can be variable during treatment or customized for each patient.

[0051] The flatness and duration values ​​of the signal may be determined in parallel with each other, or alternatively, one may be calculated before the other.

[0052] The duration and flatness values ​​are designed to be between 0 and 1. This is due to the way computer 8 determines the priority value from the signal flatness and duration values. Indeed, in the case of signal stability, computer 8 determines the priority value using a weighted harmonic mean in the above example. Alternatively, this mean may be a harmonic mean, a weighted mean, or an arithmetic mean of the flatness and duration values.

[0053] If the signal flatness value and duration value are not within the same range of values, a relative adjustment may be made or a different formula may be used to calculate the priority value.

[0054] A Boolean value may be determined from the priority value, for example by setting the value to 1 if the weighted harmonic mean is greater than 0.5, and 0 otherwise.

[0055] cardiac cycle length The local cycle length (i.e., "LCL") or cardiac activation cycle length is the time interval between successive activations of an electrical signal at a specific location during a cardiac mapping procedure. The global cycle length (i.e., "GCL") is calculated from the coronary sinus and corresponds to the time interval between two successive cardiac cycles. It represents the average duration of complete atrial activation.

[0056] Several methods for determining the LCL are known, and the applicant has further proposed in application FR2206690 an invention for optimally estimating this variable.

[0057] Applicant's research has demonstrated that an LCL of less than 100 milliseconds and / or an LCL 20% lower than the GCL is characteristic of a cardiac region of interest.

[0058] The priority value for the cardiac cycle length criterion can be determined by the computer 8 in two ways. According to a first variant, it is a Boolean value (yes / no or 0 / 1), in which case the priority value is the result of the two aforementioned tests. According to a second variant, it is a value between 0 and 1. In this case, the computer 8 can calculate the trace priority value according to the following formula: if LCL<20% GCL, then the value V=scaling constant*(GCL-LCL) / GCL, otherwise V=0. The scaling constant is then used to define the threshold above which the trace priority value is considered to indicate a preferred site. Thus, if the constant is 2.5, any priority value greater than 0.5 indicates a preferred site. For example, an inverse exponential function (exp -(GLC-LCL) ) may also be apparent to those skilled in the art.

[0059] Voltage Histogram Uniformity Retrospective analysis of regions responsible for atrial fibrillation shows that some of these regions have a patchy pattern on voltage maps.

[0060] By examining these regions in more detail, the applicant discovered that these patterns can be quantified by the uniformity of the mapping catheter voltage histograms calculated over time windows. Uniformity is statistically tested using likelihood ratio tests such as the G-test or the chi-square test. The first test is proportional to the Kullback-Leibler information (a measure of dissimilarity) between the uniform histogram and the analyzed histogram. The second test calculates Pearson's chi-square, i.e., the sum of squared deviations between the uniform histogram and the analyzed histogram. Indeed, the values ​​are very similar. 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 value and the chi-square test is used. In this case, the combination may be selected from a group including the minimum of these values, the maximum of these values, the harmonic mean of these values, the weighted mean, the weighted harmonic mean, or the arithmetic mean of these values.

[0061] In all cases, the voltage histogram uniformity value resulting from one of these variations is used. Applicant's research has shown that regions where a voltage histogram uniformity value of less than 0.05 is calculated over 10 seconds are considered to be the cause of atrial fibrillation. Typically, the threshold may be up to 0.06 or less than 0.05, and the calculation time may be 6 to 15 seconds.

[0062] The priority value of the voltage histogram uniformity criterion may be determined by the computer 8 in two ways.

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

[0064] According to a second variant, it is a value between 0 and 1. In this case, the computer 8 calculates an inverse exponential function, e.g. (exp -(ダイバージェンス / 定数)), where the constant is chosen to be equal to, for example, 0.05 / In(2), which ensures that a voltage histogram uniformity value less than 0.05 will result in a priority value greater than 0.5.

[0065] Calculating trace priority values If several criteria are used, the computer 8 can determine a trace priority value that depends on the priority value calculated for each criterion.

[0066] If the priority values ​​are Boolean, then the trace priority value is determined as a function of the Boolean value of each criterion. Applicant's research has revealed the following hierarchy of trace priorities: 1) Three criteria in one 2) Signal stability criteria and cardiac activation cycle length criteria are 1 3) Signal stability criteria and voltage map criteria are 1 4) Cardiac activation cycle length criteria and voltage map criteria are 1 5) Signal stability standard is 1 6) cardiac activation cycle length criterion is 1, and 7) Voltage map reference is 1.

[0067] If the priority values ​​are between 0 and 1, the computer 8 must combine the priority values ​​into a single trace priority value. One possible approach is to use a weighted average, where the weights reflect the relative importance of the three criteria. The weighting 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 (voltage map).

[0068] In addition to using a weighted average, there are other approaches to aggregating priority values. Maximum Score: Select the maximum value from the individual criteria as the overall rating for prioritization. Decision Tree: Use a decision tree (e.g., a set of if / else conditions) to determine priority based on the scores of different criteria. The value of each criterion can be used as a branching condition to traverse the decision tree and arrive at a final trace priority value.

[0069] method An exemplary operation loop for device 2 will now be described. In operation 200, monitor 6 is called with the current variance value for a given trace. When monitor 6 determines that the variance value is relevant, it triggers operation 210 in which extraction is determined from the variance value time marker of operation 200, the associated trace identifier, and any variance value signals already received for this trace identifier. Once extraction is determined, computer 8 can determine flatness and duration values ​​and derive a trace priority value therefrom in operation 220, which it returns in operation 230.

[0070] In one variation, operation 220 also includes calculating LCL and GCL values ​​and / or voltage histogram uniformity values. In another embodiment, the LCL and GCL values ​​and / or voltage histogram uniformity values ​​are calculated continuously during operation 200, and operation 220 accesses these values ​​according to points in time determined by operation 200 to be relevant.

[0071] Thus, it is believed that the trace priority value can be tied to two criteria in addition to signal stability: cardiac cycle length and voltage histogram uniformity. If these additional criteria are used, operation 220 is designed to return a priority value for each criterion: signal stability priority value, cardiac cycle length priority value, and voltage histogram uniformity priority value.

[0072] As explained in the section "Calculating Trace Priority Values" above, operation 230 may, depending on the variant, return the highest priority value, or a value that aggregates three trace priority values, such as the harmonic mean, weighted mean, weighted harmonic mean, or arithmetic mean of these values. Further alternatively, the trace priority value returned by operation 230 may be a binary indication of the type "relevant trace" or "irrelevant trace," or the same indicating importance.

[0073] Then, based on the feedback of the trace priority values ​​and other clinical factors, the clinician can determine a map of the areas of the heart to ablate and treat the heart using an ablation catheter to ablate those areas.

[0074] Figure 3 shows an example of the spatiotemporal variance signal received in association with a 10-trace device. Figure 4 shows an image displayed on the user interface 14 that allows the clinician to receive the calculated trace priority values. As shown in this figure, electrodes 7-8 and 13-14 are subject to priority trace detection, indicated by the electrical spark symbol, while electrodes 1-2 are subject to associated variance detection but do not result in priority trace detection.

[0075] If applicable, device 2 will determine a trace priority value for each trace for which a variance value signal is received as input. This allows for enriching the information transmitted to the clinician, enabling the clinician to perform a diagnosis to determine whether or not to ablate the site associated with a given trace.

Claims

1. 1. A device for processing spatiotemporally distributed signals of an electrocardiogram, comprising: a memory (4) designed to receive the spatiotemporal dispersion signal of an electrocardiogram, the cardiac cycle length value and the voltage histogram uniformity value, each associated with a time marker on the one hand and an electrocardiogram trace identifier on the other hand; a computer (8) designed to receive as input an electrogram trace identifier and a time marker, analyze the spatiotemporal dispersion signal of the electrocardiogram associated with the electrogram trace identifier and the time marker, analyze an extract of this signal between the time marker and the first preceding time marker where the value of the spatiotemporal dispersion signal of the electrocardiogram indicates no dispersion to derive on the one hand a flatness value of the signal 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 computer (8) further designed to calculate a second priority value from the cardiac cycle length value associated with the electrogram trace identifier and the time marker received as input, and a third priority value from the voltage histogram uniformity value associated with the electrogram trace identifier and the time marker received as input, and calculate and return a trace priority value determined from the first priority value, the second priority value, and the third priority value for the electrogram trace identifier received as input; a monitor (6) designed to receive an electrocardiogram spatiotemporal dispersion signal associated with each electrocardiogram trace, and to call the computer (8) with the corresponding time marker and electrocardiogram trace identifier when the value of the electrocardiogram spatiotemporal dispersion signal indicates a relevant dispersion; A device comprising:

2. the electrocardiogram spatiotemporal variance signal is a sequence of values ​​derived from the electrogram signal, each of which indicates a confidence level in the fact that variance has occurred for the possible electrogram trace and time marker; 2. The device of claim 1, wherein the monitor (6) and / or the computer (8) are designed to determine whether an electrocardiogram spatiotemporal dispersion signal exhibits relevant dispersion by comparing the value of the electrocardiogram spatiotemporal dispersion signal with a threshold value.

3. 3. The device according to claim 1 or 2, wherein the computer (8) is designed to calculate the flatness value from at least one of the following values: the standard deviation of the signal extraction, the total variation of the signal extraction, the entropy of the signal extraction, or a value derived from one or more first or higher order derivatives of the signal extraction.

4. 4. The device according to any one of claims 1 to 3, wherein the computer (8) is designed to calculate the duration value by comparing the duration of the signal extraction with a minimum and / or a maximum value and by returning the value 0 if the duration of the signal extraction is smaller than the minimum value, by returning the value 1 if the duration of the signal extraction is larger than the maximum value, and by returning a value between 0 and 1 otherwise.

5. 5. The device according to claim 4, wherein the computer (8) is designed to determine the value between 0 and 1 by applying a projection function of the interval between the minimum value and the maximum value onto the interval between 0 and 1 to the duration of the signal extraction, the projection function being selected from an affine function, an exponential function, a polynomial, and a threshold function.

6. 6. The device according to any one of claims 1 to 5, wherein the computer (8) is designed to calculate the first priority value by performing a weighted harmonic mean, a harmonic mean, a weighted or an arithmetic mean of the flatness values ​​and the duration values.

7. the memory (4) receives cardiac cycle length values ​​including cardiac activation cycle length values ​​and total cycle length values; 7. The device of claim 1, wherein the computer is configured to calculate the second priority value by comparing the cardiac activation cycle length value associated with the electrogram trace identifier and the time marker received as input with a threshold value, and / or by comparing the cardiac activation cycle length value and the total cycle length value associated with the electrogram trace identifier and the time marker received as input with each other.

8. the memory (4) is designed to receive voltage histogram uniformity values ​​obtained by performing a G-test or a chi-squared test between a uniformity histogram and a histogram of voltage values ​​associated with a 6 to 10 second period including an electrocardiogram trace identifier and the time marker with which each voltage histogram uniformity value is associated; 8. The device of claim 1, wherein the computer is configured to calculate the third priority value from the voltage histogram uniformity value and threshold associated with the electrogram trace identifier and the time marker received as input.

9. If the first priority value, the second priority value and the third priority value are Boolean values, the computer (8) selects 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 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; 9. A device according to claim 1, which is designed to determine a trace priority value according to:

10. 1. A method for determining trace priority values ​​for spatiotemporal dispersion signals of an electrocardiogram, comprising: The following steps: a) receiving a spatiotemporal variance signal of an electrocardiogram, a cardiac cycle length value and a voltage histogram uniformity value each time associated with a time marker on the one hand and an electrocardiogram trace identifier on the other hand; b) determining whether the values ​​of the spatiotemporal dispersion signal of the electrocardiogram indicate dispersion; c) if operation b) is negative, repeating with a variance value having a later time marker; d) If operation b) is possible, d1) analyzing the spatiotemporal variance signal of the electrocardiogram associated with the corresponding electrogram trace identifier by analyzing a signal excerpt between the time marker and the first preceding time marker for which the value of the spatiotemporal variance signal of the electrocardiogram indicates no variance, and by deriving from this signal excerpt, on the one hand, a flatness value of the signal and, on the other hand, a duration value derived from the duration of the signal excerpt, and calculating a first priority value from the flatness value and the duration value; d2) calculating a second priority value from the electrogram trace identifier and the cardiac cycle length value associated with the time marker received as input; d3) calculating a third priority value from the electrogram trace identifier and the voltage histogram uniformity value associated with the time marker received as input; and d4) calculating a trace priority value determined from the first priority value, the second priority value, and the third priority value of the electrogram trace identifier received as input; e) returning the trace priority value of operation d); A method comprising:

11. the electrocardiogram spatiotemporal variance signal is a sequence of values ​​derived from the electrogram signal, each of which indicates a confidence level in the fact that variance has occurred for the possible electrogram trace and time marker; The method of claim 10 , wherein operation b) comprises comparing the value of the electrocardiogram spatiotemporal variance signal with a threshold value.

12. 12. The method of claim 10 or 11, wherein operation d1) comprises calculating the flatness value from at least one of the following values: the standard deviation of the signal extraction, the total variation of the signal extraction, the entropy of the signal extraction, or a value derived from one or more first or higher order derivatives of the signal extraction.

13. 13. The method according to any one of claims 10 to 12, wherein operation d1) comprises calculating the duration value by comparing the duration of the signal extraction with a minimum and / or a maximum value and by returning the value 0 if the duration of the signal extraction is smaller than the minimum value, returning the value 1 if the duration of the signal extraction is larger than the maximum value, and returning a value between 0 and 1 otherwise.

14. A computer program comprising instructions for carrying out the method of any one of claims 10 to 13 when executed by a computer.

15. A data storage medium on which the computer program according to claim 14 is stored.

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