Adjust annotation points in real time

Abstract

The present invention is entitled "Real-time Adjustment of Annotation Points". The present invention discloses a system comprising a signal acquisition circuit and a processing unit. The signal acquisition circuit is configured to receive a plurality of intracardiac signals acquired by a plurality of electrodes of an intracardiac probe in a patient's heart. The processing unit is configured to select a group of intracardiac signals, extract a corresponding most likely annotation value from each intracardiac signal in the group according to a likelihood criterion, identify in the group an intracardiac signal whose most likely annotation value statistically deviates by more than a predefined measure of deviation in the group, extract at least a second most likely annotation value from the intracardiac signal with the statistically deviated annotation value according to the likelihood criterion, and select a valid annotation value for the corresponding intracardiac signal in response to the statistical deviation of the second most likely annotation value.

Description

Technical Field

[0001] The present invention relates generally to in vivo medical procedures and instruments, and particularly to in vivo cardiac electrocardiogram (ECG) sensing and visualization. Background Art

[0002] When measuring and annotating internal electrocardiogram (iECG) signals generated by a large number of electrodes, it may be desirable to process these signals (eg, by a computer) in order to reduce embedded noise.

[0003] Various methods exist for such iECG signal processing. For example, U.S. Patent Application Publication No. 2016 / 0089048 describes an automated method for determining the local activation time (LAT) of four or more multi-channel electrocardiogram signals, the multi-channel electrocardiogram signal including a ventricular channel, a mapping channel, and multiple reference channels.

[0004] Another example is U.S. Patent Application Publication 2017 / 0311833, which describes a system for diagnosing cardiac arrhythmias and guiding catheter therapy by measuring, classifying, analyzing, and mapping spatial electrophysiological (EP) patterns within the body.

[0005] Yet another example is U.S. Patent Application Publication 2017 / 0042436, which describes systems and methods for automatically integrating measurements taken over multiple heartbeats into a single cardiac map. Summary of the Invention

[0006] Embodiments of the present invention described herein provide a system comprising a signal acquisition circuit and a processing unit. The signal acquisition circuit is configured to receive a plurality of intracardiac signals acquired by a plurality of electrodes of an intracardiac probe in a patient's heart. The processing unit is configured to select a group of intracardiac signals, extract a corresponding most likely annotation value from each of the intracardiac signals in the group according to a likelihood criterion, identify intracardiac signals in the group whose most likely annotation value statistically deviates from the group by more than a predefined measure of deviation, extract at least a second most likely annotation value from the intracardiac signals having the statistically deviated annotation value according to the likelihood criterion, and select a valid annotation value for the corresponding intracardiac signal in response to the statistical deviation of the second most likely annotation value.

[0007] In some embodiments, the processing unit is configured to define a measure of deviation based on a standard score of the annotation values. In the disclosed embodiment, the processing unit is configured to calculate the deviation of the annotation values ​​on intracardiac signals acquired by a selected subset of spatially correlated electrodes that are no more than a predefined distance apart from each other in the heart.

[0008] In an exemplary embodiment, the processing unit is further configured to: for a most likely annotation value that is at least statistically deviated, identify a set of alternative annotation values ​​having a reduced likelihood rank; and select a valid annotation value responsive to the statistical deviance and likelihood rank of the alternative annotation values. In another embodiment, the annotation value comprises a local activation time (LAT).

[0009] In some embodiments, the processing unit is configured to extract the most likely annotation value in the given intracardiac signal by finding an extremum of the given intracardiac signal in the cardiac cycle, and to extract the second most likely annotation value by finding the second highest local extremum of the intracardiac signal. In other embodiments, the processing unit is configured to extract the most likely annotation value in the given intracardiac signal by finding an extremum derivative of the given intracardiac signal in the cardiac cycle, and to extract the second most likely annotation value by finding the second highest local extremum of the derivative.

[0010] According to one embodiment of the present invention, there is further provided a method comprising receiving a plurality of intracardiac signals acquired by a plurality of electrodes of an intracardiac probe in a patient's heart. A group of intracardiac signals is selected. Based on a likelihood criterion, a corresponding most probable annotation value is extracted from each intracardiac signal in the group. An intracardiac signal is identified in the group whose most probable annotation value statistically deviates from a predefined measure of deviation in the group. Based on a likelihood criterion, at least a second most probable annotation value is extracted from the intracardiac signal having the statistically deviated most probable annotation value. In response to the statistical deviation of the second most probable annotation value, a valid annotation value is selected for the corresponding intracardiac signal.

[0011] According to an embodiment of the present invention, a method for obtaining the effective local excitation time of an intracardiac electrocardiogram signal is also provided. The method includes collecting a group of digitized signals representing intracardiac electrocardiogram (ECG) signals, and extracting a first best estimate of the effective local excitation time from the group of ECG signals. Calculate the statistical characteristics of the group of ECG signals. Calculate the standard score of each signal in the group of ECG signals based on the group statistical characteristics. Compare the standard score of each signal with a preset limit. The first best estimate of the effective local excitation time is replaced by the local excitation time of the signal having a standard score within the preset limit.

[0012] The present invention will be more fully understood through the following detailed description of embodiments of the present invention in conjunction with the accompanying drawings, in which: BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 is a schematic illustration of an electroanatomical system for multi-channel measurement of ECG signals within a heart according to an embodiment of the present invention;

[0014] Figure 2A diagram schematically illustrating a group of spatially correlated electrodes acquiring signals in a single cardiac cycle according to an embodiment of the present invention;

[0015] Figure 3 is a flow chart schematically illustrating a method for enhancing the reliability of annotation values ​​according to an embodiment of the present invention; and

[0016] Figure 4 4 is a flow chart schematically illustrating a method for enhancing the reliability of annotation values ​​of a set of spatially correlated LAT values ​​according to an embodiment of the present invention. DETAILED DESCRIPTION

[0017] Overview

[0018] Cardiac diagnostic and therapeutic systems based on intracardiac probes (e.g., catheter-based) can measure multiple intracardiac signals, such as electrocardiograms (ECGs), during invasive procedures. Such systems can use electrodes mounted at the distal end of the probe (hereinafter also referred to as "distal electrodes") to acquire multiple intracardiac signals. The measured signals are typically analyzed, and local activation signals (LATs) are annotated, which can be used to provide physicians with visual cardiac information, such as 3-D mapping of the patient's intracardiac pathological electrographic sources, and to support corrective medical procedures, such as ablation.

[0019] The measured signal is typically weak, resulting in a low signal-to-noise ratio (SNR). Furthermore, pathological electrocardiograms, such as those caused by atrial flutter or atrial fibrillation, can exhibit multiple peaks during the cardiac cycle, complicating the measurement of LAT values. Furthermore, many electrodes are used, so the data received by the system from the electrodes may contain some redundancy.

[0020] Embodiments of the invention disclosed herein provide methods for analyzing the statistical properties of signals collected using intracardiac probes and electroanatomical measurements and analysis systems using distal electrodes to improve the quality and reliability of the collected data. These methods are rapid and can therefore be performed in real time; for example, during invasive procedures.

[0021] Although the description below refers to annotation values ​​of local activation time (LAT), in various embodiments of the present invention, other suitable signal parameters may be used mutatis mutandis. Thus, the term "annotation value" includes other parameters as well as those related to LAT.

[0022] According to an embodiment, the most likely LAT annotation value for a measured intracardiac signal can be estimated by analyzing the intracardiac signal using preset criteria. Several LAT estimation criteria can be used, including (but not limited to) the maximum signal voltage event, the minimum signal voltage event, the maximum rate of change of the positive voltage slope event, and the maximum rate of change of the negative voltage slope event. The LAT estimate is then set to the time of occurrence of the event based on the selected criteria. The value of the voltage or slope at the event will be referred to herein as the "y value."

[0023] As described above, due to noise and / or cardiac pathology, such LAT estimates may sometimes incorrectly identify a local extrema (either a maximum or minimum, depending on the criterion) rather than the desired extrema. In those cases, a more accurate LAT estimate can be achieved if the processor reanalyzes the signal using the same criterion, but searches for a second, third, fourth, or other extrema. (To avoid confusion between min / max / high / low, we will use terms such as "best LAT estimate," "second best," "third best," etc. below. For a maximum voltage or maximum dv / dt event, the best estimate is the highest voltage or highest dv / dt; the second best is the second highest local maximum, etc. Similarly, for a minimum voltage or minimum dv / dt event, the best estimate is the minimum voltage or minimum dv / dt; the second best estimate is the second lowest local minimum, etc.)

[0024] The above LAT estimates are sometimes referred to as "LAT annotation values."

[0025] The technology disclosed herein assumes that, in the absence of noise and irregular current connections, electrodes that are physically close to each other ("adjacent electrodes") and / or signals acquired at temporally adjacent heartbeats exhibit similar annotation values. Signals extracted from adjacent electrodes and LAT values ​​annotated from such signals are referred to as "spatial correlation," while signals extracted from temporally adjacent heartbeats and LAT values ​​annotated from such signals are referred to as "temporal correlation." Spatially and / or temporally correlated signals and annotation values ​​will be collectively referred to as "correlated."

[0026] Embodiments according to the present invention exploit the expected similarity of related signals to improve the reliability of visualized LAT values.

[0027] In some embodiments, the processor annotates the LAT values ​​of a group of related intracardiac electrophysiological signals using, for example, one of the four criteria described above. The processor then calculates a statistical property of the group and uses a measure of deviation responsive to the statistical property to determine which of the signals deviate substantially from the LAT values ​​of the group (e.g., signals having LAT values ​​that are not within a predetermined distance from the group mean).

[0028] According to an embodiment, for a signal that substantially deviates from the group value, the processor decides to re-evaluate the LAT value using a second best estimate, a third best estimate, and so on, until the processor finds a LAT value that does not substantially deviate from the group value. In an embodiment, the statistical characteristic includes an average of the LAT values ​​for the group (e.g., ) and standard deviation (e.g., The measure of deviation is the standard score of the LAT value (defined as the difference between the value and the mean divided by the standard deviation), which is compared to preset limits. For example, a substantially deviant LAT value can be defined as any value that is more than 3.5 standard deviations above the mean (standard score = 3.5), or more than 1.5 standard deviations below the mean (standard score = 1.5).

[0029] In summary, according to an embodiment of the present invention, the quality and reliability of a set of annotation values ​​for spatially correlated intracardiac signals visualized for a user can be improved in real time by calculating statistical properties of the annotation values ​​and using the next best estimate to recalculate LAT values ​​that substantially deviate from the group values.

[0030] System Description

[0031] Figure 1 is a schematic illustration of an electroanatomical system 21 for multi-channel measurement of ECG signals in a heart, according to an embodiment of the present invention. In some embodiments, system 21 is used for electroanatomical mapping of the heart.

[0032] Figure 1 A physician 22 is depicted using an electroanatomical catheter 23 to perform electroanatomical mapping of a heart 24 of a patient 25. The catheter 23 includes at its distal end one or more arms 26, which may be mechanically flexible, with one or more distal electrodes 27 coupled to each of the one or more arms. It should be understood that although Figure 1 A catheter with five arms is depicted, but other types of catheters may be used in accordance with alternative embodiments of the present invention. The electrodes are coupled to a processor 34 through an interface 32 .

[0033] During an electroanatomical mapping procedure, a tracking system is used to track the intracardiac position of the distal electrodes 27 so that each of the acquired electrophysiological signals can be associated with a known intracardiac position. One example of a tracking system is the Active Current Location (ACL) system described in U.S. Patent 8,456,182. In the ACL system, a processor estimates the respective positions of the distal electrodes 27 based on impedance measured between each of the distal electrodes 27 and a plurality of surface electrodes 28 coupled to the skin of the patient 25 (for ease of illustration, the respective positions of the distal electrodes 27 are estimated by a processor). Figure 1Only one surface electrode is shown.) The processor can then associate any electrophysiological signals received from distal electrode 27 with the location where the signal was acquired.

[0034] In some embodiments, multiple distal electrodes 27 acquire intracardiac ECG signals from tissue of a chamber of heart 24. The processor includes signal acquisition circuitry 36 coupled to receive the intracardiac signals from interface 32, memory 38 to store data and / or instructions, and a processing unit 42 (e.g., a CPU or other processor).

[0035] The signal acquisition circuit 36 ​​digitizes the intracardiac signals to generate a plurality of digital signals and then transmits the digitized signals to a processing unit 42 included in the processor 34 .

[0036] Among other tasks, the processing unit 42 is configured to extract annotation parameters from the signal, such as local activation time ("LAT"), based on a criterion selected from a set of LAT estimation criteria, including (but not limited to) maximum ECG voltage, minimum ECG voltage, maximum positive rate of change of ECG voltage, and maximum negative rate of change of ECG voltage. When the processing unit estimates LAT based on, for example, the maximum ECG voltage criterion, the LAT value will be equal to the time when the Y value of the ECG signal is at a maximum value (for each cardiac cycle). Similarly, the estimated LAT may be equal to the time when the Y value is at a minimum value, when the first derivative of the Y value is at its maximum value, or when the first derivative is at its minimum value.

[0037] The processing unit 42 is further configured to calculate statistical properties, such as the average of annotation parameters of a group of possibly similar adjacent signals (in the present context, adjacent signals refer to signals from electrodes located close to each other ("spatially correlated")).

[0038] Depending on the embodiment, the acquired ECG signals may be noisy due to poor current connections, induced noise from various sources, noise in the signal acquisition circuit 36, or noise from any other source. In addition, pathological ECG signals (such as those associated with atrial flutter and right bundle branch obstruction) may exhibit multiple voltage peaks and / or dips, as well as multiple dv / dt peaks and dips, during each cardiac cycle. By comparing the LAT values ​​of each signal in the group of signals, the processing unit can determine that LAT values ​​that deviate significantly from the group's values ​​are likely to be erroneous. LAT values ​​that are unlikely to be erroneous (e.g., best-estimated LAT values) are hereinafter referred to as valid LAT values.

[0039] In an embodiment, for any of the LAT estimation criteria, in addition to the most likely value (which corresponds to the absolute maximum or minimum), the processing unit may also extract a series of alternative LAT values ​​with decreasing likelihood. For example, for the maximum voltage criterion, the processing unit may be configured to find a local maximum of the ECG signal, then extract a second best LAT estimate from the second highest maximum, a third best estimate from the third highest maximum, and so on. In a similar manner, the processing unit may construct a series of alternative LAT values ​​with decreasing likelihood for any of the four criteria by finding a local maximum or minimum of voltage and a first-order derivative of the voltage of the ECG signal.

[0040] If the processing unit 42 determines that the LAT value is invalid, the processing unit may try alternative LAT values, starting with the second best estimate and proceeding to less likely LAT values ​​until a valid value (e.g., a LAT value that is less likely to be erroneous) is found (if the processing unit does not find any valid values, the processing unit may, for example, discard the signal, or use a best estimate that may be erroneous).

[0041] In some embodiments, processing unit 42 uses the valid annotation values, for example, to construct an electroanatomical map 50 of the heart and displays the map in real time to physician 22 on screen 52. Alternatively, processing unit 42 may present the valid annotation values ​​in any other suitable manner.

[0042] Figure 1 The exemplary illustrations shown are chosen solely for conceptual clarity. In alternative embodiments of the present invention, for example, a voltage gradient may be applied between pairs of surface electrodes 28 and the resulting potentials may be measured using distal electrodes 27 (e.g., using a CMOS sensor manufactured by Biosense-Webster of Irvine, California). Therefore, embodiments of the present invention are applicable to any position sensing method.

[0043] Other types of catheters may be used equivalently, such as Catheter (produced by Biosense-Webster) or basket catheter. A contact sensor can be mounted on the distal end of the electroanatomical catheter 23. Other types of electrodes (such as electrodes used for ablation) can be used on the distal electrode 27 in a similar manner to collect intracardiac electrophysiological signals.

[0044] Figure 1 The diagram primarily shows the parts relevant to the embodiments of the present invention. Other system components, such as external ECG recording electrodes and their connections, are omitted. Various ECG recording system components, as well as components for filtering, digitizing, protecting the circuit, etc., are omitted.

[0045] In an alternative embodiment, a readout application specific integrated circuit (ASIC) is used to measure the ECG signal within the heart. The various components used to route the signal acquisition circuit 36 ​​can be implemented in hardware, for example, using one or more discrete components such as a field programmable gate array (FPGA) or an ASIC. In some embodiments, some components of the signal acquisition circuit 36 ​​and / or the processing unit 42 can be implemented in software, or by using a combination of software and hardware components.

[0046] The processing unit 42 typically includes a general-purpose processor having software programmed to perform the functions described herein. For example, the software may be downloaded in electronic form over a network, or alternatively or in addition, the software may be provided and / or stored on non-transitory tangible media such as magnetic, optical, or electronic memory.

[0047] Figure 2 FIG200 schematically illustrates a set of spatially correlated electrodes acquiring signals during a single cardiac cycle, according to an embodiment of the present invention. The horizontal axis represents time, and the vertical axis represents voltage level. Four signals are shown—a first electrode signal 202, a second electrode signal 204, a third electrode signal 206, and a fourth electrode signal 208. Each signal exhibits an R peak followed by a T peak.

[0048] Processing unit 42 ( Figure 1 ) uses a maximum voltage criterion to annotate the LAT values ​​of the signals—value 210 corresponding to the R-peak of signal 208; value 212 corresponding to the R-peak of signal 202; and value 214 corresponding to the R-peak of signal 206. Due to noise and / or pathology, for signal 204, the voltage of the T-peak is higher than the voltage of the R-peak, and therefore the initial LAT annotation (best LAT estimate) of signal 204 is the LAT value 216 corresponding to the peak of the T signal. However, the second best estimate of the LAT of signal 204 (i.e., the second highest local maximum) is the R-peak, represented by LAT value 218.

[0049] according to Figure 2 In the exemplary embodiment shown, LAT value 216 deviates substantially from the LAT value of the group. Therefore, processing unit 42 will try alternative values, starting with the second best estimate. Since LAT value 218 does not deviate from the LAT value of the group and therefore does not deviate from the most likely annotation value, LAT value 218 is a valid LAT value.

[0050] Thus, using a relatively fast method that can be done in real time, the processing unit can enhance the reliability of the annotated LAT values ​​by checking LAT values ​​associated with local maxima that are below the absolute maximum if the best LAT estimate deviates significantly from the group's LAT value.

[0051] Figure 2 The exemplary illustrations shown are chosen purely for the sake of conceptual clarity. For example, in alternative embodiments of the present invention, more spatially correlated signals may be used; the number of local maxima may be more than two, and other LAT estimation criteria may be used.

[0052] Figure 3 FIG3 is a flow chart 300 schematically illustrating a method for enhancing the reliability of annotation values ​​according to an embodiment of the present invention. The method is executed by the processing unit 42 ( Figure 1 ).

[0053] The method starts at a "collect signals" step 302, where the processing unit collects a plurality of intracardiac ECG signals. Then, in a "select group" step 304, the processing unit selects a group of related signals from the collected signals. This selection can be done, for example, using technology or by other suitable techniques.

[0054] Then, in a "Select Criteria" step 304, the processing unit selects a LAT estimation criterion. The selected criterion may be, for example, one of maximum voltage, minimum voltage, maximum dv / dt, and minimum (most negative) dv / dt. This selection may be indicated by the user or made in any other manner.

[0055] Using the criteria selected in step 304, the processing unit extracts the LAT values ​​for all group signals at an "Extract Group Annotation Values" step 306 by finding the best LAT estimate corresponding to the selected criteria. For example, Figure 2 In FIG. 1 , the processor may review the set of signals ( 210 - 218 ) having LAT value 210 , LAT value 212 , LAT value 214 , LAT value 216 , and LAT value 218 and consider these values ​​against a selected likelihood criterion to select LAT value 218 (e.g., from Figure 2 ) is step 306 (in Figure 3 The “best LAT estimate” (or LAT value that is less likely to be wrong) in the ) becomes the “valid annotation value” that can be displayed graphically.

[0056] It should be noted that depending on the results of the statistical tests used in loops 310 to 314, loops 316 to 320, or loops 324 to 328, the processor may replace the best LAT estimate from step 306 with the best estimate from the corresponding statistical test loop 316 to 320 (i.e., replacing the first best estimate from step 306 with the second best estimate at step 322), or with the best estimate from loops 324 to 328 (to replace the first best estimate from step 306 with the third best estimate at step 330).

[0057] Next, in a “Calculate Statistical Properties” step 308 , the processing unit calculates one or more parameters of the set of LAT values, such as a mean, a standard deviation, etc.

[0058] After calculating the group statistics in step 308, the processing unit begins a loop (steps 310 to 314) in which the LAT annotation of each signal is checked against the statistical properties of the group (from step 308) and recalculated if the LAT value deviates significantly from the group LAT value. That is, the processor checks for LAT values ​​that are "statistically deviated" from the group statistics obtained in step 308 by more than a predefined measure of statistical deviation. The loop (steps 310 to 314) begins with a "select next signal" step 310 in which the processing unit selects a signal from the group (e.g., Figure 2 The next signal is selected from the list of signals 210 to 218 in the figure, and in a "Calculate Standard Score" step 312, the standard score of the signal relative to the group statistical characteristics is calculated (i.e., the processor calculates the number of standard deviations between the LAT value of the signal and the group mean).

[0059] Next, in a "Compare to Limits" step 314, the processing unit checks whether the LAT signal's standard score is within preset limits. If the LAT value is within preset limits (such as, for example, 0.25), the processing unit proceeds to a "Check All Considered Signals" step 315. If more signals are to be considered in step 315, the processing unit re-enters step 310 to examine the next signal in the group; however, if no more signals are to be considered, the flowchart ends (or, alternatively, can be re-run for another group of signals).

[0060] Steps 310 to 314 allow the processor to identify any intracardiac signals in the set of intracardiac signals having a "statistically deviant" annotation value; for example—an annotation value that deviates from the group mean by more than a predefined measure of statistical standard deviation.

[0061] If, at step 314, the LAT value of the signal is not within the preset limits, the processing unit proceeds to an "Extract Second Best LAT" step 316 and calculates the second best LAT value (as described above with respect to step 312), calculates a standard score for the second best LAT in a "Calculate Standard Score" step 318, and compares the standard score to the preset limits in a "Compare to Limits" step 320.

[0062] If, in step 320, the standard score is within the preset limits, then the second best estimate is better than the first estimate; the processing unit will proceed to a "Replace Best by Second Best" step 322 and replace the best estimate LAT in the set of signals (from step 306) with the second best, and then re-enter step 310 to check the next signal. However, if, in step 320, the standard score is not within the preset limits, the processing unit assumes that the second best estimate is wrong and tries a third best estimate - in an "Extract Third Best LAT" step 324, the processing unit extracts the third best value; in a "Calculate Standard Score" step 326, the processing unit calculates the standard score of the third best LAT estimate and checks whether the standard score is within the preset limits in a "Compare to Limits" step 328.

[0063] If, in step 328, the standard score is within the preset limits, then the third best estimate is better than the first best estimate in step 306 (and the second best estimate in step 316); the processing unit will proceed to a "Replace Best by Third Best" step 330, replacing the best estimate LAT (from step 306) in the set of signals with the third best, and then re-enter step 310 to examine the next signal. However, if, in step 328, the standard score of the third best estimate is not within the limits, then the best estimate LAT should not be changed, and the processing unit re-enters step 310 to examine the next signal.

[0064] As described above, when there are no more signals of the current group to consider, the flowchart ends at step 315. At this stage, the processing unit will have annotated LAT values ​​for all signals in the group. The processing unit can then re-enter the flowchart for another group of related signals, or perform other tasks beyond the scope of this disclosure.

[0065] Figure 3The exemplary flowchart shown in is selected solely for conceptual clarity. In alternative embodiments, for example, the flowchart may include checking a fourth and / or less likely best estimate; in other embodiments, only the second best estimate is checked. In some embodiments, the less likely estimates are calculated and stored as part of step 306 for the entire group, and thus steps 312, 318, and 326 are redundant. In some embodiments, some or all of the steps may be performed simultaneously. Reference will be made to Figure 4 Describe some typical alternative flow charts.

[0066] Figure 4 FIG4 is a flow chart 400 schematically illustrating a method for enhancing the reliability of annotation values ​​of a set of spatially correlated LAT values ​​according to an embodiment of the present invention. The method is performed by a processing unit 42 ( Figure 1 ) after computing the statistical properties of the group for each member of the group (e.g., Figure 3 After step 308; however, it should be noted that Figure 4 Replaced Figure 3 (additional steps from step 310 to step 330).

[0067] and Figure 3 The exemplary embodiments are different, according to Figure 4 In the method shown, the processing unit creates a new set of valid LAT signals while examining the set of signals, which can then be visualized to the user.

[0068] The flowchart begins with the "Get Optimal LAT" step 402, where the processing unit stores the data from the Figure 3 The optimal LAT and corresponding Y value of the routine described in the flowchart of FIG. We can assume that when the processor is, for example, Figure 3 When calculating the group annotation value in step 306, the optimal LAT and the corresponding Y value are extracted.

[0069] Next, in the "Calculate Standard Score" step 404, the processing unit calculates the number of standard deviations between the LAT value of the signal and the group mean, and proceeds to the "Compare to Limit Value" step 406 to check whether the standard score of the LAT signal is within the preset limit.

[0070] If the standard score of the LAT value is not within the preset limits, the processing unit will enter the "check whether to allow the next iteration" step 408. When the processing unit enters step 408 for the first time, the processing unit will start the first iteration, and each time the processing unit re-enters step 408, the number of iterations will increase. In an embodiment, there may be a limit on the number of iterations - for example, the processor is unlikely to skip an estimate after the third best estimate (and therefore, in step 408, the next iteration will not be allowed after three iterations). In another example, if there are no longer any local maxima or minima (according to the selected criteria), the processing unit may skip further iterations.

[0071] If the next iteration is allowed in step 408, the processing unit will proceed to a "calculate next best LAT" step 410, where the processing unit calculates the next best LAT and the corresponding Y value.

[0072] according to Figure 4 In the exemplary embodiment shown, to qualify as a valid LAT value, a local maximum (or minimum, depending on the selected criterion) must be substantial relative to the best estimate. For example, if the criterion is a maximum dv / dt; absolute maximum of 25 mV / Sec and a second local maximum (second best estimate) of 1 mV / Sec, the processing unit may reject the second best estimate even though the best estimate may be substantially different from the group average.

[0073] The processing unit performs this test in a "Check Y-Value Ratio" step 412, which is executed after step 410. The processing unit divides the second best estimate (1 mV / Sec in the above example) by the best estimated Y value (25 mV / Sec) and compares the result (0.04) to a preset threshold. If the ratio is greater than the threshold, the processing unit proceeds to a "Calculate Standard Score" step 414 and calculates the standard score of the current LAT estimate relative to the group statistic. It then proceeds to a "Compare to Limits" step 416 to check whether the standard score of the next best LAT signal is within the preset limits. If the standard score is not within the limits, the processing unit re-enters step 408 and tries the next best estimate.

[0074] according to Figure 4In the exemplary embodiment shown, the processing unit can be in a discard mode, in which invalid LAT values ​​are not visualized (instead of visualizing the best estimate, which is most likely incorrect). If, in step 408, no more iterations are allowed, or if, in step 412, the ratio is too low to deem the current best LAT estimate invalid, then no valid LAT value exists for the signal. The processing unit proceeds to a "check discard mode" step 418; if discard mode is on, the process ends (and no valid value will be included in the set of valid LAT values, and therefore the LAT of the current signal will not be visualized). If, in step 418, discard mode is off, the processing unit proceeds to a "restore to best estimate" step 420 and changes the current LAT estimate to the best LAT stored in step 402.

[0075] If, in step 406, the best LAT is within the limits; or if, in step 416, the lower best estimate is within the limits; and, after step 420, the processing unit enters an "add LAT to effective LAT" step 422 and adds the current LAT estimate to the set of effective LAT estimates, and the flowchart ends (or, typically, is rerun for the next signal in the set).

[0076] It should be understood that Figure 4 The exemplary flow chart shown in is chosen purely for conceptual clarity. In alternative embodiments of the invention, for example, there is no discard mode - in one embodiment, invalid values ​​are never visualized, and in another embodiment, invalid values ​​are always visualized. In yet another embodiment, the processing unit may decide whether to visualize or hide non-valid LAT values ​​based on a less restrictive test; for example - if a value's standard score deviates from the group mean by a threshold greater than the threshold used in steps 406 and 416, then the value will be visualized. In some embodiments, invalid values ​​are visualized but clearly marked.

[0077] It should be understood that the above embodiments are cited by way of example, and the present invention is not limited to what has been specifically shown and described hereinabove. On the contrary, the scope of the present invention includes combinations and subcombinations of the various features described hereinabove, as well as variations and modifications thereof, which will occur to those skilled in the art upon reading the above description and which are not disclosed in the prior art.

Claims

1. A system for adjusting annotation points in real time, comprising: a signal acquisition circuit configured to receive a plurality of intracardiac signals acquired by a plurality of electrodes of an intracardiac probe in a patient's heart; and A processing unit, wherein the processing unit is configured to: collecting a set of intracardiac signals; extracting a corresponding most likely annotation value from each of the intracardiac signals in the set according to a likelihood criterion, wherein the likelihood criterion comprises a maximum voltage, a minimum voltage, a maximum time derivative of a voltage, or a minimum time derivative of a voltage; identifying intracardiac signals in the group whose most likely annotation values ​​in the group statistically deviate by more than a predefined measure of deviation; extracting at least a second most likely annotation value from the intracardiac signal having the statistically deviated most likely annotation value based on the likelihood criterion; as well as Responsive to the statistical deviation of the second most probable annotation value, a valid annotation value is selected for the corresponding intracardiac signal.

2. A system for adjusting annotation points in real time according to claim 1, wherein the processing unit is configured to define the measure of the deviation based on a standard score of the annotation value, wherein the standard score of the annotation value includes a difference between the annotation value and a group average of the annotation values ​​of each intracardiac signal in the group divided by a standard deviation of the annotation values ​​of each intracardiac signal in the group.

3. A system for real-time adjustment of annotation points according to claim 1, wherein the processing unit is configured to calculate the deviation of the annotation value on an intracardiac signal, the intracardiac signal being acquired by a selected subset of spatially correlated electrodes in the heart that are no more than a predefined distance apart from each other.

4. A system for adjusting annotation points in real time according to claim 1, wherein the processing unit is further configured to identify a set of alternative annotation values ​​with reduced likelihood for at least the most likely annotation value of the statistical deviation, and select the valid annotation value in response to the statistical deviation and the likelihood of the alternative annotation values.

5. The system for adjusting annotation points in real time according to claim 1, wherein the annotation value comprises local activation time (LAT).

6. A system for adjusting annotation points in real time according to claim 1, wherein the processing unit is configured to extract the most likely annotation value in the given intracardiac signal by finding an extreme value of the given intracardiac signal in a cardiac cycle, and to extract the second most likely annotation value by finding a second highest local extreme value of the intracardiac signal.

7. A system for real-time adjustment of annotation points according to claim 1, wherein the processing unit is configured to extract the most likely annotation value in the given intracardiac signal by finding an extreme derivative of the given intracardiac signal in a cardiac cycle, and to extract the second most likely annotation value by finding the second highest local extreme of the derivative.

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