Cardiac diagnostic system

Abstract

To diagnose the patient's arrhythmia. [Solution] The system 100 for diagnosing a patient's arrhythmia is inserted into the patient's heart. A diagnostic catheter 10 for recording the patient's anatomical and electrical activity data. It includes a diagnostic catheter 10 configured as and a processing unit. The processing unit records The system receives the electrical activity data 120 and compares the electrical activity data 120 with the anatomical data. They are configured to be linked together. The processing unit is the position associated with the anatomical data. This includes an algorithm configured to analyze electrical activity.

Description

[Technical Field]

[0001] This application is a patent application filed on January 21, 2018, under Section 119(e) of the United States Patent Act. System for Recognizing Cardiac Conductio U.S. Provisional Patent Application No. 62 / 619,897, entitled "n Patterns", and 201 The "System for Identifying Card" application filed on May 8, 2008, is now available. U.S. Provisional Patent Application No. 62 / 6 entitled "iac Conduction Patterns" This asserts priority over patent number 68,647, each of which is by reference in whole. This specification is incorporated herein.

[0002] This application does not claim priority, but the "Sy" application filed on November 9, 2018 stems and Methods for Calculating Patien Regarding U.S. Provisional Patent Application No. 62 / 757,961, titled "t Information" This may be linked to other relevant documents, which are incorporated herein by reference.

[0003] This application does not claim priority, but it does not claim priority over the "Ca" application filed on May 8, 2018. Titled "rdiac Information Processing System" This may relate to U.S. Provisional Patent Application No. 62 / 668,659, which is evident by reference. It will be included in the detailed specifications.

[0004] This application does not claim priority, but the application filed on October 31, 2018, Cardiac Mapping System with Efficiency A In cases related to U.S. Patent Application No. 16 / 097,959, titled "Igorithm" This is the "Cardiac Mapping System" filed on May 3, 2017. Patent Cooperation Treaty titled "Them with Efficiency Algorithm" National phase under Section 371 of the United States Patent Act for application number PCT / US2017 / 030922 This is a transition application, filed on October 26, 2016, titled "Cardiac Map Titled "Ping System with Efficiency Algorithm" U.S. Provisional Patent Application No. 62 / 413,104, and the application filed on May 3, 2016, Cardiac Mapping System with Efficiency A Priority to U.S. Provisional Patent Application No. 62 / 331,364, titled "Igorithm" These are assertions, and each of them is incorporated herein by reference.

[0005] This application does not claim priority, but the application filed on October 31, 2018, Cardiac Information Dynamic Display System Related to U.S. Patent Application No. 16 / 097,955, entitled "em and Method" This may be the case, and this is related to the "Cardiac Inform" application filed on May 3, 2017. ation Dynamic Display System and Method” Article 37 of the United States Patent Act, concerning Patent Cooperation Treaty application number PCT / US2017 / 030915, titled This is a national phase entry application under Section 1, which was filed on May 3, 2016, for the "Ca rdiac Information Dynamic Display System claims priority to U.S. Provisional Patent Application No. 62 / 331,351, titled "and Method", each of which is incorporated herein by reference. This application does not claim priority but may be related to Patent Cooperation Treaty Application No. PCT / US2017 / 056064, titled "Ablation System with Force Control", filed on October 11, 2017, which claims priority to U.S. Provisional Patent Application No. 62 / 406,74, titled "Ablation System with Force Control", filed on October 11, 2016, and U.S. Provisional Patent Application No. 62 / 504,139, titled "Ablation System with Force Control", filed on May 20, 2017, each of which is incorporated herein by reference.

[0006] This application does not claim priority but may be related to U.S. Patent Application No. 15 / 569,457, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on October 26, 2017, which is related to Patent Cooperation Treaty Application No. PCT / US2016 / 032420, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on May 13, 2016, under 37 This application does not claim priority but may be related to Patent Cooperation Treaty Application No. PCT / US2017 / 056064, titled "Ablation System with Force Control", filed on October 11, 2017, which claims priority to U.S. Provisional Patent Application No. 62 / 406,748, titled "Ablation System with Force Control", filed on October 11, 2016, and U.S. Provisional Patent Application No. 62 / 504,139, titled "Ablation System with Force Control", filed on May 20, 2017, each of which is incorporated herein by reference. This application does not claim priority but may be related to Patent Cooperation Treaty Application No. PCT / US2017 / 056064, titled "Ablation System with Force Control", filed on October 11, 2017, which claims priority to U.S. Provisional Patent Application No. 62 / 406,748, titled "Ablation System with Force Control", filed on October 11, 2016, and U.S. Provisional Patent Application No. 62 / 504,139, titled "Ablation System with Force Control", filed on May 20, 2017, each of which is incorporated herein by reference. This application does not claim priority but may be related to Patent Cooperation Treaty Application No. PCT / US2017 / 056064, titled "Ablation System with Force Control", filed on October 11, 2017, which claims priority to U.S. Provisional Patent Application No. 62 / 406,748, titled "Ablation System with Force Control", filed on October 11, 2016, and U.S. Provisional Patent Application No. 62 / 504,139, titled "Ablation System with Force Control", filed on May 20, 2017, each of which is incorporated herein by reference. This application does not claim priority but may be related to Patent Cooperation Treaty Application No. PCT / US2017 / 056064, titled "Ablation System with Force Control", filed on October 11, 2017, which claims priority to U.S. Provisional Patent Application No. 62 / 406,748, titled "Ablation System with Force Control", filed on October 11, 2016, and U.S. Provisional Patent Application No. 62 / 504,139, titled "Ablation System with Force Control", filed on May 20, 2017, each of which is incorporated herein by reference. This application does not claim priority but may be related to Patent Cooperation Treaty Application No. PCT / US2017 / 056064, titled "Ablation System with Force Control", filed on October 11, 2017, which claims priority to U.S. Provisional Patent Application No. 62 / 406,748, titled "Ablation System with Force Control", filed on October 11, 2016, and U.S. Provisional Patent Application No. 62 / 504,139, titled "Ablation System with Force Control", filed on May 20, 2017, each of which is incorporated herein by reference. This application does not claim priority but may be related to Patent Cooperation Treaty Application No. PCT / US2017 / 056064, titled "Ablation System with Force Control", filed on October 11, 2017, which claims priority to U.S. Provisional Patent Application No. 62 / 406,748, titled "Ablation System with Force Control", filed on October 11, 2016, and U.S. Provisional Patent Application No. 62 / 504,139, titled "Ablation System with Force Control", filed on May 20, 2017, each of which is incorporated herein by reference. This application does not claim priority but may be related to Patent Cooperation Treaty Application No. PCT / US2017 / 056064, titled "Ablation System with Force Control", filed on October 11, 2017, which claims priority to U.S. Provisional Patent Application No. 62 / 406,748, titled "Ablation System with Force Control", filed on October 11, 2016, and U.S. Provisional Patent Application No. 62 / 504,139, titled "Ablation System with Force Control", filed on May 20, 2017, each of which is incorporated herein by reference.

[0007] This application does not claim priority but may be related to U.S. Patent Application No. 15 / 569,457, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on October 26, 2017, which is related to Patent Cooperation Treaty Application No. PCT / US2016 / 032420, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on May 13, 2016, under 37 This application does not claim priority but may be related to U.S. Patent Application No. 15 / 569,457, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on October 26, 2017, which is related to Patent Cooperation Treaty Application No. PCT / US2016 / 032420, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on May 13, 2016, under 37 This application does not claim priority but may be related to U.S. Patent Application No. 15 / 569,457, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on October 26, 2017, which is related to Patent Cooperation Treaty Application No. PCT / US2016 / 032420, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on May 13, 2016, under This application does not claim priority but may be related to U.S. Patent Application No. 15 / 569,457, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on October 26, 2017, which is related to Patent Cooperation Treaty Application No. PCT / US2016 / 032420, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on May 13, 2016, under This application does not claim priority but may be related to U.S. Patent Application No. 15 / 569,457, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on October 26, 2017, which is related to Patent Cooperation Treaty Application No. PCT / US2016 / 032420, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on May 13, 2016, under This application does not claim priority but may be related to U.S. Patent Application No. 15 / 569,457, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on October 26, 2017, which is related to Patent Cooperation Treaty Application No. PCT / US2016 / 032420, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on May 13, 2016, under This application does not claim priority but may be related to U.S. Patent Application No. 15 / 569,457, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on October 26, 2017, which is related to Patent Cooperation Treaty Application No. PCT / US2016 / 032420, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on May 13, 2016, under This application does not claim priority but may be related to U.S. Patent Application No. 15 / 569,457, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on October 26, 2017, which is related to Patent Cooperation Treaty Application No. PCT / US2016 / 032420, titled "Localization System and Method Useful in the Acquisition and Analysis of Cardiac Information", filed on May 13, 2016, under This is a national phase entry application under Section 1, which was filed on May 13, 2015, under the name "L localization System and Method Useful in the Acquisition and Analysis of Cardiac Superiority of U.S. Provisional Patent Application No. 62 / 161,213, entitled "Information" These are prior articulations and are incorporated herein by reference.

[0008] This application does not claim priority, but the application filed on October 25, 2017, Cardiac Virtualization Test Tank and Tes U.S. Patent Application No. 15 / 569, entitled "Ting System and Method" This may be related to patent no. 231, which was filed on May 11, 2016, "Card iac Virtualization Test Tank and Testing Patent Cooperation Treaty application number PCT / US2, titled "System and Method" This is a national phase entry application under Section 371 of the U.S. Patent Act, No. 016 / 031823, which is The "Cardiac Virtualization" patent application filed on May 12, 2015, Test Tank and Testing System and Method This application claims priority to U.S. Provisional Patent Application No. 62 / 160,501, titled "... Each of these is incorporated herein by reference.

[0009] This application does not claim priority, but the application filed on October 25, 2017, Ultrasound Sequencing System and Method” This may relate to U.S. Patent Application No. 15 / 569,185, which is titled 201 The "Ultrasound Sequencing System" was filed on May 12, 2006. Patent Cooperation Treaty application number PCT / US2016 / 0, titled "em and Method" This is a national phase entry application under Section 371 of the U.S. Patent Act, No. 32017, which was filed in 2015. The "Ultrasound Sequencing System" application filed on May 12th of that year U.S. Provisional Patent Application No. 62 / 160,529, entitled "m and Method" These are claims of priority and are incorporated herein by reference.

[0010] This application does not claim priority, but it is based on the "D" application filed on September 10, 2014. evices and methods for Determination of Electrical Dipole Densities on a Cardiac This may relate to U.S. Patent Application No. 14 / 916,056, titled "Surface". This is a patent application filed on September 10, 2014, entitled "Devices and Methods ds for Determination of Electrical Dipol A patent association article titled "Densities on a Cardiac Surface" Domestic patent application number PCT / US2014 / 54942 under Section 371 of the United States Patent Act This is a phase transition application, filed on September 13, 2013, titled "Devices and d Methods for Determination of Electrica l Dipole Densities on a Cardiac Surface” This claims priority to U.S. Provisional Patent Application No. 61 / 877,617, titled [the same application]. Each of these is incorporated herein by reference.

[0011] This application does not claim priority, but it is based on the "C" application filed on September 23, 2016. ardiac Analysis User Interface System an This may relate to U.S. Patent Application No. 15 / 128,563, titled "d Method". This is a patent application filed on March 24, 2015, for "Cardiac Analysis". The Japan Patent Association, under the title "User Interface System and Method" Domestic patent application number PCT / US2015 / 22187 under Section 371 of the United States Patent Act This is a phase transition application, which was filed on March 28, 2014, for "Cardiac A analysis User Interface System and Method This claim asserts priority to U.S. Patent Provisional Application No. 61 / 970,027, titled "... Each of these is incorporated herein by reference.

[0012] This application does not claim priority, but it is based on the "G" application filed on August 24, 2018. Titled "as-Elimination Patient Access Device" This may relate to U.S. Patent Application No. 16 / 111,538, which was filed in 2015. The "Gas-Elimination Patient Access" application filed on the 14th of the month This is a continuation application of U.S. Patent No. 10,071,227 titled "s Device", and This is the "Gas-Elimination Patient" filed on January 14, 2015. Patent Cooperation Treaty application number PCT / US201, titled "nt Access Device" This is a national phase entry application under Section 371 of the U.S. Patent Act, No. 5 / 011312, which is a 2 The "Gas-Elimination Patient" patent application filed on January 17, 2014 U.S. Provisional Patent Application No. 61 / 928,704, entitled "Access Device" These assert priority rights, each incorporated herein by reference.

[0013] This application does not claim priority, but it does not claim priority over the "Ex" filed on January 8, 2019. pandable Catheter Assembly with Flexible Printed Circuit Board(PCB)Electrical Pa This may relate to U.S. Patent Application No. 16 / 242,810, titled "thways", This is an "Expandable Catheter" patent application filed on July 23, 2015. Assembly with Flexible Printed Circuit Patent Application No. 1 titled "Board (PCB) Electrical Pathways" This is a continuation application of 4 / 762,944, which was filed on February 7, 2014, under the "E xpandable Catheter Assembly with Flexible e Printed Circuit Board(PCB)Electrical P Patent Cooperation Treaty application number PCT / US2014 / 15261 titled "athways" This is a national phase entry application under Section 371 of the U.S. Patent Act, filed on February 8, 2013. The "Expandable Catheter Assembly with Fl" exible Printed Circuit Board(PCB)Electri U.S. Provisional Patent Application No. 61 / 762,363, titled "Cal Pathways" These are claims of priority and are incorporated herein by reference.

[0014] This application does not claim priority, but it is based on the "C" application filed on June 19, 2018. atheter,System and Methods of Medical Us es of Same,Including Diagnostic and Trea U.S. Patent Application No. 16 / 0, titled "ment Uses for the Heart" This may relate to Patent No. 12,051, which was filed on February 20, 2015, under the name "C atheter,System and Methods of Medical Us es of Same,Including Diagnostic and Trea A US publication titled "Comment Uses for the Heart" (10,004) This is a continuation application of No. 459, which was filed on August 30, 2013, for the "Cathe ter,System and Methods of Medical Uses o f Same,Including Diagnosis and Treatment Patent Cooperation Treaty application number PCT / U, titled "Uses for the Heart" This is a national phase entry application under Section 371 of the United States Patent Act, patent no. S2013 / 057579, It was published as a pamphlet, International Publication No. 2014 / 036439, and this was in August 2012. The "System and Method for Diagnos" application filed on the 31st of the month A U.S. provisional patent application titled "ing and Treating Heart Tissue" has been filed. This claim asserts priority over Application No. 61 / 695,535, each of which is by reference. This specification is incorporated herein.

[0015] This application does not claim priority, but it does not claim priority over the "Se t of Transducer-Electrode Pairs for a Ca In cases related to U.S. design patent application No. 29 / 593,043, titled "theter" This is a patent application filed on December 2, 2013, for "Transducer Electr Divisional application for U.S. design patent D782686, titled "ode Arrangement" This is the "Catheter System" patent application filed on August 30, 2013. and Methods of Medical Uses of Same, Inc. luding Diagnostic and Treatment Uses for Patent Cooperation Treaty application number PCT / US2013 / 0575, titled "The Heart" This is a continuation of application No. 79, which is incorporated herein by reference.

[0016] This application does not claim priority, but it is based on the "D" filed on March 20, 2018. device and Method for the Geometric Deter mination of Electrical Dipole Densities U.S. Patent Application No. 15 / 926,18, entitled “on the Cardiac Wall” This may be related to item 7, which is "Device and Method for the Geometric Determination of Electrica l Dipole Densities on the Cardiac Wall” This is a continuation of U.S. Patent No. 9,968,268, titled "Device a nd Method for the Geometric Determinatio n of Electrical Dipole Densities on the This is a continuation of U.S. Patent No. 9,757,044, titled "Cardiac Wall". This is related to the "Device and Method f" patent application filed on March 9, 2012. or the Geometric Determination of Electr ical Dipole Densities on the Cardiac Wal Patent Cooperation Treaty Application No. PCT / US2012 / 028593, titled "l", under the United States Patent Law This is a national phase entry application under Section 371, filed on March 10, 2011. "Device and Method for the Geometric Det termination of Electrical Dipole Densitie U.S. Provisional Patent Application No. 61 / 451, titled "s on the Cardiac Wall" This asserts priority over Patent No. 357, which is incorporated herein by reference. To be included.

[0017] This application does not claim priority, but the "De" application filed on January 29, 2018 vice and Method for the Geometric Determinus ination of Electrical Dipole Densities o U.S. Patent Application No. 15 / 882,097, entitled "The Cardiac Wall" This may be related to the "Device" patent application filed on October 25, 2016. and Method for the Geometric Determinat ion of Electrical Dipole Densities on th In a continuation application to U.S. Patent No. 9,913,589 titled “e Cardiac Wall”, Yes, this is the "Device and Meth" patent application filed on October 19, 2015. od for the Geometric Determination of El etrical Dipole Densities on the Cardiac This is a continuation application of U.S. Patent No. 9,504,395 titled "Wall," which is 20 The patent application filed on July 19, 2013, was titled "Device and Method for the Geometric Determination of Electrical D Titled "ipole Densities on the Cardiac Wall" This is a continuation application of U.S. Patent No. 9,192,318, which was filed on August 20, 2013. The "Device and Method for the Geometric" was carried out. Determination of Electrical Dipole Dens A US publication titled "Cities on the Cardiac Wall" This is a continuation application of No. 255, which was filed on January 16, 2009, as "A Dev ice and Method for the Geometric Determi nation of Electrical Dipole Densities on Patent Cooperation Treaty application number PCT / IB09, titled "The Cardiac Wall" This is a national phase entry application under Section 371 of the U.S. Patent Act, No. / 00071, which is 20 Priority is primarily based on Swiss patent application No. 00068 / 08, filed on January 17, 2008. These are incorporated herein by reference.

[0018] This application does not claim priority, but it is based on the "M" application filed on June 21, 2018. ethod and Device for Determining and Pre sending Surface Charge and Dipole Densit U.S. Patent Application No. 16 / 014,3 entitled “ies on Cardiac Walls” This may be related to Patent No. 70, which was filed on February 17, 2017, "Metho d and Device for Determining and Present ing Surface Charge and Dipole Densities U.S. Patent Application No. 15 / 435,763, entitled “on Cardiac Walls” This is a continuation application, which was filed on September 25, 2015, for "Method and Device for Determining and Presenting Su rface Charge and Dipole Densities on Car This is a continuation application of U.S. Patent No. 9,610,024 titled "DIAC Walls," This is a patent application filed on November 19, 2014, for "Method and Device f or Determining and Presenting Surface Ch arge and Dipole Densities on Cardiac Wal This is a continuation application of U.S. Patent No. 9,167,982, titled "ls", which was filed in 2014. The "Method and Device for Determination" was published on December 23rd. mining and Presenting Surface Charge and A US article titled "Dipole Densities on Cardiac Walls" This is a continuation application of Japanese National Patent No. 8,918,158, which was issued on April 15, 2014. The "Method and Device for Determining an d Presenting Surface Charge and Dipole D A US publication titled "Entities on Cardiac Walls" This is a continuation application of No. 119, which was issued on April 9, 2013, as part of the "Method and Device for Determining and Presenti ng Surface Charge and Dipole Densities o Continuation application of U.S. Patent No. 8,417,313, titled "n Cardiac Walls" This is the "Method and Devic" patent application filed on August 3, 2007. e for Determining and Presenting Surface Charge and Dipole Densities on Cardiac Article 371 of the U.S. Patent Act relating to PCT application number CH2007 / 000380, titled "Walls" This is a national phase entry application under the relevant article, which was filed in Switzerland on August 3, 2006. This claim asserts priority to patent application No. 1251 / 06, each of which is by reference. This specification is incorporated herein.

[0019] The present invention relates to a system that may be useful in the diagnosis and treatment of cardiac arrhythmias or other abnormalities. With regard to the method, the present invention relates in particular to the diagnosis and treatment of such arrhythmias or other abnormalities. This relates to systems, devices, and methods useful for displaying cardiac activity. [Background technology]

[0020] Cardiac signals (e.g., charge density, dipole density, voltage, etc.) are measured across the endocardial surface. These change. The magnitude of these signals depends on several factors, including local tissue characteristics (e.g., Health vs. disease / scars / fibrosis / lesions) and area activation (activation) Examples include the electrical properties (for example, the "electrical mass" of the active tissue before local cell activation). The method is to always assign a single threshold to all signals across the surface. The use of this value can lead to the disappearance of low-amplitude activations or the dominance of high-amplitude activations. This can cause saturation / concentration, which can lead to confusion in interpreting the map. Failure to properly detect sexualization can lead to inaccurate identification of the area of ​​interest for therapeutic delivery, or other issues. This can lead to incomplete characterization of the bracing effect (excess or deficiency of blocks).

[0021] Continuous and holistic mapping of atrial fibrillation reveals temporally and spatially variable activation patterns. This generates a large amount of data. In the limited individual sampling of map data, arrhythmias It may be insufficient to provide a comprehensive picture of the liver, mechanism, and supporting substrate. Long-term clinician reviews of AF (Autism Spectrum Disorder) are a way to recall, piece together, and complete the "big picture." Effort may be required to achieve this.

[0022] For these and other reasons, providing an algorithmic objective analysis of conduction patterns is necessary. There is a general need for it. [Prior art documents] [Patent Documents]

[0023] [Patent Document 1] U.S. Patent No. 10,071,227 [Overview of the Initiative] [Problems that the invention aims to solve]

[0024] Embodiments of the systems, devices, and methods described herein are used to diagnose arrhythmias in patients. This may include systems, devices, and methods for interrupting or disconnecting. [Means for solving the problem]

[0025] According to one aspect of the concept of the present invention, a system for diagnosing arrhythmia in a patient is a system for diagnosing arrhythmia in a patient's heart It comprises a diagnostic catheter for insertion into the organ and a processing unit. The device is configured to record the patient's anatomical and electrical activity data. It receives recorded electrical activity data and relates the electrical activity data to anatomical data. It is configured to attach. The processing unit removes the anatomical data at the location associated with it. Includes an algorithm configured to determine the conduction velocity of polarized conduction waves.

[0026] According to one aspect of the concept of the present invention, a system for diagnosing arrhythmia in a patient is a system for diagnosing arrhythmia in a patient's heart It comprises a diagnostic catheter for insertion into the organ and a processing unit. The device is configured to record the patient's anatomical and electrical activity data. It receives recorded electrical activity data and relates the electrical activity data to anatomical data. It is configured to attach. The processing unit rotates at the location associated with the anatomical data. Includes an algorithm configured to identify rotational conduction.

[0027] According to one aspect of the concept of the present invention, a system for diagnosing arrhythmia in a patient is a system for diagnosing arrhythmia in a patient's heart It comprises a diagnostic catheter for insertion into the organ and a processing unit. The device is configured to record the patient's anatomical and electrical activity data. It receives recorded electrical activity data and relates the electrical activity data to anatomical data. It is configured to attach. The processing unit is not at the location associated with the anatomical data. Includes an algorithm configured to identify irregular conduction.

[0028] According to one aspect of the concept of the present invention, a system for diagnosing arrhythmia in a patient is a system for diagnosing arrhythmia in a patient's heart It comprises a diagnostic catheter for insertion into the organ and a processing unit. The device is configured to record the patient's anatomical and electrical activity data. It receives recorded electrical activity data and relates the electrical activity data to anatomical data. It is configured to attach. The processing unit is limited to the location associated with the anatomical data. Includes an algorithm configured to identify focal activations.

[0029] According to one aspect of the concept of the present invention, in order to generate diagnostic results related to the patient's cardiac condition The system is a diagnostic catheter for insertion into the patient's heart, and the patient's electrical A diagnostic catheter configured to record target activity data at multiple recording locations, and the recording The system includes a processing unit for receiving the recorded electrical activity data. The complexity is assessed using the collected electrical activity data. This includes an algorithm configured to run and generate diagnostic results based on an assessment of complexity. .

[0030] In some embodiments, the diagnostic results are used to assess complexity, or in terms of time and / or space. This includes an assessment of complexity fluctuations. The diagnostic results include complexity fluctuations across time and space. obtain.

[0031] In some embodiments, the complexity assessment includes an assessment of macro-level complexity.

[0032] In some embodiments, the complexity assessment represents the assessment of a portion of the cardiac chambers, and multiple recording locations The system includes recording locations at least three within the cardiac chambers, and the system records at least three peaks of the cardiac wall. Determine the electrical activity data calculated for each point, and the calculation is performed at at least three recording locations. Based on recorded electrical activity data. At least three recording locations are on the cardiac wall. It may include at least three locations. A portion of the cardiac chamber is 7 cm from the surface of the heart wall. 2 Below, 4cm 2 The following and / or 1 cm 2 This may include: at least three recording locations on the heart wall or It may include at least one offset position.

[0033] In some embodiments, the complexity assessment represents the assessment of a portion of the cardiac chambers, and multiple recording locations It includes at least 24 recording locations within the cardiac chambers, and the system has at least 64 locations on the cardiac wall. The electrical activity data calculated for each vertex is determined, and the calculation is performed at least 24 records. Based on electrical activity data recorded at location. At least 24 recording locations are, It can include 24 cardiac wall locations. At least 24 recording locations are less than It can include at least 48 cardiac wall locations. At least 24 recording locations are It can include at least 48 cardiac wall locations. At least 24 recording locations are It can include at least 48 locations within the cardiac chambers. At least 24 recording locations. This can include at least 64 locations within the cardiac chambers. At least 64 vertices are It can contain at least 100 vertices. At least 64 vertices can contain at least 5 It can contain 00 vertices. At least 64 vertices can contain at least 3000 vertices. It can include points. At least 64 vertices can include at least 5000 vertices. This is possible. A portion of the heart chamber is at least 1 cm from the surface of the heart wall. 2 , at least 4cm 2 , and / or at least 7 cm 2 It may include a portion of the cardiac chambers, including a portion of the atria. It is possible.

[0034] In some embodiments, the system calculates the electrical activity for multiple vertices on the heart wall. The target activity data is determined, and the calculation is performed using electrical activity data recorded at at least three recording locations. Based on the data. Recorded electrical activity data was recorded at multiple locations within the patient's heart chambers. Voltage data may be included, and multiple locations may be offset from the heart wall at least one This may include locations. Recorded electrical activity data is recorded at multiple locations within the patient's heart chambers. The recorded voltage data may include multiple locations, at least one location on the heart wall. This may include locations. Recorded electrical activity data was recorded at multiple locations within the patient's heart chambers. Voltage data may be included, and multiple locations may be at least one location on the heart wall and the heart. This may include at least one position offset from the wall. The processing unit is Furthermore, a second algorithm may be included, and the recorded electrical activity data is recorded The second algorithm can include voltage data and is based on the recorded voltage data. To calculate surface charge data and / or dipole density data for each of the number vertices It can be configured such that the complexity assessment is based on surface charge data and / or dipole density data. The processing unit can further include a third algorithm, and the third algorithm Gorhythm converts surface charge data and / or dipole density data into surface voltage data. It can be configured in such a way that the complexity can be evaluated based on surface voltage data.

[0035] In some embodiments, complexity is assessed using electrical activity data including 1 to 10 activations. Based on.

[0036] In some embodiments, complexity is assessed over a period of 0.3 milliseconds to 2000 milliseconds. It is based on recorded electrical activity data. The complexity assessment is based on a period of approximately 150 milliseconds. This can be based on electrical activity data recorded over time.

[0037] In some embodiments, complexity is assessed by electrical activity data including 3 to 3000 activations. The complexity assessment is based on electrical activity data, including 10 to 600 activations. This is possible. The complexity assessment is based on electrical activity data including 25-300 activations. It is possible.

[0038] In some embodiments, the complexity assessment is recorded over a period of 0.3 seconds to 500 seconds. Based on recorded electrical activity data. Complexity assessment is based on data recorded over a period of 1 to 90 seconds. This can be based on the electrical activity data obtained. Complexity assessment is performed over a period of 4 to 30 seconds. This can be based on electrical activity data recorded over time.

[0039] In some embodiments, the complexity assessment includes 2,000 to 300,000 activations. Based on electrical activity data. Complexity assessment includes 6,000 to 40,000 activations. This can be based on electrical activity data.

[0040] In some embodiments, the complexity assessment was recorded over a period of 5 minutes to 8 hours. Based on electrical activity data. Complexity assessment is recorded over a period of 15 to 50 minutes. This can be based on electrical activity data.

[0041] In some embodiments, the diagnostic results include an assessment of complexity at a single cardiac wall location. The stem can also be equipped with a display, and the system can display the patient's anatomy on the display. It can provide diagnostic results related to images of the biological structure.

[0042] In some embodiments, the diagnostic results include an assessment of complexity at multiple cardiac wall locations. The stem can also be equipped with a display, and the system can display the patient's anatomy on the display. It can provide diagnostic results related to images of the biological structure.

[0043] In some embodiments, the diagnostic results include an assessment of complexity over time. This may include an assessment of complexity over a fixed duration.

[0044] In some embodiments, the diagnostic catheter includes at least one electrode.

[0045] In some embodiments, the diagnostic catheter includes at least three electrodes.

[0046] In some embodiments, the diagnostic catheter has at least one ultrasound transducer Includes Sa.

[0047] In some embodiments, the diagnostic catheter includes multiple splines, and each spline It includes at least one electrode and at least one ultrasonic transducer.

[0048] In some embodiments, the cardiac condition includes arrhythmia. The cardiac condition includes atrial fibrillation. obtain.

[0049] In some embodiments, the cardiac condition is atrial fibrillation, atrial flutter, atrial tachycardia (tachycardia), Atrial bradycardia, ventricular tachycardia, ventricular bradycardia, ectopic, congestive heart failure, angina pectoris, arterial stenosis, and those This includes states selected from a group consisting of combinations of [the specified elements].

[0050] In some embodiments, the state of the heart changes in time, space, size, and / or state. Non-uniform activation, conduction, depolarization, and / or repolarization, irregular patterns, for example Irregularities in locality, re-entry, rotation, turning, direction, and velocity From a group consisting of patterns, functional blocks, permanent blocks, and combinations thereof Includes the state in which it is selected.

[0051] In some embodiments, the system is further configured to collect additional patient data. Therefore, the assessment of complexity is further based on additional patient data. Diagnostic catheters are used for additional patients. Diagnostic catheters can be configured to record data. The system may include at least one sensor configured to collect additional patient data. It may include at least one sensor configured to record. The S may be configured to be inserted into the patient when recording additional patient data. One sensor is positioned outside the patient's body when recording additional patient data. It can be configured as follows: The sensor may be an electrode or other sensor for recording electrical activity, a force sensor, Pressure sensors, magnetic sensors, motion sensors, speed sensors, accelerometers, strain gauges, physiological sensors Sensors, glucose sensors, pH sensors, blood sensors, blood gas sensors, blood pressure sensors, flow sensors - Sensors, optical sensors, spectrometers, interferometers, etc., for measuring size, distance, and / or thickness. A group consisting of measurement sensors, tissue evaluation sensors, and combinations thereof is selected for this purpose. It may include sensors that can detect the patient's physical and physiological information. , and / or functional information may be included. Additional patient data may include cardiac wall motion, cardiac wall velocity. , distortion of cardiac tissue, magnitude and / or direction of cardiac blood flow, vorticity of blood, cardiac valve dynamics, blood pressure, Tissue properties, such as density, tissue characteristics, and / or metabolic activity or drug intake. Tissue properties and tissue composition (e.g., collagen, cardiac muscle, fat, binding) are biomarkers of tissue characteristics. Data related to parameters selected from a group consisting of organizations, and combinations thereof. It may include the electromechanical delay, electrical properties and mechanical properties of the organization. This includes evaluating the ratio of sexes and the characteristics selected from groups consisting of combinations thereof. It is possible.

[0052] In some embodiments, the system is further configured to treat arrhythmias, and the system The device further includes an ablation catheter for insertion into the patient's heart. The ablation catheter is designed to deliver ablation energy to various locations on the heart wall. The algorithm is configured to determine at least one ablation location. It may be configured such that at least one ablation site is an ablation catheter It can include one or more cardiac wall locations to receive ablation energy. The ablation site is determined based on the complexity assessment and / or diagnostic results. This can be determined. At least one ablation site is one where complexity exceeds a threshold. It may include more than one cardiac location. At least one ablation site may be multiple It can include the most complex position within a numerically determined region of complexity. The catheter uses electromagnetic energy, RF energy, microwave energy, and thermal energy. Ghee, heat energy, cryogenic energy, light energy, laser light energy, chemistry Energy, acoustic energy, ultrasonic energy, mechanical energy, and combinations thereof To deliver one or more ablation energies selected from a group consisting of combinations It can be configured. The system supplies ablation energy to the ablation catheter. It may further include an energy delivery unit configured to supply energy. The delivery unit uses electromagnetic energy, RF energy, microwave energy, and thermal energy. - Heat energy, cryogenic energy, light energy, laser light energy, chemical energy From the group consisting of energy, acoustic energy, ultrasonic energy, and combinations thereof It can be configured to deliver one or more selected ablation energies.

[0053] The technologies described herein, along with their attributes and associated benefits, are described in relation to typical implementations. Considering the attached drawings, which illustrate the situation as an example, along with the following detailed explanation, it is most likely that It is recognized and understood. [Brief explanation of the drawing]

[0054] [Figure 1] A block diagram of a cardiac information processing system consistent with the concept of the present invention is shown. [Figure 2A] This shows a visual representation of the data structure of a cardiac information processing system, consistent with the concept of the present invention. [Figure 2B] This shows a visual representation of a portion of the data structure of a cardiac information processing system, consistent with the concept of the present invention. [Figure 3] A schematic diagram of an algorithm for performing complexity assessment, consistent with the concept of the present invention, is shown. [Figure 3A] A schematic diagram of an algorithm for performing complexity assessment, consistent with the concept of the present invention, is shown. [Figure 4] A schematic diagram of an algorithm for determining conduction velocity data, consistent with the concept of the present invention, is shown. [Figure 5] A schematic diagram of an algorithm for determining local rotational activity, consistent with the concept of the present invention, is shown. [Figure 5A] A graphic diagram of anatomical data including the neighborhood of a vertex, defined by an outer ring around the vertex, is shown, consistent with the concept of the present invention. [Figure 5B]A simplified neighborhood diagram is shown, including an outer ring of vertices arranged around a central vertex, consistent with the concept of the present invention. [Figure 5C] This shows a typical anatomical structure that exhibits propagating waves rotating around a nearby area, consistent with the concept of the present invention. [Figure 5D] Figure 5C shows a plot of activation times in the outer ring of the vertices, consistent with the concept of the present invention. [Figure 5E] Figure 5C shows a graph of the conduction velocity vectors, which is consistent with the concept of the present invention. [Figure 6] A schematic diagram of an algorithm for determining local disorder activity, consistent with the concept of the present invention, is shown. [Figure 6A] An example of a propagation wave exhibiting irregular activity, consistent with the concept of the present invention, is shown. [Figure 7] A schematic diagram of an algorithm for determining localized activation, consistent with the concept of the present invention, is shown. [Figure 7A] This shows a representative anatomical structure that exhibits localized activation, consistent with the concept of the present invention. [Figure 7B] This shows a representative anatomical structure that exhibits localized activation, consistent with the concept of the present invention. [Figure 8] This shows a display on which cardiac data can be rendered, consistent with the concept of the present invention. [Figure 9] A schematic diagram of a mapping catheter consistent with the concept of the present invention is shown. [Figure 9A] This shows an oblique anatomical view of the cardiac chamber with a mapping catheter inserted into it, consistent with the concept of the present invention. [Modes for carrying out the invention]

[0055] Herein, current embodiments of the present technology are referred to in detail, examples of which are shown in the accompanying drawings. The same reference number may be used to refer to similar components. However, the explanation is in this publication. This is not intended to limit the indications to any particular embodiment, but rather to the implementations described herein. It should be interpreted as including various forms, equivalents, and / or substitutions.

[0056] The terms "comprising" and "comprise" s) and any other form of "to have"), "having" (and "have") "have" (or any other form of "have"), "include" (and "include" (inc) "Includes" and any other form of "contains," or "contains" ) (and any form of "contains" such as "contains" and "contain") When used herein, this refers to the specified features, integers, processes, operations, elements, and / or Specifies the existence of a component, but not one or more other features, integers, processes, actions, elements, or components. It is understood that this does not preclude the existence or addition of such groups.

[0057] The terms 1, 2, 3, etc., are used herein to represent various limitations, elements, components, and domains. It may be used to describe layers and / or sections, but these limitations, elements, and components Elements, regions, layers, and / or sections should not be limited by these terms. This will be further understood. These terms refer to a single limit, element, component, area, layer, or section. Use "tion" only to distinguish it from another restriction, element, component, area, layer, or section. It is used. Therefore, the first restriction, element, component, domain, layer, or The section, without departing from the disclosure of this application, covers the second limitation, element, component, and area. It can be called a layer or section.

[0058] An element is "on top of," "attached," "connected to," or "joined" another element. When it is said that something is "attached" to another element, it means that it is directly on top of or connected to or joined to another element. It is further understood that there may be one or more intervening elements. In contrast, if the elements are separate For the element, "directly on," "directly attached," "directly connected," or "directly When it is said that elements are "contigually coupled," there are no intervening elements. Other words used in the same way should be interpreted (for example, between) (e.g., "directly between," "adjacent" vs. "directly adjacent").

[0059] When the first element is said to be "inside," "above," and / or "inside" the second element, The first element is within the internal space of the second element, within a portion of the second element (for example, within the second element) The second element may be placed on the outer and / or inner surfaces (within the wall), and these Further understanding is needed, as there can be one or more combinations.

[0060] As used herein, the term “proximity” means a second component of a first component or location. When used to describe proximity to an element or location, it refers to the proximity of the second element or location. This includes more than one location, and similarly, locations within, on, and / or within the second component or location. It should be interpreted as such. For example, if it is close to an anatomical site (e.g., the location of the target tissue) The components that are positioned are those that are positioned near anatomical sites, and similarly anatomically This includes components located within, above, and / or within the part.

[0061] "Beneath", "below", "lower", "above", Spatially relative terms such as "upper" are used, for example, in the drawing, for elements and / Or used to describe the relationship of a feature to another element(s) and / or feature(s). It is possible. Spatially relative terms include, in addition to the orientation shown in the drawing, in use and / or It is further understood that this is intended to accommodate different orientations of a device in operation. For example. If the device in the drawing is inverted, the "underside" of another element or feature and / or An element described as "below" is oriented "above" another element or feature. It can be oriented to other states (for example, rotated 90° or in other directions), as specified herein. Spatially relative descriptors used are interpreted accordingly.

[0062] As used herein, terms such as “decrease,” “decreasing,” and “decrease” are used with respect to the same meaning. This includes a decrease in quantity, including a decrease to zero. Reducing the probability of occurrence means reducing the probability of occurrence. This includes prevention. Similarly, the terms "prevent," "preventing," and "prevention" are defined as follows: Each of these terms shall include the actions of "decreasing," "decreasing," and "decrease."

[0063] As used herein, the terms "and / or" mean two specified special features, with or without the other. It should be interpreted as a specific disclosure of each of the characteristics or components. For example, "A and "B / or B" means as each is described separately in this specification, (i) A, ( ii) B, and (iii) A and B respectively should be interpreted as specific disclosures. .

[0064] In this specification, unless otherwise specified, "and" may mean "or", "Or" can mean "and". For example, it can mean that the features include A, B, or C. If revealed, the features may include A, B, and C, or any combination of A, B, and C. It is possible. Similarly, if a feature is described as having A, B, and C, then that feature is A, B, Or it may have only one or two of C.

[0065] As used in this disclosure, the expression "configured (or set up)" means, for example, depending on the context, "Suitable," "Capable," "Designed," "Adapted," "Manufactured" and It can be used interchangeably with "possible". The expression "configured (or set up)" is hard It doesn't just mean "specially designed" in terms of clothing. Alternatively, in some situations So, the expression "configured device" means that a device moves together with another device or component. It can also mean "to be able to create."

[0066] As used herein, the term “threshold” is related to a desired or undesirable state. Refers to the maximum level, minimum level, and / or range of the assigned value. In some embodiments The system parameters are above the minimum threshold, below the maximum threshold, within the threshold range of the value, and / or It is kept outside the threshold range of the value, producing the desired effect (e.g., effective treatment), and / Or to prevent undesirable events (e.g., device and / or clinical adverse events), or reduce (hereinafter, "prevent"). In some embodiments, the system parameter is: Above a threshold of 1 (for example, above the first temperature threshold to produce the desired therapeutic effect on the tissue) (to), and below the second threshold (for example, the second temperature to prevent undesirable tissue damage) It is maintained (below the threshold). In some embodiments, the threshold includes a safety margin. Determined and used to explain, for example, patient variability, system variability, tolerances, etc. When used, "exceeding the threshold" means exceeding the maximum threshold, falling below the minimum threshold, or being within the threshold range. Regarding parameters within and / or outside the threshold range. The threshold is determined by the user (e.g., the patient's clinical settings). It may be defined by the medical professional and / or by the system (e.g., by the system manufacturer). (In construction) it can be something.

[0067] The term "diameter" is used herein to describe non-circular geometry, and is explained below. It is interpreted as the diameter of a virtual circle that approximates the geometry. For example, the cross-section of a component. When describing a surface, the term "diameter" refers to a surface having the same cross-sectional area as the cross-section of the component being described. It shall be interpreted as representing the diameter of a hypothetical circle.

[0068] As used herein, the terms “long axis” and “short axis” of a component mean that the component is complete These are the length and diameter of the smallest virtual cylinder that can enclose it.

[0069] As used herein, the term “functional element” means an element that is constructed to perform a function. It is interpreted as including one or more elements that are placed. Functional elements include sensors and / or transformers. It may include a deucer. In some embodiments, the functional element delivers energy and and / or otherwise configured to treat tissue (e.g., configured as a therapeutic element) (A functional element that has been added). Alternatively or additionally, a functional element (e.g., a functional element including a sensor) The parameters are the patient's physiological parameters and the patient's anatomical parameters (e.g., tissue morphology parameters). One or more parameters such as patient environment parameters and / or system parameters. It may be configured to record. In some embodiments, a sensor or other functional element is , to perform diagnostic functions (for example, to record data used to perform diagnostics) It is configured in such a way that the functional elements perform therapeutic functions. It is configured (for example, to deliver therapeutic energy and / or therapeutic agents). In that embodiment, the functional elements are energy delivery, energy extraction (e.g., configuration) (To cool elements), delivery of drugs or other medications, manipulation of system components or patient tissues Recording or sensing parameters such as the patient's physiological parameters or system parameters. and built to perform a function selected from a group consisting of one or more combinations of these. It includes one or more elements that are arranged. The functional elements are fluids and / or fluid delivery systems. It may include functional elements such as an expandable balloon or other fluid retention reservoir. It may include a reservoir. A "functional assembly" is a device with diagnostic and / or therapeutic functions, etc. It can include assemblies that are built and arranged to perform a function. A functional assembly may include an expandable assembly. A functional assembly consists of one or more functional elements. It can include.

[0070] As used herein, the term "transducer" refers to a device that receives energy or any input. This is interpreted as including any component or combination of components that generate the output. For example, a transducer receives electrical energy and converts electrical energy (for example, electricity It may include electrodes that distribute to the tissue (based on the size of the electrodes). In some configurations, transformers A deducer converts an electrical signal into any output, such as light (e.g., light-emitting diode or electric light). (A transducer including a sphere), sound (for example, configured to transmit ultrasonic energy) A transducer containing a piezoelectric crystal, pressure, heat energy, cryogenic energy, chemical Mechanical energy (e.g., transducers including motors or solenoids) (c) magnetic energy and / or different electrical signals (e.g., Bluetooth (registered trademark)) Converts to (or other wireless communication elements). Alternatively or additionally, the transducer is physically A transducer can convert a quantity (for example, a change in a physical quantity) into an electrical signal. It may include any components that deliver energy and / or drugs to tissue, for example, A transducer is a transformer that delivers electrical energy to an organization (for example, a transformer containing one or more electrodes). Deducer), light energy into the tissue (e.g., laser, light-emitting diode and / or lens) Alternatively, a transducer (including optical components such as a prism) organizes mechanical energy. (For example, a transducer containing tissue manipulation elements) delivers acoustic energy to the tissue (for example) (including piezoelectric crystal transducers), chemical energy, electromagnetic energy, magnetic energy - and are configured to deliver one or more combinations thereof.

[0071] As used herein, the term “fluid” means a liquid, gas, gel, or lumen and / or This can refer to any fluid material, such as a material that can be propelled through an opening.

[0072] Specific features of the present invention are described in the context of separate embodiments for clarity, and in a single embodiment It is understood that the various features of the present invention may be provided in combination with other forms. Conversely, the various features of the present invention are For the sake of brevity, this will be described in the context of a single embodiment, and separately or as any appropriate subcontract. They may be provided in combination. For example, all features described in any of the claims It is understood that these can be combined in any given way (whether independently or dependently). ru.

[0073] At least some of the figures and descriptions of this invention focus on elements relevant to a clear understanding of the invention. It is simplified to align the points, but for clarity, other details that a person skilled in the art would understand. We understand that excluding elements may also constitute a part of the present invention. However, Elements such as these are well known in the art and do not necessarily lead to a better understanding of the present invention. Since this does not facilitate such matters, no explanation of such elements is provided in this specification.

[0074] The terms defined herein are used solely to describe specific embodiments of this disclosure. This disclosure is not intended to limit its scope. Terms provided in the singular are defined as clearly in the context. Unless otherwise indicated, plural forms are intended. All terms used herein are , including technical or scientific terms, unless otherwise defined herein, to those skilled in the art. Therefore, it has the same meaning as it is generally understood. It is defined in commonly used dictionaries. Terms are interpreted as having the same or similar meaning as their meaning in the context of the relevant technology. It should be, and unless otherwise clearly defined herein, it does not have an ideal or exaggerated meaning. It should not be interpreted as such. In some cases, the terms defined in this disclosure may be interpreted as such. This should not be interpreted as excluding the embodiments.

[0075] This specification describes a cardiac information system for generating diagnostic results related to the patient's cardiac condition. The system provides medical information about patients, including diagnosis, prognosis, and / or treatment. It can be used to perform procedures. The system is used to transmit cardiac signals to patients such as those with arrhythmias. It can identify lead patterns. The system is a diagnostic tool for insertion into a patient's heart. Includes a catheter for diagnostic purposes. A diagnostic catheter is a catheter with one or more functions for measuring voltage. The system may be configured to record the patient's electrical activity data, for example, if it includes electrodes. It may further include a processing unit that receives recorded electrical activity data. A unit can include an algorithm configured to perform one or more functions. For example, it generates calculated electrical activity data, complexity assessments, and / or diagnostic results. In some embodiments, the algorithm performs a complexity assessment to generate diagnostic results. In some embodiments, the complexity assessment is performed using one or more algorithms described herein. This is performed by a sm, which can be done alone or in combination with other algorithms to reduce complexity. The evaluation is performed. In some embodiments, the system is a cardiac ablation device. and / or further include therapeutic devices such as pharmaceuticals.

[0076] Referring now to Figure 1, an embodiment of a cardiac information processing system consistent with the concept of the present invention is shown. A block diagram is shown. The cardiac information processing system is shown as system 100, and the cardiac information processing A system configured to perform ping, diagnosis, prognosis, and / or treatment, or This includes, for example, arrhythmias or other cardiac conditions as described herein. To treat the patient's disease or disability. In addition or alternatively, System 100 , to instruct and / or provide devices and methods for diagnosing and / or treating cardiac abnormalities or diseases in patient P. This could be a system configured to verify. System 100 further displays cardiac activity It can be used to generate activity waves, for example, activity waves propagating across the surface of the heart. This is a dynamic display of the surface. In some embodiments, the system 100 generates a diagnostic result 1100. To accomplish. The diagnostic result 1100 represents diagnostic data related to the patient's heart condition, for example, this This is a diagnostic result based on the complexity assessment described in the specification.

[0077] System 100 includes a catheter 10, a cardiac information console 20, and a patient interface Including the module 50, it cooperates (for example, collectively) with various functions of the system 100. It may be configured to achieve the function. System 100 may include a single power supply (PWR), A single power supply can be shared by the console 20 and the patient interface module 50. Using a single power supply as described above allows leakage current to propagate to the patient interface module 50. This can lead to errors in stereotactic positioning (for example, the process of determining the location of one or more electrodes within patient P's body). The possibility of this is greatly reduced. Console 20 is as shown in Figure 1. Includes a bus 21 that electrically and / or otherwise connects various components to each other in an operable manner. .

[0078] The catheter 10 includes an electrode array 12 that can be delivered percutaneously to the cardiac chambers (HC). In this embodiment, the array of electrodes 12 has a known spatial configuration in three-dimensional (3D) space. For example, in the extended state, the physical relationships of the electrode array 12 are known or reliably assumed. The electrode array 12 may have at least one electrode 12a, or at least three electrodes. 12a may be included. The diagnostic catheter 10 also includes a handle 14 and extending from the handle 14. It includes an elongated flexible shaft 16. The distal end of the shaft 16 is radially expanded An electrode array 12, such as a possible and / or compact assembly, is attached. In this embodiment, the electrode array 12 is shown as a basket array, but the electrode array 12 In other embodiments, it can take other forms. In some embodiments, it is expandable The electrode array 12 is based on the "SYSTEM AND MET" patent application filed on August 30, 2013. HOD FOR DIAGNOSING AND TREATING HEART TI Applicant's international patent application titled "SSUE" PCT patent application number PCT / US2013 / 05 Patent No. 7579, and the "Expandable Catheter" filed on February 7, 2014. TER ASSEMBLY WITH FLEXIBLE PRINTED CIRCU International patent application titled "IT BOARD" PCT patent application number PCT / US2014 / 01 It may be constructed and arranged as described with reference to No. 5261, and each of its contents is for all eyes For the purposes of this document, the entirety is incorporated herein by reference. In other embodiments, it is extensible. The electrode array 12 includes a balloon, a radially deployable arm, a spiral array, and / or including other expandable and compact structures (e.g., elastically biased structures) It is possible.

[0079] The shaft 16 and the expandable electrode array 12 are located inside the body (e.g., inside an animal or patient P) It is inserted into the human body (such as the femoral vein) and advances through internal blood vessels such as the femoral vein and / or other blood vessels. The shaft 16 and electrode array 12 are constructed and arranged in such a manner. It can be constructed and arranged to be inserted through, for example, an electrode array 12 through a transseptal sheath or the like. When the electrode array 12 is in a compressed state, it can be slidably advanced through the lumen of the introducer into a body cavity such as a heart cavity (HC) such as the right atrium or the left atrium.

[0080] The expandable electrode array 12 can include a plurality of splines (for example, the plurality of splines elastically biased in the basket shape shown in FIG. 1), and each spline has a plurality of electrodes 12a and / or a plurality of ultrasonic (US) transducers 12b. Three splines can be seen in FIG. 1, but the basket array is not limited to three splines, and more or fewer splines can be included in the basket array. Each electrode 12a can be configured to record (for example, as described herein, record, measure, and / or sense) a bioelectric potential such as a voltage level at a position on the surface of the heart and / or at a position within the heart cavity HC (also referred to herein as "electrical activity"). The recorded electrical activity is stored as electrical activity data 120a by the system 100. The system 100 can perform one or more calculations on the recorded electrical activity data 120a to generate calculated electrical activity data 120b. The electrical activity data 120 can include the recorded electrical activity data 120a and / or the calculated electrical activity data 120b. The calculated electrical activity data 120b can include data selected from the group consisting of voltage data, mathematically processed voltage data (for example, averaged data, integrated data, classified data, data for which a minimum value and / or a maximum value is determined), and / or data mathematically processed by other means), surface charge data, dipole density data, timing data of electrical events, filtered electrical data, electrical patterns and / or template data, images formed by electrical values at multiple positions, and consist of one, two, or a combination of two or more of these. As used herein, the terms dipole density, surface charge, and surface charge density shall be used interchangeably.

[0081] The calculated electrical activity data 120b represents data representing the fact of electrical activation (also referred to herein as "activation") of heart tissue, and may include activation timing data 121. In some embodiments, the calculated electrical activity data 120b includes conduction velocity data 122, which is data representing conduction velocity, and / or conduction divergence data 123, which is data representing conduction divergence, each of which is described below. The calculated electrical activity data 120b may be associated with one or more locations of the heart referred to herein as vertices (a single location) and vertices (multiple locations). In some embodiments, the calculated electrical activity data includes data selected from the group consisting of electrical differences (e.g., deltas), averages, weighted averages, patterns and / or templates, fitness to one or more patterns or templates (e.g., best fit), "flow" between two or more images formed by electrical values at multiple positions (e.g., calculated by one, two, or more optical flow algorithms such as the Horn-Schunck and / or Lucas-Kanade algorithms), training data sets (e.g., ), and the "flow" between two or more images formed by electrical values at multiple positions (e.g., calculated by one, two, or more optical flow algorithms such as the Horn-Schunck and / or Lucas-Kanade algorithms), training data sets (e.g., ), and the "flow" between two or more images formed by electrical values at multiple positions (e.g., calculated by one, two, or more optical flow algorithms such as the Horn-Schunck Classification or categorization of electrical activity using individually acquired data such as historical data. Data analysis and / or statistical methods such as transformation, computationally optimized fit (e.g., New Machine learning or predictive analytics using multi-level networks or deep learning, cluster analysis, etc.) and consists of one, two, or more combinations thereof. Calculated electrical activity The input can include a probabilistic model that uses one or more of the aforementioned methods as input.

[0082] In some embodiments, activation is performed by an algorithm (e.g., an activation detection algorithm). The algorithm is determined by comparing electrical data with a threshold, and the gradient of the electrical data. Measurement of maximum and / or minimum, electrical data of one location and one or more nearby locations This may include comparison with electrical data of the location (e.g., weighted comparison), and combinations thereof. In some embodiments, the activation detection algorithm was filed on May 3, 2017. "CARDIAC INFORMATION DYNAMIC DISPLAY SY The applicant's international patent application, titled "STEM AND METHOD," PCT patent application number P CARD, filed in CT / US2017 / 030915 and on May 3, 2017. IAC MAPPING SYSTEM WITH EFFICIENCY ALGOR International patent application titled "ITHM", PCT patent application number PCT / US2017 / 03092 The construction and arrangement may be similar to that described in reference to item 2, and the contents of each are For all purposes, the entirety of the propagation history map is incorporated herein by reference. To promote spatial continuity, the activation detection algorithm uses the raw signal (dipole density data) Two parallel lines that take into account both the data and / or voltage data, etc.) and the spatial Laplacian signal may be included. In some embodiments, the activation detection algorithm is used to detect potential activity timing selection between, and gradient, spatial Laplacian, peak amplitude, and / or other such features, etc. As one consideration in the development of a voting scheme for multiple features, the conduction velocity is further included may be considered.

[0083] In the extension of the activation detection by adding the conduction velocity, the problem can be represented as a cost function with either regularization of the conduction velocity or an inequality constraint on the conduction velocity. In some embodiments, the activation detection algorithm creates a Gaussian probability distribution function around each detected activation, and the highest probability is in the currently detected activation. Without constraints, the propagation history can be output by maximizing the probability of activation for all channels. Alternatively, by including at least one constraint, the solution can be restricted to include physiologically reasonable conduction (e.g., less than 2 m / s), and the activation can be configured to shift slightly from the currently selected activation time. The following shows an example of how the cost function is described with the conduction velocity constrained.

[0084] [Number]

[0085] ] where P is the probability that activation occurs at a specific vertex i at time τ. The calculation of the conduction velocity depends on τ.

[0085] In some embodiments, the activation detection algorithm includes minima of the time derivative of the unipolar electrogram where the minimum separation between activations is set to a time threshold (e.g., between 50 and 150 milliseconds). (e.g., between 50 and 150 milliseconds) in the time derivative of the unipolar electrogram where the minimum separation between activations is set to a time threshold ].

[0086] In some embodiments, the activation detection algorithm determines that the minimum separation between activations is a time threshold. (For example, between 50 and 150 milliseconds) Includes local minimums or maximums.

[0087] In some embodiments, the activation detection algorithm is (0.5~1Hz)~(100 With a band passthrough of (~300Hz) or (10~30Hz)~(100~300Hz) Includes aggressive standard filtering after bandwidth pass.

[0088] In some embodiments, the activation detection algorithm determines that the minimum separation between activations is a time threshold. (For example, between 50 and 150 milliseconds) Includes local minimums and / or maximums of the time derivative. The activation detection algorithm is (0.5~1H With bandpass from (100~300Hz) or (10~30Hz)~(100~ It can further include standard filtering after aggressive bandwidth passing at 300Hz. .

[0089] In some embodiments, the activation detection algorithm determines that the minimum separation between activations is a time threshold. (For example, between 50 and 150 milliseconds) The Laplacian potential diagram after a negative fluctuation Includes Roccrossing.

[0090] In some embodiments, the minimum separation between activations is a time threshold (e.g., 50-150 mm). Includes the maximum value of the Hilbert transformed potential diagram (phase mapping) set to (seconds).

[0091] In some embodiments, the activation detection algorithm is machine learning (e.g., neural Supervised learning using networks, support vector machines, and / or deep learning. The problem may include an algorithm. In these embodiments, the algorithm is Training datasets including historical data and / or simulated data. You can use the dataset.

[0092] Each US transducer 12b transmits an ultrasound signal and receives ultrasound reflections to the cardiac chambers. This determines the range to reflective targets such as points on the surface of HC (Hydrogen-Coefficient of Human Oxide) and is used in the creation of digital anatomical models. It can be configured to provide anatomical data to be used. Recorded ultrasound data and / Alternatively, other anatomical data is stored by the system 100 as anatomical data 110. It is possible. Electrical activity data 120 (for example, activation timing data 121, conduction velocity data) (including data 122 and / or conduction divergence data 123) and / or anatomical data 110 This may be stored in the memory of system 100, for example, in the storage device 25 described below. ru.

[0093] As a non-limiting example, in this embodiment, three electrodes 12a and three US transducers The 12b is shown on each spline. However, in other embodiments, the basket The toarray has more or fewer electrodes and / or more or fewer US transduction It may include a transducer. Furthermore, the electrode 12a and transducer 12b may be arranged in pairs. Here, one electrode 12a is paired with one transducer 12b, and the spline Each comprises multiple electrode-transducer pairs. However, the concept of the present invention is this Not limited to a specific electrode-transducer arrangement. In other embodiments, all electrodes 12a and transducer 12b do not need to be arranged in pairs; some may be arranged in pairs. They can be arranged in pairs, and the others are not arranged in pairs. Also, in some embodiments, all splines are The arrangement of electrodes 12a and transducer 12b is not necessarily the same. In addition, how many In one embodiment, the electrode 12a is arranged in a first set of splines, and the transducer Array 12b is positioned in the second set of splines. Array 12 has at least four electric The electrode 12a includes, for example, at least 24 electrodes 12a, or for example, at least 48 electrodes. It is possible. Array 12 has at least three splines, for example, at least four splines It can include splines, for example, at least six splines.

[0094] In some embodiments, the second catheter, catheter 10', is catheter 1 Used in combination with 0, for example, the basket of catheter 10' or other electrode arrays. By placing them in separate cardiac chambers, multiple cardiac chambers can be mapped simultaneously. Lu 10' may have a construction similar to or different from the catheter 10 described herein. The electrode array of catheter 10' has a different configuration from the electrode array 12 of catheter 10. It can be arranged as follows. For example, the array of catheter 10' may have only 24 electrodes. It is possible, and there is no US transducer, while the array 12 of catheter 10 has 48 electrodes. It possesses 48 US transducers. Catheter 10 and / or 10' are shown in the illustration. Two or more electrode arrays, such as array 12, and a catheter located proximal to array 12. It may include a second array positioned on a shaft 16 of 10 or 10'.

[0095] The catheter 10 may include a cable 18 or other conduit, and it is a catheter Tel 10 connects to console 20 via connectors 18a and 20a, respectively, electrically and optically. , and / or configured to be connected electro-optically. In some embodiments, the cable The Ru-18 includes cables such as control cables, mechanical linkages, hydraulic tubes, and pneumatic tubes. The mechanism includes B, and a mechanism selected from the group consisting of one or more combinations thereof.

[0096] The patient interface module 50 connects one or more components of the console 20 to the patient P It can be configured to be electrically insulated from (e.g., shock or other undesirable electrical shock) (To prevent undesirable delivery of energy to patient P). Patient interface module The 50 can be integrated with the console 20, as shown in the figure, and / or so This may include separate, independent components (e.g., separate housings). Console 2 0 includes one or more connectors 20b, each connector containing a jack, plug, terminal, port This includes, or other custom or standard electrical, optical, and / or mechanical connectors. In some embodiments, connector 20b is terminated, and 10 kHz to 20 MHz Maintain a desirable input impedance across RF frequencies such as Lutz. Several implementations In this configuration, termination is achieved by terminating the cable shield with a filter. In some embodiments, the termination filter provides a high input impedance in a certain frequency range. This minimizes leakage at localization frequencies, for example, and also reduces input input across different frequency ranges. By supplying pedance, for example, to achieve maximum signal integrity at ultrasonic frequencies. Similarly, the patient interface module 50 includes one or more connectors 50b. At the very least, one cable 52 is connected to the patient interface via connectors 20b and 50b. Connect module 50 to console 20.

[0097] In this embodiment, the patient interface module 50 is an isolated stereotactic drive system Includes a 54, a set of patch electrodes 56, and one or more reference electrodes 58. Isolated stereotactic The drive system 54 isolates the localization signal from the rest of the system 100, reducing performance degradation. This prevents current leakage (e.g., signal loss) that results from this. In some embodiments, sys The separation of the localization signal from the rest of the system is approximately 500 kiloohms at the localization frequency, etc. This includes the impedance range exceeding kilohms. The isolation of the localization drive system 54 is localization Positional drift can be minimized while maintaining altitude separation between axes (as explained below). The positioning drive system 54 uses current, voltage, magnetism, acoustics, or other types of energy. It can operate as a Darity Drive. The patch electrode 56 and / or one or more reference electrodes 58 The set includes conductive electrodes, magnetic coils, acoustic transducers, and / or positioning drive systems. Other types of transducers based on the energy modality used by 54 It may consist of sensors. Furthermore, the isolated positioning drive system 54 is the same on all axes. Maintaining output at time (for example, while localization signals are present in each axial electrode pair, there are at each electrode position) (Also increases the effective sampling rate). In some embodiments, the localization sampling rate The frequency range includes speeds between 10kHz and 20MHz, for example, a sampler at approximately 625kHz. It's great.

[0098] In some embodiments, the set of patch electrodes 56 includes three pairs of patch electrodes and ribs An "X" pair with two patch electrodes positioned on both sides (X1, X2), in the lumbar region (Y1) It has one patch electrode positioned and one patch electrode positioned in the upper chest (Y2). A "Y" pair, one patch electrode placed on the upper back (Z1), and one placed on the lower abdomen (Z2) It is a "Z" pair having one patch electrode. The pair of patch electrodes 56 are any orthogonal and / or they may be arranged on a set of non-orthogonal axes. In the embodiment of Figure 1, the electrode arrangement is on patient P. The electrodes on the back are shown with dashed lines.

[0099] Reference patch electrode 58 may be placed in the lumbar / buttock region. In addition, or alternatively, reference catheter The device may be placed within internal blood vessels, such as those in the lumbar / buttock region and / or proximal vessels.

[0100] The arrangement of electrodes 56 defines a coordinate system made up of three axes, for each pair of patch electrodes 56 It is one axis. In some embodiments, the axis is non-orthogonal to the natural axis of the body. That is, from head to toe, from chest to back, and from side to side (for example, from rib to rib) The electrodes are non-orthogonal. The electrodes are positioned so that their axes intersect at the origin, such as the origin located in the heart. For example, the origin of the three intersecting axes can be placed at the center of the atrial volume. The Stem 100 is configured to provide an "electrical zero" that is located outside the heart. This can be done, for example, by positioning the reference electrode 58 so that the resulting electrical zero is outside the heart. Place it in a location (for example, a crossover from positive voltage to negative voltage at one or more localized locations) (Avoid it).

[0101] As described above, a pair of patches can operate differentially, for example, either patch of the pair Chi 56 also does not act as a reference electrode, and both are driven by system 100 between the two. This is the case when an electric field is generated. Alternatively or additionally, one or more of the patch electrodes 56 may be used. It can function as a reference electrode 58, and as a result they operate in single-wire ground mode. Any one of the pairs of patch electrodes 56 acts as the reference electrode 58 of that pair of patches, and A pair of wire-grounding patches can be formed. One or more pairs of patches are unrelated to single-wire grounding. It can be configured such that: One or more pairs of patches share a patch as a single-wire grounding reference. It may have a reference patch in which a pair of electrically connected patches are located.

[0102] Through the processing performed by console 20, the axis moves in a first direction (for example, electrode 5 It can be transformed (e.g., rotated) from a non-physiological direction based on the arrangement of 6 to a second direction. Direction 2 can include the standard left-posterior-superior (LPS) anatomical direction, for example If the "x" axis is directed from the right side to the left side of the patient, then the "y" axis is directed from the front to the back of the patient. The "z" axis is directed from the patient's caudal side to the cranial side. The placement of the patch electrode 56 and its Therefore, the defined non-standard axis is the patched axis in the resulting axis that gives normal physiological direction. It can be selected to provide improved spatial resolution compared to polar configurations (for example, (Due to favorable tissue characteristics between electrodes 56 in non-standard directions). For example, non-standard electrode 5 The placement of 6 reduces the negative impact of the lung's low impedance volume on the stereotactic field. This could result in the following. Furthermore, the arrangement of electrodes 56 is such that they are in paths of equivalent or at least similar length. It may be chosen to create an axis that passes through the patient's body along the path. An axis of similar length can be created within the body. It occupies a more similar energy density per unit distance and is more uniform along such axes. A uniform spatial resolution is obtained. Converting non-standard axes to standard directions makes it easier for the user. A simple display environment can be provided. Once the desired rotation is achieved, each axis can be scaled. For example, it is extended or shortened as needed. Rotation and scaling are predetermined (e.g.) For example, the shape and relative dimensions of the electrode array 12 (expected or known) are determined by the patch electrode. Based on comparison with measured values ​​corresponding to the shape and relative dimensions of the electrode array in the coordinate system. It is executed by performing rotation and scaling, which are relatively inaccurate (e.g., not The representation of the calibration can be converted into a more accurate representation. The representation of the electrode array 12 is shaped and By scaling, the axis direction and relative size are adjusted for much more accurate localization. , alignment, and / or other methods can be used to improve it.

[0103] The electrical reference electrodes (multiple electrodes are permitted) 58 shall be patch electrodes and / or electrical reference catheters. It may, or at least may include, the patient's "analog grounding" standard. It can function. The patch electrode 58 can be placed on the skin and function as a return of current for defibrillation. It can be used (for example, to serve a secondary purpose). An electrical reference catheter is simple It may include a polar reference electrode, which is used to enhance common-mode rejection. Unipolar reference electrode, or reference Other electrodes on the catheter are used to measure the physiological, mechanical, electrical, and / or numerical signals of cardiac signals. Calculation artifacts can be measured, tracked, corrected, and / or calibrated. Several embodiments So, these artifacts are added by breathing, heart movement, and / or filters. This is due to artifacts induced by the signal processing. Another form of the electrode can be an internal analog reference electrode, which is used for all internal catheter electrodes. It can function as a low-noise "analog ground" for the pole. Each of these types of reference electrodes is They can be placed in relatively similar locations, for example (as a catheter) near the lumbar region of internal blood vessels. and / or on the waist (as a patch). In some embodiments, system 10 0 includes a reference catheter 58 that includes a fixation mechanism (e.g., a fixation mechanism operated by the user). This is due to the displacement of one or more electrodes of the reference catheter 58 (for example, accidental or not). The fixing mechanism can be constructed and arranged to reduce unintended movement. Expander, spherical expander, circumferential expander, axially acting expander Select from the group consisting of a rotary expander and two or more combinations thereof. It may include a mechanism that performs this action.

[0104] In some embodiments, the console 20 is connected to the connector 20a, which is a defibrillator (D The FIB) includes a protection module 22, which receives cardiac information from the catheter 10. It is configured as follows. The DFIB protection module 22 has a precise clamp voltage and reduced It is configured to have (for example, minimum) capacitance. Functionally, it provides DFIB protection. Module 22 functions as a surge protector, directing the circuitry of console 20 to the patient. During the application of high energy, for example, a patient (such as one using a standard defibrillator) It is configured to provide protection during defibrillation.

[0105] The DFIB protection module 22 has three signal paths, a bioelectric potential (BIO) signal path 30, It can be coupled to the local positioning (LOC) signal path 40 and the ultrasound (US) signal path 60. Generally The BIO signal path 30 filters out noise and stores the recorded biopotential data. Furthermore, while reading the bioelectric signal (for example, recording it normally), ablation (For example, the delivery of RF energy to tissue) is possible, which is not the case with other systems. There is no. Generally, the LOC signal path 40 allows for high voltage input, while the received constant Noise is filtered from the positional data. Generally, the US signal path 60 is an ultrasonic transistor. Using the 12b, distance data is obtained from the physical structure of anatomical structures, and the cardiac chambers H It can generate 2D or 3D digital models in C, which can then be stored in memory.

[0106] The BIO signal path 30 uses an RF filter 31 coupled to the DFIB protection module 22. Includes. In this embodiment, the RF filter 31 has a low input impedance. It operates as a filter. High input impedance is preferred in this embodiment, This minimizes voltage loss from the source (e.g., catheter 10), thereby (e.g., For example, to better preserve the signal received during RF ablation. The RF filter 31 receives the biopotential signal from the electrode 12a on the catheter 10. For example, it is configured to allow the passage of frequencies below 500Hz. For example, the frequency range is 0.5Hz to 500Hz. However, RF abrasion High frequencies, such as high-voltage signals used in the system, are removed from the biopotential signal pathway 30. The F filter 31 may include a breakpoint frequency between 10 kHz and 50 kHz.

[0107] The BIO amplifier 32 is a low-noise single-wire grounded amplifier that amplifies the RF filtered signal. It may include an input amplifier. The BIO filter 33 (e.g., a low-pass filter) amplifies The BIO filter 33 filters out noise from the signal. It may include a filter. In some embodiments, the BIO filter 33 is used to ensure that the system 100 is at heart. When configured to accommodate organ pacing, etc., it includes a filter of approximately 7.5 kHz. For example, to avoid significant signal loss and / or reduction during cardiac pacing.

[0108] The BIO filter 33 may include a differential amplifier stage, which can be used to detect bioelectric potentials. Removes common-mode power line signals from the data. This differential amplifier has a baseline recovery function. It can implement this, and it removes DC offset and / or low-frequency artifacts from bioelectric signals. Remove. In some embodiments, this baseline recovery function removes one or more filters. Includes a programmable filter which may include stages. In some embodiments, fill The filter includes state-dependent filters. The properties of a state-dependent filter are the threshold and / or parameters. For example, it can be based on other levels (voltage), and the filter rate is based on the state of the filter. It changes accordingly. The components of the baseline recovery function include the baseline recovery voltage. Noise reduction techniques such as ping and / or pulse width modulation can be incorporated. Baseline The recovery function further involves measurement, feedback, and / or characterization of one or more states. The filter response can be determined. The baseline recovery function further represents the physiological signal morphology. Determine and / or identify a portion of the signal from the artifacts in the filtered response, and determine its original form or otherwise. A portion of it can be recovered by calculation. In some embodiments, the recovery of the original form is done by filling Direct subtraction of the response and / or additional signal processing of the filtered response, e.g., static, time-dependent Subtraction, multiplication, and filtering of filtered responses after existence and / or spatially dependent weighting. This may include inversion and combinations thereof. In some embodiments, baseline recovery is performed. The functionality is implemented in the BIO filter 33, the BIO processor 36, or both.

[0109] The LOC signal path 40 is connected to a high-voltage buffer 41 coupled to the DFIB protection module 22. This includes the high-voltage buffer 41, which provides a therapeutic RF ablation voltage. It is configured to handle the relatively high voltages used in the technology. For example, a high-voltage buffer is , may have a ±100V power rail. In some embodiments, each high voltage buffer 41 It has a high input impedance, for example, 100 kilohms to 10 megaohms at the localization frequency. This is the impedance of the system. In some embodiments, all high-voltage buffers 41 are When combined as a total parallel electrical equivalent, it also has a high input impedance, for example, constant The impedance is 100 kilohms to 10 megahms at a certain frequency. Several implementations In this configuration, the high-voltage buffer 41 maintains good performance over a high-frequency range. It has a range, for example, a frequency between 100 kHz and 10 MHz, for example, about 2 MHz. This is the frequency of . In some embodiments, the high-voltage buffer 41 is a passive RF filter. Excluding the input stage, for example, if the high-voltage buffer 41 has a ±100V power supply. Yes. The high-frequency bandpass filter 42 can be coupled to the high-voltage buffer 41 and used for localization. Therefore, it can have a passband frequency range of approximately 20kHz to 80kHz. In one embodiment, the filter 42 has a unity gain (for example, a gain of 1 or about 1). It has low noise.

[0110] US signal path 60 is a US isolation multiplexer, MUX61, Tx / Rx switch. A US transformer equipped with a US transformer 62, a US generation and detection module 63, and U Includes an S-signal processor 66. The US isolation MUX 61 is connected to the DFIB protection module 22. This is followed by the operation to turn the US transducer 12b on / off in a predetermined sequence or pattern. It is used for the US isolation MUX61, which is a set of high input impedance switches. When open, it separates the US system from the remaining US signal path elements and impedance The signal is sent to ground (via transducer and US signal path 60) through LOC and BIO. It decouples from the input of the path. The US isolation MUX61 also has one transmit / receive circuit. Multiple transducers 12b on the catheter 10 are multiplexed. The instrument 62 operates in both directions between the US isolation MUX 61 and the US generation and detection module 63. The US transformer 62, during ultrasonic transmission and reception by the US transducer 12b, The patient is isolated from the current generated by the US transmit and receive circuits of module 63. The S transformer 62, for example, by using a transmit / receive switch, transmits the transducer 1 Based on the operating mode of 2b, the transmitting and / or receiving electronic equipment of module 63 is selectively controlled. It can be configured to engage. That is, in transmission mode, module 63 (data It receives control signals from the US processor 66 (within processor 26), and it generates US signals. It operates and connects the output of the Tx amplifier to the US transformer 62. The US transformer 62 divides the signal into US components. Decoupled from MUX61, this selectively activates US transducer 12b. Receive mode In this configuration, the US isolation MUX61 receives reflected signals from one or more transducers 12b. The signal is then passed to the US transformer 62. The US transformer 62 generates and detects the US signal. Module 63 is coupled to the receiving electronic equipment, which then processes the reflected data signal into the US processor. It is transferred to SA66 and processed by user interface 27 and display 27a. In some embodiments, the processor 66 is used with the MUX 61 and the US transformer 62. It commands one of the associated transducers 12b to enable the transmission and reception of ultrasound. The above are operated in a predetermined order or pattern. The US processor 66 is, for example, a single Detection of the first reflection, detection and identification of multiple reflections from multiple targets, Doppler method and / or Determination of velocity information from subsequent pulses, and from the amplitude, frequency, and / or phase characteristics of the reflected signal. This may include determining tissue density information and one or more combinations thereof.

[0111] The analog-to-digital converter (ADC) 24 is connected to the BIO filter 33 of the BIO signal path 30. And coupled to the high-frequency filter 42 of the LOC signal path 40. By the ADC24, each A set of time-varying analog biopotential voltage signals is received one for each electrode 12a. These biopotential signals are transmitted via the BIO signal path 30, with each individual channel receiving a single-electrode electric current. The poles are differentially referenced to enhance common-mode rejection, filtering, and gain calibration. Furthermore, the ADC processes the individual time-varying analog localization voltage signals. The signal is received via path 40 for each axis of each patch electrode 56, and this is relative to electrode 12a. The ADC24 receives a collection of 48 (in this embodiment) localization voltages measured in a single time period. Output. The ADC24 enables noise shaping and filtering. It has high oversampling, for example, an oversampling rate of approximately 625 kHz. It has a Nyquist frequency. In some embodiments, sampling is performed around the Nyquist frequency of system 100. It operates at a frequency of more than one wave. The ADC24 is a multi-channel circuit and uses BIO signals and LOC. The signals can be combined or kept separate. In one embodiment, multi-channel As a circuit, the ADC24 has a total of 80 channels (for example, ablation It accommodates 48 stereotactic electrodes 12a and 32 auxiliary electrodes (for other processes). It may be configured as follows. In other embodiments, more or fewer channels may be provided. In Figure 1, for example, almost all elements of console 20 are (for example, UI system) (Except for 27) each channel may be duplicated. For example, console 20 may be duplicated for each channel In this embodiment, B may include a separate ADC or an 80-channel ADC. Signal information from IO signal path 30 and LOC signal path 40 is transmitted to various channels of ADC24. It is input to the jack and output from the channel. The output from the ADC24 channel is BIO signal It is coupled to either the signal processing module 34 or the LOC signal processing module 44, and these As explained below, each signal is preprocessed for subsequent processing. In this case, preprocessing is performed for processing by each dedicated processor as described below, for the received signal Prepare the number. In some embodiments, the BIO signal processing module 34 and the LOC signal The processing module 44 may be implemented entirely or partially in firmware.

[0112] The biopotential signal processing module 34 adjusts the gain and offset and / or non-dispersive low-pass A digital RF filter having a filter and an intermediate frequency band can be installed. The frequency band can exclude ablation signals and stereotactic signals. Biopotential signal processing module Lu34 can also include digital biopotential filtering, which outputs sample The rate can be optimized.

[0113] In addition, the bioelectric signal processing module 34 also includes "pace blanking". This can be done, for example, by receiving data during a time frame in which a doctor is "pacing" the heart. This is information blanking. Temporary cardiac pacing occurs, for example, within the heart, within the esophagus, and It may be implemented by inserting or applying a percutaneous pacing lead. The goal of the testing is to interactively test and / or improve cardiac rhythm and / or hemodynamics. This may be the case. To achieve the above, active and passive pacing triggers and input Algorithmic trigger determination can be performed (by system 100, etc.). The trigger determination uses channel subsetting, edge detection, and / or pulse width detection. This allows us to determine whether pacing has occurred in the patient. If necessary, pace brand King includes all channels or subchannels, including channels where detection was not performed. The set can be applied by system 100.

[0114] Additionally, the biopotential signal processing module 34 also processes ultrasonic signals and / or other unwanted signals. It includes special filters to remove signals (e.g., artifacts from bioelectric data). To obtain this, in some embodiments, edge detection, threshold Value detection and / or timing correlation are used.

[0115] The localization signal processing module 44 performs individual channel / frequency gain calibration and adjusted demodulation. Phase-dependent IQ demodulation, synchronous and continuous demodulation (without MUX), narrowband R filtering, and / or time filtering (e.g., interleaving, blanking, etc.) can be provided, and the following This will be explained. The localization signal processing module 44 may further include digital localization filtering. Then, optimize the output sample rate and / or frequency response.

[0116] In this embodiment, BIO signal path 30, LOC signal path 40, and US signal path 60 The algorithmic calculations will be performed on console 20. This does not limit the process to processing multiple channels at once, and propagation between channels. This includes measuring the delay and converting x, y, and z data into a spatial distribution of electrode positions. Then, a correction is calculated and applied to the set of positions, and the individual ultrasonic distances and electrode positions are combined. This includes calculating the detected endocardial surface points and constructing a surface mesh from the surface points. Yes. The number of channels processed by console 20 is between 1 and 500, for example, 24. The number of channels can be between ~256, for example, 48, 80, or 96.

[0117] The data processor 26 includes multiple types of processing circuits (e.g., microprocessors) and The BIO signal processing module 34 may include one or more of the memory circuits, and positioning Processing of pre-processed signals from signal processing module 44 and UTX / RXMUX61. The data processor 26 executes the necessary computer instructions to perform the task. It performs the calculations necessary to execute the functions of M100, and also performs data storage and retrieval. It can be constructed in the following way.

[0118] In this embodiment, the data processor 26 is a bioelectric potential (BIO) processor 36, It may include a line of occlusion (LOC) processor 46 and an ultrasound (US) processor 66. The processor 36 processes the recorded, measured, or sensed biopotential (e.g., from electrode 12a). The LOC processor 46 can perform the processing of localization signals. The US processor 66 receives the reflected US signal (for example, from transducer 12b). Image processing can be performed.

[0119] The biopotential processor 36 can be configured to perform various calculations. For example, BI The O processor 36 may include an enhanced common-mode rejection filter, which is bidirectional. It is capable of minimizing distortion and can be seeded with common-mode signals. BIO Processor 36 It also includes an optimized ultrasonic rejection filter and selectable bandwidth filtering. It can be configured for this purpose. The data processing step for the US signal path 60 is a biosignal process. This can be performed by the 34 and / or the bioprocessor 36.

[0120] The positioning processor 46 can be configured to perform various calculations. More details are provided below. As explained, the LOC processor 46 is based on the known shape of the electrode array 12 and the axes In contrast, electronic correction (calculation) is performed, and one or more based on the known shape of the electrode array 12. Correct for axis scaling or skew, perform "fitting", and measure The positions of the electrodes can be aligned to known possible configurations, which is subject to one or more constraints (for example) However, this is a physical constraint, and the distance between two electrodes 12a on a single spline, and two different Distance between two electrodes 12a on the spline, maximum distance between two electrodes 12a, two electrodes Optimized for the minimum distance between 12a and / or the minimum and / or maximum curvature of the spline, etc. It is possible.

[0121] The US processor 66 generates US signals via the US transducer 12b and US Various calculations related to the processing of US signal reflections received by transducer 12b It can be configured to perform the following: The US processor 66 interacts with the US signal path 60 It is configured to selectively transmit and receive US signals with the US transducer 12b. It is possible. Each US transducer 12b transmits under the control of the US processor 66. It can be set to do and / or receive mode. The US processor 66 has an electrode array 12 Two-dimensional and / or three-dimensional images of the cardiac chambers (HCs) to be positioned are obtained from the US transducer 12b. It may be configured to be constructed using reflected US signals received via US path 60.

[0122] Console 20 may also include a positioning drive circuit, a positioning signal generator 28 and positioning A drive current monitoring circuit 29 is included. The positioning drive circuit receives a high-frequency positioning drive signal (e.g., 10 It supplies frequencies such as kHz to 100kHz (10kHz to 1MHz). It drives these high frequencies. Signal-based stereotactic analysis is influenced by cellular responses (e.g., from blood cell deformation) to stereotactic data. This reduces and / or enables higher drive currents (e.g., a better signal-to-noise ratio). The signal generator 28 generates a drive signal (e.g., a sine wave) with ultra-low phase noise timing. It generates high-resolution digital synthesis of waves. The drive current monitoring circuit uses a high-voltage, wideband current source. A supply is provided, which is monitored to measure the impedance of patient P.

[0123] The console 20 may also include at least one data storage device 25, and various Type of recorded, measured, sensed, and / or calculated information and data, as well as console 20 It stores program code that embodies the available functions.

[0124] Console 20 is also configured to output the results of stereotactic, biopotential, and ultrasound processing. It may include a user interface (UI) system 27. It may include at least one display 27a, and such results may be 2D, 3D Render graphically using D, or a combination thereof. In some embodiments The display 27a can be independently configured for viewing direction, zoom level, pan position, etc. View / camera properties, as well as object properties such as color, transparency, brightness, and luminance. Includes two simultaneous views of 3D results with an element. UI system 27 allows one or more users to enter It can include force components, such as a touchscreen, keyboard, or joystick. , and / or mice.

[0125] Console 20, or another component of System 100, is an algorithm of the complexity shown. It may include one or more algorithms such as M600. The complexity algorithm 600 is shown in Figure 3. Refer to the following and include algorithms such as the one described below. Zoom 600 may include one or more algorithms, for example, CV algorithm 200. LRA algorithm 300, LIA algorithm 400, FA algorithm 500, and / or one or more of the 600 complexity algorithms, as described below. Gorhythm 600 identifies, quantifies, categorizes, and / or identifies cardiac conduction patterns or characteristics. It can be evaluated by other methods, and in this specification, diagnostic information and diagnostic results 1100 are generated. The complexity algorithm 600 evaluates complexity over time and / or space, and / or This can generate an assessment of the variation in complexity over time. In some embodiments, the complexity The Gorhythm 600 and / or other algorithms of System 100 include bias. In some embodiments, the algorithm is biased towards false positives (for example, when multiple complex regions are involved). In contrast to not classifying something as messy, there is a tendency to mistakenly identify simple areas as complex. This includes bias. In some embodiments, the algorithm includes bias for false negatives. In some embodiments, the algorithm of system 100 is set by a clinician and and / or adjusted ("set" in this specification) bias, for example, system 100 It creates a bias towards the specific preferences of clinicians.

[0126] The complexity determined by the algorithm of the concept of the present invention is otherwise simple and repetitive. A return-and-return, consistent pattern of electrical activity, an deviation from expected or normal motion. Including dissociation. In the electrical activity of the heart, the expected or normal movement of the cardiac chambers is called sinus rhythm. It is a coordinated activation of the tissue that is detected through consistent repetition, originating from a certain location (such as the sinoatrial node). It begins and propagates smoothly along the cardiac chambers. Complexity includes any deviations and lacks consistency (e.g., For example, activation time, amplitude, direction, and / or repetition rate, and / or coordination / sequence (e.g.) For example, it interferes with the time and / or direction of activation. The tissue area self-activates electrical activation. Initiation (automatic), otherwise may interrupt coordinated activation. Increased susceptibility to infection, scarring. Scarring, disease, and / or other heterogeneous properties (e.g., fibrosis, various fiber orientations, various Areas of tissue that may have a pathway from the endocardium to the epicardium are, as mentioned above, cardiac activity This introduces dynamic complexity. The regions where complexity arises disrupt the expected conduction in a consistent manner. In some cases, conduction is redirected in a different direction, resulting in a decrease in amplitude, but the activity remains active. In some cases, the same redirection may occur with each transformation. Alternatively, it may be a region that demonstrates complexity (for example). (identified by the algorithm of system 100) the expected conduction is probabilistic or It may interfere in a probabilistic way (for example, like random variation), but in that way This deals with recognizable statistical movements in a way that interferes with conduction. For example, modified conduction is X% For time 1%, a distinctive method is used, and for time Y%, a second, different, distinctive method is used. And it can be identified through the region. In some embodiments, Z% (where Z<100) With respect to time, activation shows normal conduction, but that region is affected by system 100. For a given portion of time, it remains complex due to one or more modified forms of conduction. It is identified as such.

[0127] The algorithm of the present invention is one in which multiple domains of complexity interact or do not interact. This combines to create further complexity throughout the cardiac chambers, thereby increasing the overall complexity across the cardiac chambers. It can be configured to identify cases where the degree increases, as described below with reference to Figure 3A. Because organ tissues have refractory period (inactivity) propagation characteristics, this affects the order and timing of activation. The complexity it imposes has a sustained / permanent effect on subsequent activation, both temporally and spatially, across a wide range of domains. This may result in an increase in the number of unique or distinct zones of autonomy or heterogeneity. (Complexity of tissue mediation), the resulting electrical activation becomes increasingly complex (e.g.) For example, the complexity of tissue mediation and the increased complexity related to connectivity, and the temporal and spatial relationship of cardiac tissue It is linked to propagation properties, established by preceding changes in conduction, and influences subsequent changes in conduction. As complexity increases, the complexity related to coupling, based on simple electrical measurements, shifts from the complexity of the structure to the complexity of the tissue. The ability to identify the complexity of the intervention becomes more difficult. System 100 is used over time and throughout space. It can be configured to collect more information across (for example, simultaneously), and the collected The additional information is one or more that decipher the local, regional, and overall complexity across the cardiac chambers. Supports algorithms.

[0128] The complexity algorithm 600 uses computed electrical activity data 120 representing multiple vertices. Based on b, complexity can be assessed, for example, by the relevant recorded electrical activity data The 120a records at least three locations within the cardiac chambers (e.g., on the cardiac wall and / or heart). Includes data recorded from (offset from the visceral wall). In some embodiments, The recorded electrical activity data 120a is located at at least one point offset from the wall of the heart. The location includes (for example, at least one non-contact recording). In some embodiments, the recording The generated electrical activity data 120a is located at at least one location on the wall of the heart (for example, a small Includes at least one contact record. In some embodiments, recorded electrical activity data T120a is located at least one position offset from the wall of the heart, and on the wall of the heart at least one location (for example, at least one contact record and one non-contact record, Includes "hybrid"). In some embodiments, each of the heart walls on which contact-based measurements are taken. Regarding location, system 100 is biased to categorize that location as a vertex. It will be done.

[0129] In some embodiments, algorithm 600 includes a second algorithm, which is: For example, if the complexity analysis is based on surface charge data and / or dipole density data, then the data is recorded. Based on the recorded electrical activity data 120a (e.g., recorded voltage), each of the multiple vertices The system is configured to calculate surface charge data and / or dipole density data for each. Surface charge data and / or dipole density data were published on April 9, 2013, in "ME THOD AND DEVICE FOR DETERMINING AND PRES ENTING SURFACE CHARGE AND DIPOLE DENSITI The applicant's U.S. patent application, titled "ES ON CARDIAC WALLS", is 8,417, Issue 313, and the "DEVICE AND METHO" published on August 20, 2013 D FOR THE GEOMETRIC DETERMINATION OF ELE CTRICAL DIPOLE DENSITIES ON THE CARDIAC calculated as described in U.S. Patent No. 8,512,255, entitled "WALL", and each content is hereby incorporated by reference in its entirety for all purposes. In some embodiments, algorithm 600 includes a third algorithm, which is when the complexity analysis is based on surface voltage data, converts surface charge data and / or dipole density data to surface voltage data.

[0130] In some embodiments, algorithm 600 performs a complexity assessment over a relatively small portion of the patient's heart (e.g., a relatively small portion of the patient's heart chamber), e.g., a portion representing up to 7 cm of the heart wall, e.g., a portion representing up to 4 cm 2 of the heart wall, e.g., a portion representing up to 1 cm 2 of the heart wall. 2 In these embodiments, the electrical activity can be recorded from at least three recording locations (e.g., by electrode 12a), and the calculated electrical activity data 120b can be determined for at least three vertices (as described in this specification). In some embodiments, at least three recording locations include at least three locations on the heart wall (e.g., via contact-based recording). In some embodiments, at least one recording location is offset from the heart wall (e.g., non-contact mapping). In some embodiments, algorithm 600 uses voltage data and / or dipole density data to perform a complexity assessment of a small portion. In some embodiments, the analysis of a small portion of the patient's heart is performed using system 100 and the related method described below with reference to FIGS. 9 and 9A.

[0131] In some embodiments, the algorithm 600 measures the moderate or large portion of the patient's heart. Perform an assessment of complexity across various regions, for example, the small amount of cardiac wall tissue (e.g., the wall tissue of the atrial region of the heart). At least 7cm 2 A portion of a patient's heart, for example, with a minimum surface area of ​​1 cm². 2 For example, 4c m 2 For example, 7cm 2 In these embodiments, electrical activity occurs within the heart (for example, in a single It can be recorded from at least 24 locations (for example, by electrode 12a) within one cardiac chamber. The calculated electrical activity data 120b can be determined for at least 64 vertices. In some embodiments, electrical activity is offset from the heart wall (e.g., non-contact). (In the blood flowing through the base record) with or without additional recording, At the very least, it can be recorded from 24 locations on the heart wall (for example, via contact-based recording). In these embodiments, electrical activity occurs at at least 48 locations on the cardiac wall, or at least a small number of locations. At the very least, it can be recorded from 64 locations of the heart. In some embodiments, electrical activity It is recorded from both a position on the heart wall and a position offset from the heart wall, for example. The data is collected from at least 24, at least 48, or at least 54 locations within the cardiac chambers. This is the case when recording is made from contact and non-contact positions. In these embodiments, the calculated electricity The activity data 120b has at least 100 vertices, for example, at least 500, and at least This can be determined for at least 3000 and / or at least 5000 vertices.

[0132] In some embodiments, the complexity algorithm 600 calculates various depths of the organization (e.g., Data is incorporated through layers. In thicker tissues, electrical conductivity can change through thickness. Tissue elongation and / or strain can also affect the conductive properties of the tissue. Using the measurement, recording, and / or calculation of electrical or biomechanical data passed through, The accuracy and / or singularity of the misuse algorithm 600 can be improved. In the embodiment, the surface charge density and / or dipole density are calculated through the thickness of the tissue in the cardiac chamber. The calculated data is then used as input to the complexity algorithm 600. In some embodiments, the surface charge density and / or dipole density were released on March 20, 2018. Titled, "DEVICE AND METHOD FOR THE GEOMETRY C DETERMINATION OF ELECTRICAL DIPOLE DEN The applicant's concurrently pending claims, titled "SITIES ON THE CARDIAC WALL" It was decided to describe it in U.S. Patent Application No. 15 / 926,187, and its contents are The entirety of this is incorporated herein by reference for all purposes.

[0133] The complexity algorithm 600 considers one or more properties, such as time, space, size, and / or changes in the electrical, mechanical, functional, and / or physiological properties of the heart as its condition changes It can be evaluated. Research on the movement, function, and other characteristics of the heart over the past several decades. This has led to a substantive understanding of what is considered "standard," such as cardiac arrhythmias. The state of the heart shows deviations from the standard in many ways, and these deviations are complex algorithms It can be quantified, certified, and / or evaluated by Zoom 600.

[0134] In some embodiments, variations in time or temporal repetition and / or stability (e.g., Measurement of temporal regularity and / or irregularity indicates the presence of cardiac arrhythmia. Electrical characteristics (e.g.) If, period length, dominant frequency, harmonic organization, waveform "energy" division or measurement, Canon entropy, waveform bias within a time window, temporal waveform recurrence, regularity, and / or Higher-order statistics of electrical data such as kurtosis are measured by system 100 or determined by other means. These characteristics can be determined and are included in the evaluation performed by the complexity algorithm 600. It is possible. System 100 can determine these variables using a tool. The tool is used for interval analysis, Fourier transform, Hilbert transform or other transforms, and wavelets. This includes analysis, and combinations thereof.

[0135] Mechanical and / or functional (referred to as "mechanical" in this specification) are evaluated by algorithm 600. The characteristics may include the timing of the deflection of the cardiac wall over time. In some embodiments, System 100 determines, and algorithm 600 determines the combination of electrical and / or mechanical data. In addition, we evaluate, for example, the electromechanical delay (which can also vary as a function of time).

[0136] In some embodiments, the algorithm 600 is determined by the system 100. Evaluate the magnitude and / or variation in the state of the characteristics. For example, the evaluated electrical characteristics are heart This can include evaluation of electrical activity on the surface, such as RMS amplitude, inter-vertex amplitude, and vertex shadow. This involves evaluating the peak-negative amplitude and combinations thereof. The evaluated mechanical properties are as follows: This may include the overall or average deflection of the cardiac wall through one or more phases of the cardiac cycle. In this embodiment, the combination of electrical and mechanical data is the electrical magnitude, the mechanical magnitude Includes ratio to performance and / or functional efficiency.

[0137] In some embodiments, algorithm 600 is used to analyze spatially or one or more characteristics. The variation in the direction is evaluated. For example, the electrical characteristics to be evaluated are (e.g., a single electrode) Directive dipoles formed in different directions (determined from data recorded by) conduction This may include velocity direction analysis, spatial waveform analysis, and combinations thereof. In some embodiments, The Laplacian operator is recorded from the electrical activity data of multipolar and / or fully polarized catheters. Applied to -120a, it can provide computational data for evaluation by algorithm 600. .

[0138] In some embodiments, the algorithm 600 considers time, space, size, and / or state. The variation of one or more characteristics is evaluated with respect to two or more of the states. In some embodiments, Algorithm 600 evaluates two or more of these simultaneously changing factors, such as spatiotemporal variations. It is worthwhile. In these embodiments, algorithm 600 evaluates the electrical characteristics of interest. Certain patterns (for example, localized patterns, rotational patterns, irregular patterns, directional patterns) It can determine whether a turn and / or timing pattern occurs. Algorithm M600 exhibits one or more of the following characteristics in a spatiotemporal manner, such as an activation sequence or conduction pattern. The characteristic features or patterns can be evaluated, and the characteristics can be evaluated through a limited "gap" or opening. "Generating" propagation, geographically constrained swirling reentry, and other irregular conduction patterns ( For example, patterns in which time and space change, rotational properties centered on a central core or obstacle, and It is a localized activation that spreads from a single location. Algorithm 600 is the conduction velocity This can include evaluating changes (e.g., magnitude and / or direction). Algorithm 600 This involves performing one or more qualitative and / or quantitative analyses of these characteristics to provide an assessment of complexity. It can be provided.

[0139] The complexity assessment provided by algorithm 600 is evaluated at each position being assessed (for example, This may include a binary measurement of whether complexity occurred one or more times at each vertex. The complexity assessment provided by Zoom 600 is a static level of complexity over a certain period of time. For example, including sum, mean, median, variance, standard deviation, and / or percentile levels. This is possible. The determined static level calculates and / or displays a subset range of static data. Thresholding is performed for this purpose. The complexity assessment provided by algorithm 600 is based on This may include an assessment of temporal (e.g., over one or more periods) variations in complexity, for example, This is an evaluation of changes in degree, frequency, extent, percentile, and / or probability. Complexity Algorithm 6 00 sequentially evaluates multiple complexities, for example, as described below with reference to Figure 8, "Lori This can be done using a "complexity window". Multiple complexity evaluations involve multiple static quantities over time. It is possible to include an assessment of miscellaneous properties.

[0140] The complexity algorithm 600 evaluates complexity (e.g., changes in complexity) and uses multiple perspectives. It can generate results that are used for specific purposes (e.g., diagnostic result 1100). For example, algorithm 600 is an assessment of the stability and / or consistency of complexity, and / or other arrhythmia occurrences. This is based on the analyzed recording duration of a few minutes or less (e.g., duration of less than 10 minutes). It can be provided. The evaluation is in the realm of consistent complexity and the realm of temporary or intermittent complexity. It is possible to distinguish between them. Consistent regions can be associated with the characteristics of specific tissue substrates. Cardiac system Therefore, in areas where the tissue matrix is ​​anisotropic, heterogeneous, abnormal, or diseased, the electrical activity at that tissue location is affected. Activities may consistently experience fluctuations and / or complexity. However, within the bounds of a normal organization. The region is also caused by the complex downstream interactions of propagating wavefronts resulting from the anisotropic region of the tissue matrix. You may see fluctuations or other complexities (such as wave collisions, interference, fusion, and functional blocking). This complexity is a "functional" effect, and these are due to the electrophysiological interactions of the propagating waves. The waves may interfere or interact in complex ways, often intermittently. (Cardiac tissue) Because it remains in a refractory (unable to reactivate) state for a certain period after each activation, the wave of activation passes through. Functional effects occur not only during the moment of exposure, but also over a long period afterward. The final result is that the complexity of cardiac tissue activation is identified by the complexity algorithm 600. Therefore, it is possible that it may occur in areas where the tissue itself is neither abnormal nor diseased, but other tissues This is due to a previous complex interaction that occurred at that location. Interventional complexity (or mechanical complexity) recurs probabilistically at the same location. Functional complexity is location and The frequency of occurrence at a given location can vary. The complexity algorithm 600 is shown in Figure 3A. Refer to the patterns of consistency, stability, reproducibility, and / or complexity described below. It can be configured to evaluate and distinguish between fixed substrate-mediated complexity and functional complexity. .

[0141] Using the complexity algorithm 600, the delivered treatment (for example, as described below) Therapy subsystem 800 provides RF or other cardiac abrasive treatments. Determine the electrical changes resulting from () the complexity of the timing before, during, or between therapeutic activities and / or Using a comparison of complexity consistency (hereinafter referred to as “complexity”), the electrogenic properties of the delivered treatment It may show scientific effects. Algorithm 600 provides comparisons in the form of mean difference plots. This can be done. Therapeutic events can last for a short time (a few seconds, at one or a few locations) or up to a few minutes (abdominal). (For broader operations such as ration lines, loops, cores, boxes, etc.) The longer the therapeutic activity or interval, the greater the change may be in the comparison. In some embodiments, system 100 includes cause (treatment) and effect (before treatment and after treatment). Real-time feedback (e.g., during treatment) of complexity assessment (including subsequent complexity fluctuations). The system provides a complexity assessment (e.g., recorded electrical activity data). The complexity calculation via algorithm 120a and algorithm 600 is performed in a relatively short time (e.g., 1 It may be configured to be delivered in less than 0 minutes or less than 5 minutes, and as a result, clinicians can provide therapeutic treatment. The interval time is reduced, and the complexity after each interval is evaluated. In these embodiments, This allows for the avoidance of unnecessary ablation and / or shortens the overall procedure time. It is possible.

[0142] The complexity algorithm 600 processes complexity data in real time (for example, complexity assessment). It can be configured to generate value output, and as a result, complexity data (e.g., diagnostic results) The result (1100) can also be shown dynamically in real time. For example, system 100 is electric The atmospheric activity data 120a can be recorded and processed, and the algorithm 600 records The activities described can be explained below, for example, using a rolling window (see Figure 8 for an example). (For example, analysis can be performed using time windows with durations of 5 to 60 seconds.) Rhythm 600 records electrical activity data 120a over the total duration evaluated. By continuously analyzing the data, it provides an assessment of multiple complexities, and electrical activity data 120 As the record of 'a' continues, new data is added and the oldest data is removed. Complex Gender assessment (e.g., assessment of multiple complexities provided in video format) is performed in real time. For example, it may be provided with a short processing delay, for example, during treatment (ablation, etc.) When the treatment achieves the desired outcome (to produce the desired effect such as an electrical block) (When sufficient energy is supplied), and / or the treatment is modified to achieve the treatment goal, Alternatively, dynamically determine other methods to improve efficiency. Alternatively or additionally, provided The complexity assessment was performed one or more times after the relevant recording of electrical activity data 120a stopped. It can be visualized (for example, in regeneration mode), additional treatment can be performed, and / or treatment can be modified. do.

[0143] The complexity algorithm 600 considers two distinct clinical procedures (e.g., the first clinical procedure). Electrical activity data 120 (and / or below) recorded during the subsequent second clinical procedure The complexity assessment can be provided based on additional patient data (150) described below. Mu600 can provide one or more complexity assessments for each clinical procedure, for example For example, evaluation from two different procedures (e.g., evaluation performed by algorithm 600) This allows for comparison between the two. The second clinical procedure is performed several days after the first clinical procedure. This can be done over several weeks, months, or even years, according to algorithm 600. The comparative evaluation involves the therapeutic effect of the first treatment and the recovery of cardiac tissue (e.g., healing) between treatments. Alternatively, the adaptation of cardiac tissue can be evaluated. Cardiac tissue may have altered electrical properties (e.g., electrical Patterns, rhythms, etc. that have been changed due to remodeling, etc., and / or changes to the structure of the mechanism It can be adapted in response to mechanical properties (e.g., function), and each can be pulled by the aforementioned treatment procedures. It is brought about. The technique used in the second clinical procedure is provided by algorithm 600. Based on the above evaluation (for example, the form of diagnostic result 1100), the first treatment can be performed. These include tissue responses to the treatment provided (e.g., the electrical and mechanical responses mentioned above).

[0144] Algorithm 600 is described above as analyzing electrical activity data 120. However, in some embodiments, the algorithm 600 is used for evaluation by the system 10 Further analysis of "additional patient data" recorded by 0 (for example, complexity assessment is , additional patient data 150 recorded by system 100, and the above electrical activity data (Based on data 120 and anatomical data 110). For example, system 100 is a sensor It may include one or more functional elements composed of such elements, for example, the functional element 9 of the catheter 10. 9. Functional elements 899 and / or systems of the therapeutic catheter 800 as described below. There are 100 functional elements and 199 functional elements of the catheter 10, including the electrode array 12. An expandable spline (illustrated) and / or one or more sensors located on shaft 16 It may include the following: The functional element 199 of system 100 is in close proximity to the patient (for example, Sensors placed on the patient's skin or relatively close to the patient and / or placed inside the patient This may include sensors that are placed (for example, temporarily or chronically under the patient's skin). In some embodiments, one or more electrodes 12a and / or ultrasonic transducers 12b It is configured to record an additional 150 patient data entries.

[0145] In some embodiments, sensor-based functional elements 99, 199, and / or 899 This includes electrodes or other sensors for recording electrical activity, such as force sensors, pressure sensors, and magnetic sensors. S, motion sensors, speed sensors, accelerometers, strain gauges, physiological sensors, glucose sensors pH sensors, blood sensors, blood gas sensors, blood pressure sensors, flow sensors, optical sensors , spectrometers, interferometers, measuring sensors for measuring size, distance and / or thickness, From tissue assessment sensors, and groups consisting of one, two, or more combinations thereof Includes the selected sensors.

[0146] System 100 (for example, catheter 10, functional element 199, functional element 8) Additional patient data recorded (via 99 and / or other sensors of the system 100) This may include the patient's mechanical information, the patient's physiological information, and / or the patient's functional information. Additional data recorded by Stem 100 is collected from patients selected from the following groups. The data may include information on lapertality, and the group may include information on cardiac wall movement, cardiac wall velocity, and cardiac tissue strain. Furthermore, the magnitude and / or direction of cardiac blood flow, blood vorticity, cardiac valve dynamics, blood pressure, and tissue properties were For example, density, tissue characteristics, and / or bio-characteristics of tissues such as metabolic activity or drug intake. The markers are tissue properties, tissue composition (e.g., collagen, cardiac muscle, fat, connective tissue), and It consists of one, two, or more of these in combination.

[0147] As explained above, algorithm 600 performs an assessment of one or more complexities. The value is included in the analysis performed, which includes both electrical activity data 120 and additional patient data 150. In some cases, this additional patient data can be used as a basis. In some embodiments, The complexity assessment performed by Lugorism 600 involves the electromechanical delay and electrical characteristics of an organization. This includes an evaluation of one or more of the ratios of the magnitudes of the properties and mechanical properties, and combinations thereof.

[0148] The additional patient data 150 also includes previous data from the same patient (e.g., during previous treatments). (Data collected by) or a set of historical patterns of patients other than those who have been diagnosed or treated. It may include previous data from [source]. The data can be used to form a computational model, and In the computational model, existing patient data is fitted, classified, and ranked. They are prioritized, optimized, and / or evaluated as described above.

[0149] The diagnostic result 1100 is the measured data and / or analysis of the measured data (for example, (Analysis of recorded electrical activity data 120a and / or anatomical data 110) It may include data such as the diagnostic result 1100 may be provided in one or more forms (e.g. For example, if it is displayed on display 27a, (for example, provided to the patient's clinician) (e.g., provided audibly by the speaker of system 100) and / or (e.g., system The report may be provided printed by a printer (M100). The diagnostic result 1100 is It can be used by clinicians to customize patient treatment, for example, cardiac In ablation procedures, the location to be excised can be determined, for example, "CA THETER, SYSTEM AND METHODS OF MEDICAL USE S OF SAME,INCLUDING DIAGNOSTIC AND TREAT Titled "MENT USES FOR THE HEART," on February 20, 2015 As described in the applicant's concurrently pending U.S. Patent Application No. 14 / 422,941, Its entire contents are incorporated herein by reference for all purposes.

[0150] In some embodiments, the diagnostic result 1100 indicates the location of a single heart wall or multiple heart walls This is based on a complexity assessment performed by the complexity algorithm 600 for the given position. The diagnostic results 1100 for one and / or multiple locations are (for example, via the display 27a) (The patient's anatomical structure is shown to the user (e.g., the patient's clinician) by referring to images of the patient's anatomical structure. The diagnostic result 1100 provides an assessment of complexity over time, for example, the complexity over a given period of time. It can include an evaluation.

[0151] As described above, System 100 provides medical treatment related to the patient's arrhythmia or other cardiac condition. It may be configured to perform procedures (e.g., diagnosis, prognosis, and / or treatment). M100 performs medical procedures on patients with cardiac conditions selected from the following group. The group can be configured to include atrial fibrillation, atrial flutter, atrial tachycardia, atrial bradycardia, ventricular tachycardia, and cardiac Ventricular bradycardia, ectopic, congestive heart failure, angina pectoris, arterial stenosis, and one, two, or both of these. It consists of more than the above combinations. In some embodiments, system 100 is time, space , heterogeneous activation in which the size and / or state (e.g., combination of speed, etc.) changes, Perform medical procedures on patients exhibiting conduction, depolarization, and / or repolarization of the patient's heart. The activity may include patterns that can be detected or mapped by system 100. For example, patterns include localization, re-entry, rotation, swirling, and irregularity (e.g., direction and (or in terms of speed), functional blocks, permanent blocks, and combinations thereof Selected from the following group.

[0152] System 100 treats a patient (for example, treats one or more cardiac conditions in a patient). ) may include a device or drug (e.g., a pharmaceutical product), and a therapeutic subsystem 800. In the embodiment shown in 1, the treatment subsystem 800 includes a treatment catheter including a shaft 860. It includes 850, which uses standard intervention techniques to deliver one or more doses through the patient's vascular system. It can be configured to advance into the heart chambers of the patient. In some embodiments, shaft 860 The distal portion, although not shown in the illustration, is a standard part used in left atrial ablation procedures. It is advanced into the patient's left atrium via a transseptal sheath such as a Vice catheter. Therapeutic catheter 85 0 includes the therapeutic element 870 at the distal end (indicated) or at least in the distal portion of the shaft 860. The therapeutic element 870 may include one or more therapeutic elements, for example, one that delivers energy. A device configured to excise cardiac tissue (e.g., excision energy delivered to the heart wall) It is an energy delivery element of more than one. The therapeutic element 870 is an array of therapeutic elements (e.g., a line The therapeutic element 870 may include a shape or other array. The therapeutic element 870 uses radio frequency (RF) or other electromagnetic energy. It may include one or more electrodes configured to deliver energy to tissue. In that embodiment, the therapeutic element 870 emits energy in a form selected from the group consisting of the following. The group comprises one or more energy delivery elements configured to deliver RF energy - and / or electromagnetic energy such as microwave energy, heat energy and / or poles Thermal energy such as low-temperature energy, optical energy such as laser light energy, ultrasonic energy Acoustic energy such as ghee, chemical energy, mechanical energy, and combinations thereof It consists of the following. In some embodiments, the therapeutic element 870 is applied to the patient's cardiac tissue or other tissue. One or more drug delivery elements configured to deliver a drug (e.g., pharmaceuticals) (e.g., Includes one or more needles, ion introduction elements, and / or fluid jets.

[0153] The therapeutic subsystem 800 may further include an energy delivery unit, EDU810. It supplies energy to one or more therapeutic elements 870. The EDU810 consists of the following: It can supply one or more forms of energy selected from the group, and the group is RF energy Electromagnetic energy such as ghee and / or microwave energy, heat energy and / or Thermal energy such as cryogenic energy, optical energy such as laser light energy, ultrasonic energy Energy such as acoustic energy, chemical energy, mechanical energy, and combinations thereof. It consists of the following: Alternatively or additionally, EDU810 contains a drug in one or more therapeutic elements 870. It can be provided, for example, if the therapeutic element 870 includes a drug delivery element as described above. That's right.

[0154] In some embodiments, the treatment subsystem 800, the treatment catheter 850, and / or EDU810 is a document submitted on February 20, 2015, titled "CATHETER, SYSTEM M AND METHODS OF MEDICAL USES OF SAME,IN CLUDING DIAGNOSTIC AND TREATMENT USES FO The applicant's concurrently pending U.S. Patent Application No. 14 / 422, titled "R THE HEART" The construction and arrangement are similar to those described in No. 941, and the entire content is as follows: This is incorporated herein by reference.

[0155] In some embodiments, the treatment subsystem 800 is used to obtain the diagnostic result 1100 (for example) Based on the results of the complexity assessment provided by algorithm 600, the patient To treat. For example, ablation energy is applied to one or more locations (for example, the above 1 It is delivered to the heart wall at more than one vertex, where the complexity is assessed at the level of complexity relative to the location. The system determines whether the threshold is exceeded (for example, above it), and treatment is administered if the threshold is exceeded. It is delivered to all locations. In some embodiments, in the region of multiple vertices, One vertex is selected for the sequence, and there the system 100 (for example, algorithm 6) Determine the maximum level of complexity that exists (through 00) (e.g., "local maximum" is excised) The level of maximum complexity can be either absolute maximum or relative maximum.

[0156] In some embodiments, the treatments provided by the system 100 (e.g., one or more) Ablation energy delivered to the apex is, for example, manual (clinician-driven), automatic ( For example, system 100 driven), and / or semi-automatic (for example, a clinician and system 100) In the combined drive mode, it is delivered in a closed-loop manner. Closed-loop operation is therapeutic Operation of the therapeutic element 870 to the position where it will be operated (e.g., by a clinician and / or by the system 100) (via a robotically operated treatment device 850) and / or supplied energy This may include setting the level.

[0157] Referring to Figures 2A and 2B, the data structure and data are consistent with the concept of the present invention. Visual representations of parts of the structure are shown below. As described above, system 100 is a cardiac chamber H The size and shape of C are measured and recorded to approximate, for example, the shape of the cardiac chambers HC during diastole. It may provide. In some embodiments, the system 100 provides ultrasound to the catheter 10. Cardiac chamber HC is measured via the lanceducer 12b, and the measurement information is then processed by the processor 26. It is processed in this way and recorded as a set of information defined by the data structure described below. It may include, alternatively or additionally, other imaging elements and / or devices. Furthermore, anatomical information of the heart can be provided to the processor 26. Provided by the processor 26 The processed information (e.g., anatomical data 110) is stored as a set of nodes. Each node is a vertex V of the geometric representation of the anatomical shape, for example, in a mesh of 80. Includes a triangular mesh representing the indicated cardiac chambers HC. Each vertex V of mesh 80 corresponds to mesh 8 Edge E, which is an edge of the polygon (e.g., a triangle) that defines 0, is adjacent to the vertex It is connected to V.

[0158] Any vertex V can be defined as the central vertex CV. For the central vertex CV, vertex V A “neighborhood” surrounding a vertex can be defined (referred to here as a “neighborhood” or “neighborhood of a vertex”). For example, the first neighboring vertex is the central vertex CV, and the central vertex CV is connected to it by a single edge E. It may include all connected vertices V. Furthermore, the second neighboring neighborhood is connected by a single edge E. The two vertices V may include all vertices V connected to any of the first adjacent vertices CV of the central vertex. A neighborhood connected by edges is shown in Figure 2B. A neighborhood connected by multiple edges is connected to the central vertex. It can be defined by the number of edges from the CV (for example, a neighborhood connected by 5 edges) (Each vertex V included is within the five edges of the central vertex CV). Used in this specification In this case, the "border vertex" is defined as the vertex V contained within the neighborhood. Then, a certain number of edges from the central vertex (i.e., the number of edges that define the size of the neighborhood) It is located at ). A "boundary vertex" is connected to a boundary vertex by one edge. However, it can be defined as a vertex V that is not included in the neighborhood (one edge tangent to a vertex of the boundary line). (Vertices that are within the continuum but not within the neighborhood).

[0159] For each vertex V, information corresponding to its anatomical location is recorded by system 100. and can be stored. For example, biological data measured by system 100 for a given point in time. Potential data can be processed and recorded as a set of values, each corresponding to the peak V at that point in time. (Data "frames"). System 100 is represented by multiple consecutive frames. Record bioelectric potential or other data over a long period (e.g., 100 milliseconds to 500 milliseconds). It can be configured such that each contains time-related information associated with vertex V of mesh 80. .

[0160] In some embodiments, each frame contains only biopotential data corresponding to each vertex V. This also includes other calculated and / or measured information corresponding to each vertex V. For example, sys Tem100 may include one or more algorithms, as described below, for each frame Each vertex V is classified against (for example, classification information is stored in each frame). Alternatively, system 100 “preprocesses” the recorded biopotential data for each frame. The results of the processing can be saved for each vertex V in each frame. Sessa 36, ​​at that moment, the peak (for example, depolarization propagating through cardiac tissue) It is possible to determine whether it is "active" (along the leading edge of the waveguide). In some embodiments, it is binary. The activity or inactivity "flag" (i.e., a binary yes / no data point) is used in the algorithm. Reduce processing time. Additionally or alternatively, for each vertex V in each frame, the current activity The activation status and activation history can be saved (for example, the history can show whether a vertex is active or (Indicates whether it was active within a specified period, such as within 100 milliseconds prior.) These implementation forms In this state, the length of the history recorded for each vertex, and / or the resolution of that record, The speed of one or more algorithms in Stem100 and the overall fraction of the resulting computations It may be selected to strike a balance with resolution (for example, by the manufacturer of system 100) (Pre-selected and / or selected by the operator) as used herein In other words, activation "within" the neighborhood is for all frames (e.g., the length of the recording) This includes all activations recorded for each vertex V within the array, or for the central vertex CV of the neighboring array. Activation time window (for example, see Figure 8 and the rolling time window described below) Within the DOUBLE, for example, only activations within + / - 100 milliseconds of the activation of the central vertex CV. It may include. In some embodiments, activation is as described below with reference to Figure 4. If considered to be within the "minimum and maximum velocity estimates", the activation is within the set of neighboring activations. This includes, for example, activation of a boundary vertex within 100 milliseconds of activation of the central vertex CV. It occurs internally, but the physical distance between the points on the tissue represented by the two vertices is "too long". "Too short or too long" can result in the calculated speed being either the maximum or minimum speed (for example, due to the physiology of tissues). If it is not within the estimated range of scientific conduction, activation is excluded.

[0161] In some embodiments, the system 100 is one or more algorithms described herein. The rhythm is constructed and positioned to run on a portion of the mesh 80. For example, the lungs. Analyze a portion of the mesh 80 representing tissue adjacent to the vein (for example, F as described below) Algorithm A500 can identify localized activity, which is near the pulmonary veins. This is because some localized activity is associated with patients with arrhythmias such as AF. Alternatively, one or more algorithms of system 100 may include bias. , and / or one or more thresholds of the algorithm are based on the anatomical tissue being analyzed. It can be adjusted (e.g., biased). For example, the FA algorithm 500 is near the pulmonary veins. It is possible to apply a bias to identify localized activity.

[0162] Next, referring to Figure 3, we see an A for performing complexity assessment that is consistent with the concept of the present invention. A schematic diagram of the algorithm is shown. The algorithm 600 shown is the same as the system 100 described above. It can be included in one or more parts; for example, console 20 includes algorithm 600. In this case, algorithm 600 uses recorded biopotential data, for example, catheter 10 The complexity assessment is performed based on the biopotential data recorded by electrode 12a. The algorithm 600 is configured as shown in Figure 3, using electrical activity data 120 Based on (for example, activation timing data 121) and / or anatomical data 110 This allows for the performance assessment of complexity.

[0163] In step 610, for each frame (as explained above), anatomical data 110 active vertices (as defined above) are determined, and activation propagation data is calculated. Step 610 uses optical flow algorithms (e.g., Horn-Schunck). ) or other 2D or 3D image-based analysis algorithms are used to analyze the activity at each location. The propagation data can be calculated.

[0164] Step 620 performs an analysis of activation propagation data from frame to frame. This analysis examines rotational patterns, localized irregularity patterns, and localized activation patterns. It can identify patterns such as and / or other normal or abnormal electrical activity patterns. The pattern is one or more pattern detection algorithms, for example, algorithm 30 described below. It can be identified using 0, 400, and / or 500.

[0165] Step 630 performs a complexity assessment and generates, for example, diagnostic result 1100. The diagnostic result 1100 is provided to the clinician, for example, to determine the treatment to be administered to the patient (cardiac ab). For example, refer to Figure 1 to identify one or more cardiac tissue locations for performing ration procedures. The treatment subsystem 800 is used to determine the treatment subsystem. In some embodiments, the algorithm M600 processes the diagnostic result 1100 and / or as described below with reference to Figure 3A. This further includes 650 complexity algorithms configured to evaluate the complexity.

[0166] The diagnostic result 1100 may include a scalar value, for example, the scalar value is each evaluated. Assigned to a vertex and calculated over a certain period (for example, the period TP described below) This represents the "level" of complexity. Additionally or alternatively, diagnostic result 1100 is a time-varying value. It can include, for example, a binary value is assigned to each evaluated vertex, within time (for example, The "complex" or "non-(not)" values ​​calculated for several points in time during period TP1) described below. ) represents ". In some embodiments, binary time-varying values ​​are summed or otherwise combined. Combined, a longer period TP (for example, periods TP2, TP3, or described below) Determine the scalar value of the complexity level across TP4). In some embodiments, a binary value is used. And / or scalar values ​​are "permanently" assigned to the vertices of subsequent data frames, for example. For example, the binary "yes" is permanently assigned to the vertices of two, three, or more subsequent frames. It may be possible to invalidate the binary "No" result from the calculation. In addition, A return positive indicator can be assigned a longer persistence, for example, three binary " A frame (for a single vertex) can be assigned 5 additional "yes" values ​​(total (Assuming all eight related subsequent values ​​are "no"), on the other hand, a single binary value " A "Yes" frame can only be assigned two additional "Yes" values ​​(a total of three).

[0167] In some embodiments, electrical activity data 120a is (for example, contact mapping) (In the procedure) at least 10 locations, or at least 48 locations, or at least 64 locations These are recorded from the position of the heart wall (for example, recorded by electrode 12a). In this embodiment, the vertex determined by system 100 is the recording position and / or other heart This may include the location of the wall. In these embodiments, electrical activity data is recorded simultaneously or sequentially. It can be recorded.

[0168] In some embodiments, electrical activity data 120a is obtained from at least 10 cardiac chambers. 100 locations, or at least 48 locations, or at least 64 locations (for example, in contact with the heart wall) These are recorded (and / or non-contact) (for example, recorded by electrode 12a). In this embodiment, the vertex determined by system 100 is the recording position based on the heart wall. and / or other locations on the heart wall may be included. In these embodiments, electrical activity data 12 The number 0 can be recorded simultaneously or sequentially.

[0169] Furthermore, referring to Figure 3A, and as described above with reference to Figure 3, the complexity algorithm 6 50 to process and / or evaluate the diagnostic result 1100 generated in step 630. It can be configured. In step 6510, algorithm 650 identifies in diagnostic result 1100 The type and consistency of each complex activation pattern can be evaluated. Step 6 In steps 520 and 6530, algorithm 650 determines the proximity between each complex activation pattern. Connectivity (e.g., spatial) and / or relation (e.g., temporal) can be evaluated, and then The identified complex activation patterns are part of the "macro-level" complex activation patterns. It is possible to determine whether or not it exists. In step 6540, algorithm 650 calculates the method The probabilistic outcome of applying and delivering treatment to the location of complex activation patterns at the macro level The results can be evaluated and / or predicted. In some embodiments, the calculation method is: A learning dataset (e.g., separately acquired data such as historical data) and / or total Computationally optimized fit (e.g., neural network or deep learning, class Data analysis / statistical analysis of electrical activity using machine learning or predictive analytics (such as stanza analysis) Laws, including, for example, classification or categorization.

[0170] Step 6540 is configured to provide the updated diagnostic result 1100' as shown in the figure. This can be done to identify macro-level complexity, prioritize therapeutic targets, and make probabilistic and / or predictive decisions. Measured therapeutic strategies, one or more changes to diagnostic outcomes, and combinations thereof This may include: In some embodiments, the probabilistic results of delivering treatment may involve the use of machine learning. Determined or provided through and filed on May 8, 2018, "CARDIAC INF The applicant's concurrently pending application, titled "ORMATION PROCESSING SYSTEM" It is described in U.S. Provisional Patent Application No. 62 / 668,659, and its contents are for all purposes The whole is incorporated herein by reference. In some embodiments, predictive The therapeutic strategy is to shift the current rhythm to a less complex rhythm (for example, atrial fibrillation). This can lead to atrial tachycardia, and for example, a strategy determined using state analysis. The current rhythmic state is determined by one or more complexity indicators (e.g., period length, number of heart waves). It can be defined by Shannon entropy and / or dominant frequency. A change in state is For various therapeutic strategies (e.g., different ablation locations and / or durations) It can be estimated. Next, therapeutic strategies that are estimated to change the rhythm to its least complex state. This can be implemented. The complexity algorithm 650 uses other patient data (e.g., M RI / CT data, patient health history data, and / or previous ablation history data ) can be used as input.

[0171] The complexity algorithm 600 includes the analysis of recorded electrical activity data 120a. This can be done, and it is recorded over a period TP that may include similar or different lengths of time. Each period TP is either all or part of the continuous record of that period TP, or cumulatively It may represent all or part of multiple records. In some embodiments, period TP is This represents two or more periods for recording electrical activity, and the time between recordings. In some embodiments, this represents two or more periods for recording electrical activity and the time between recordings. Data recorded over a certain period of time can be used for multiple periods TP (for example, multiple periods of the same duration). The data is segmented into periods (number of periods), and the complexity assessment is calculated over each period TP. The complexity assessment is (for example, as explained below with reference to Figure 8, display 2 It can be displayed to the user in a video-like format (as shown in 7a). In some embodiments Each period TP (for example, period TP2 described below) includes a sufficiently long period TP. As a result, users can reasonably perceive the displayed information in a "real-rate" manner. For example, information is displayed at the same speed as it is generated. In these embodiments, the information is displayed The information may be presented in a "real-time" manner (for example, the information may be displayed as it occurs). (The delay is minimal due to processing by system 100). Alternatively or additionally, period T P may include a sufficiently short period (for example, the period TP1 described below), and as a result, When displayed in real-time format, users may not be able to reasonably perceive the displayed information. In these embodiments, the rolling "average" of the data may be displayed at real rates. And / or the data may be played back frame by frame or in other slow-motion modes. The user can reasonably perceive the data. Additionally or alternatively, cumulatively, summed, averaged, or persistent. Various methods can be implemented to display the data, and the calculated data is perceptible over time. Provides the user with a representation of existence. Furthermore, each period TP (e.g., TP3 and / described below) (or TP4) includes extended periods and / or periods spanning two or more separate records. This allows for the display of time-compressed (time-lapse, etc.) datasets to the user. Raw and other data display modes are described in detail below with reference to Figure 8.

[0172] In some embodiments, the period TP1 includes a relatively short time (for example, in this specification) In cardiac tissue evaluated as being represented by a set of vertices as described, This is the period during which activation occurs, etc. Similarly, TP1 is 0.3 milliseconds to 2000 milliseconds. The duration can include seconds, for example, a period of about 150 milliseconds. In some embodiments, Catheter 10 is a contact mapping catheter (e.g., a "roving" contact This is a tactile mapping catheter that transmits signals from only one distinct portion of the cardiac chamber at a time via electrode 12a. These embodiments include (which are configured to record electrical activity data 120a). Therefore, period TP1 is the total recording time for a single, distinct part of the cardiac chamber, "visit". This can be estimated. The subsequent period TP1 is the subsequent examination of the same individual part or a different part of the cardiac chamber. The estimate can be roughly calculated. In these embodiments, there are two, three periods, each containing a period approximately equal to TP1. By combining one or more records, a more complete dataset of recorded electrical activity can be obtained. A record can be created. Two, three, or more records can be used for contact cardiac mapping. As is known in the field, spatially based on the recorded portion of the cardiac chambers, and based on cardiac cycle information. They can be combined in time. In some embodiments, the catheter 10 is It includes a mapping catheter (e.g., a basket catheter) that can position the entire circumference of the cardiac chambers. To record electrical activity data 120a via electrode 12a from a distributed set of electrodes. It is configured such that the electrode positions are intended to be in contact with or close to the heart wall. In one embodiment, the catheter 10 is a mapping catheter (e.g., a basket catheter). It includes a tere, which is distributed from an offset position in the heart wall via electrode 12a It is configured to record electrical activity data 120a.

[0173] In some embodiments, the complexity algorithm 600 is recorded for the period TP2. This includes an analysis of the electrical activity data 120a, which includes a moderate number of electrical activations, e.g., 3-3 Includes activations of 000, for example, activations of 10-600, or activations of 25-300. TP2 has a duration of 0.3 seconds to 500 seconds, for example, 1 second to 90 seconds, or 4 seconds to 30 seconds. It may include a period of seconds. In some embodiments, the period TP2 is a single data record, e.g. This represents the length of contact and / or non-contact recording of the electrical activity data 120a within the cardiac chamber.

[0174] In some embodiments, the complexity algorithm 600 is recorded for the period TP3. It is configured to analyze the electrical activity data 120a, which includes a number of electrical activations, for example 2,000 to 300,000 activations, for example, including 6,000 to 40,000 activations. Accordingly, TP3 can include durations ranging from 5 minutes to 8 hours, for example, from 15 minutes to 60 minutes. In some embodiments, period TP3 is a recording of several acute electrical activities, for example, diagnostics. and treatment (for example, treatment provided by the treatment subsystem 800 described above, see Figure 1) This represents the length of several recordings obtained before, after, and / or in between loop repetitions of the treatment. .

[0175] In some embodiments, the complexity algorithm 600 uses regional focus. It is configured to analyze activation and / or electrical data from measurements performed locally. The focal point is approximately 5% to 50% of the cardiac chamber surface (for example, 5% to 50% of the endocardial surface of the atria or ventricles). ) may include areas of tissue. The measurement captures the complex conduction characteristics that represent rhythm. Measurements can be taken with sufficient time, for example, capturing approximately 3 to 3000 activations. In some embodiments, the electrode array 12 is sequentially moved to different positions, each Form a set map that includes location data.

[0176] In some embodiments, the complexity algorithm 600 is recorded for the period TP4. This includes an analysis of electrical activity data 120a over several days, weeks, months, and / or years. For example, a period spanning multiple clinical diagnostic procedures performed on a patient. In the application method, the period TP4 can be multiple, for example, several days, several weeks, several months, or several years. This represents the length of the recording of several electrical activities during a clinical procedure.

[0177] In some embodiments, the complexity algorithm 600 uses additional patient data 150 Receiving, for example, as described above with reference to Figure 1, electrical activity data in complexity analysis Includes both data 120 and patient data 150. In some embodiments, complexity algorithm Zoom 600 uses algorithms 200, 300, 400, and / or 50, which are described below. It includes one or more of the following: electrical activity data 120, anatomical data This may include an assessment of complexity based on 110 and / or additional patient data 150.

[0178] Next, referring to Figure 4, a method for determining conduction velocity data that is consistent with the concept of the present invention. A schematic diagram of the algorithm is shown. System 100 is a CV algorithm, which is a conduction velocity algorithm. This may include 200 argolisms, anatomical data shown in data 110, and data 12 The activation timing data shown in 1 is analyzed. The above complexity algorithm 600 is , a CV algorithm 200 can be included. The CV algorithm 200 is system 1 One or more processors, for example, one run by the processor 26 of console 20. The instructions may include the following. The CV algorithm 200 associates as described herein. For each activation of the selected vertex, anatomical data 110 and electrical activity data 120 (example) For example, processing the activation timing data 121) and each vertex of the anatomical data 110 The conduction velocity can be determined.

[0179] In some embodiments, the CV algorithm 200 is used when the depolarization conduction wave passes through the peak. At that time, one or more of the velocities (direction and / or magnitude) at each vertex of the anatomical data 110 Calculate the components of the conduction velocity (for example, the velocity at each peak as the depolarized conduction wave passes through the peaks). The degree can be determined by determining the spatial gradient of the activation time (τ) using the following formula. It is possible.

number

[0180] Each processed vertex can be considered a "central vertex," and the vertices adjacent to each central vertex are... Using a small "neighborhood" consisting of the activation time, we estimate the spatial gradient and at the central vertex. The conduction velocity can be determined. In some embodiments, a small neighborhood is given vertex A method for estimating the spatial gradient of activation time for a point and the positions of small neighboring vertices is to use the neighborhood This involves fitting the activation time to a function of the vertex position (e.g., a polynomial function). In some embodiments, polynomial surface fitting is used.

[0181] The CV algorithm 200 uses anatomical data 110 recorded by system 100. And each frame of electrical activity data 120a can be processed. Step 21 is described below. Steps 0 through 250 process data from a single frame. Multiple frames are processed. This can be processed by repeating steps 210 to 250 in subsequent frames. .

[0182] In step 210, the set of active vertices is compared with anatomical data 110 and electrical activity data. This is determined using TA120 (for example, activation timing data 121).

[0183] In step 220, (for the current frame) each active vertex of the anatomical structure Thus, a neighborhood of a vertex can be defined around that vertex (for example, the central vertex of that neighborhood). In some embodiments, a neighborhood connected by multiple edges (e.g., five) is used. , approximately 200 mm of the anatomical surface 2 ~315mm 2 Define a neighborhood that covers the neighborhood (for example, Figure A neighborhood (as described above, refer to 2B) contains 60 to 120 vertices. Within a neighborhood defined by neighbors connected by a number of edges, all activation times τ are specific It is required that the minimum velocity estimate be within a certain range (for example, a minimum velocity estimate of approximately 0.3 m / s). The speed is estimated as follows:

number

[0184] Next, the principal components of this neighborhood are obtained by taking the matrix of all neighboring vertex positions with the mean removed. Determined by creation. Using Singular Value Decomposition (SVD) of the vertex position matrix. Using this, we can determine the three singular vectors of the local neighborhood corresponding to the principal components of the neighborhood. The position of the vertex is in a neighborhood P of the singular vector. original Multiplying the position of each vertex It is then transformed into a bias defined by the neighboring principal components, where, P original × Singular vector = P prinipal This is the result.

[0185] After the transformation, the neighbor is a spatial variable (u i ,v i ,k i ) can be written as, where (u i ,v i ,k i ) are the amounts of the first, second, and third principal components, respectively, and as shown below, the i-th (i th It is used to describe the position of the vertices of ).

number

[0186] In some embodiments, an optional step 230 is performed. Step 230 So, P prinipal The singular vector with the smallest singular value is removed, and the 3D domestic A transformation from an in-line to a two-dimensional planar domain occurs and is performed using the following function.

number

[0187] The resulting plane is the best fit for the 3D positions of the vertices transformed into a 2D plane. It is a plane. A conversion from 3D to 2D is performed, and the calculated conduction velocity is used to dissect the surface. Ensure that the polynomial table is tangent to the scientific structure and / or is performed in the subsequent step. The dimension of the surface fitting can be reduced, as explained below.

[0188] In step 240, the function (for example, the best-fit cubic polynomial surface function, T) Use the position function (u i ,v i ) as the local activation time τ in the vicinityi Describe, for example , as follows T(u i ,v i )≒τ i It will become.

number

[0189] Given a set [u,v]=τ, the following matrix is ​​constructed to solve for coefficient A. It is possible.

number

[0190] The above can be solved using least squares analysis. The singular value decomposition is matrix A: A = USV T This can be applied to calculate the pseudo-inverse matrix of A, and using this, the coefficients It can be calculated.

number

[0191] In step 250, the conduction velocity is analyzed by taking the derivative of the surface (e.g., polynomial surface T). This can be solved by calculating the following, as shown below.

number

[0192] Next, the conduction velocity can be normalized to create a unit vector, for example, using the following equation: do.

number

[0193] Through the previous step, algorithm 200 uses the conduction velocity data shown in data 122. A set of data is generated, which consists of anatomical data 110 and activation timing data 121. Based on.

[0194] In some embodiments, the conduction velocity data 122 is the resulting conduction velocity unit. By returning the coordinate system to its original coordinate system (for example, the coordinate system of anatomical data 110), (example For example, it can be displayed on the anatomical surface (via the display 27a of system 100). For example, use the following equation.

number

[0195] For each activation (for example, each activation at each central vertex of each frame), the conduction velocity is quadratic. It can be expressed in three dimensions, for example, using the following equation:

number

[0196] Next, referring to Figure 5, in order to determine local rotational activity consistent with the concept of the present invention A schematic diagram of the algorithm is shown. System 100 determines localized rotational activity. This may include the LRA algorithm 300, which is an algorithm for doing so. Algorithm 600 can include LRA algorithm 300. The rhythm 300 can be configured to determine the angular change in conduction velocity relative to the central vertex. In patients with atrial fibrillation (AF) and other arrhythmias, the electrical activity of the heart manifests as a rotor. This can be caused by rotational electrical activity around a central obstacle. Activity has long been thought to play a major role in the persistence of cardiac arrhythmias such as AF (for example) Rotational activity can cause and / or perpetuate these undesirable conditions. (and related to).

[0197] In some embodiments, the LRA algorithm 300 is used by the system 100 The collected anatomical data 110 and electrical activity data 120 (for example, activation time) Process each frame of the data (121). Steps 310 to 121 are described below. In Pro360, data is processed in single frames. Multiple frames are processed in subsequent frames. This can be handled by repeating steps 310 to 360 in the frame. In that embodiment, the LRA algorithm 300 further includes conduction velocity data 122 in its analysis. This includes, alternatively or additionally, the LRA algorithm 300 is, for example, the LRA algorithm When 300 is configured similarly to the CV algorithm 200, the conduction velocity data 122 is determined. It can be configured to be fixed.

[0198] In step 310, the set of active vertices is based on anatomical data 110 and electrical activation. This is determined using data 120 (for example, activation timing data 121).

[0199] In step 320, for each active vertex of the anatomical structure (of the current frame), A neighborhood of a point can be defined around its vertex (for example, the central vertex of its neighborhood). In contrast, the ring of vertices around the central vertex is the neighborhood boundary, as shown in Figures 5A and 5B. It can be defined by the vertices of a world.

[0200] In step 330, for each neighborhood, the activation time and conduction velocity of the vertices within that neighborhood are grouped together. It can be binned (for example). For each neighborhood, a specific maximum velocity estimate ( For example, all activation times within the maximum velocity (estimated at approximately 0.05 m / s) are grouped together. A set of activations can be defined (e.g., restricted). In some embodiments, given the maximum number of activations, Activations reachable from the central vertex activation of the group at high velocity (e.g., 0.05 m / s) Only time is included within the group. The activations of each neighborhood are grouped as shown in Figure 5B. It is possible. In some embodiments, the average activation over all activations in a group. Timing data 121 and / or average conduction velocity data 122 are also shown in Figure 5B. They are assigned to the vertices of the boundary, as shown.

[0201] Step 340 shows a linear trend in activation time around the outer ring of the vertices (e.g., increasing). Vertices with a trend (or decreasing trend) are identified. For example, a linear fit with R² ≥ 0.7 shows a trend and It can be identified as such. Figure 5D shows the trend line of activation time.

[0202] In step 350, the first and last peaks of the linear trend identified in step 340 are divided. The total angular change between the applied average conduction velocities is determined. Figure 5E is transformed to the origin 0,0. Furthermore, the identified linear trend in conduction velocities is shown. Figure 5E shows the average conduction velocities between the above-mentioned average conduction velocities. The total angle change is shown in the graph.

[0203] In step 360, the LRA algorithm 300 uses the linear algorithm identified in step 340. If the trend exceeds a threshold (e.g., an operator-defined threshold), and / or step 350 If the total angle change identified exceeds a threshold, the central vertex is classified as "rotational".

[0204] The LRA algorithm 300 generates a set of data (for example, creating new data). (and / or modify existing data), and it is classified into activation data 140 (for example) Filtering, categorizing, identifying, and / or classifying to activate in an essentially rotational manner This is data used for identification.

[0205] Next, referring to Figure 5A, a graphic representation of anatomical data 110 is shown, and the vertices It includes the neighborhood of vertices defined by the outer ring.

[0206] Next, referring to Figure 5B, a simplified representation of the neighborhood of a vertex is shown, and around the central vertex... It includes an outer ring of vertices located in the vicinity. In some embodiments, activation within the neighborhood It is segmented or binned and then averaged. The mean is a single peak, for example. It can be assigned to the vertices of the boundary lines within the segment. For example, by the shaded portion S1 All activations within the neighboring area are averaged and "assigned" to vertex V1. It is possible. In some embodiments, binning is performed on the data. Limit the impact of noise on subsequent calculations. In some embodiments, segments The size of S1 is selected to increase the resolution of the system 100 (for example, a smaller size). (Initialization) or reduce subsequent computation time (e.g., larger segments).

[0207] Referring to Figure 5C, a representative anatomy shows an exemplary propagation wave rotating around a neighbor. The geometric structure is shown, and the neighborhood is defined by an outer ring of vertices arranged around the central vertex. The mean conduction vector is also shown from the vertices of each boundary of the ring.

[0208] Next, referring to Figure 5D, the activation time plot in the outer ring of the vertices in Figure 5C is The activation times are shown and plotted against the frequency around the central vertex. As described above, The points on the plot represent a set of vertices within a ring that exhibit a linear tendency, as shown in Figure 5D. In the data, the trend spreads from approximately 200° to approximately 375°, with the cardiac wave around the central peak. This indicates that it propagated 175°.

[0209] Next, referring to Figure 5E, a graph of the conduction velocity vector related to Figure 5C is shown, and the vector Torr is converted to point 0,0. The change in conduction velocity around the central vertex is the same as the continuous conduction velocity. This can be determined by summing the angles between vectors. In this example, it is represented by angle α. The velocity vectors of the data shown in the diagram total 155°.

[0210] Next, referring to Figure 6, we determine localized disorder activity consistent with the concept of the present invention. A schematic diagram of the algorithm is shown. System 100 determines local randomness activity. This may include the LIA algorithm 400, which is an algorithm for doing so. LIA Algorithm 600 can include LIA Algorithm 400. M400 is the angle between the direction of conduction approaching the central vertex and the direction of conduction away from the central vertex. It can be configured to determine the degree of irregular activity, e.g., significant splitting, irregular ligation Trant-type activity and / or disorganized conduction play a significant role in the persistence of cardiac arrhythmias, including AF. It has long been thought that this will be achieved.

[0211] In some embodiments, the LIA algorithm 400 is used by the system 100 Anatomical data 110 and electrical activity data 120 (e.g., activation timing) were collected. Process each frame of the data (121). Steps 410 to 121 are described below. In 460, processing is performed on a single frame of data. Multiple frames are processed in subsequent frames. This can be handled by repeating steps 410 to 460 in the frame. In this embodiment, the LIA algorithm 400 also analyzes conduction velocity data 1 Includes 22. Alternatively or additionally, LIA algorithm 400 is, for example, LIA Algo When rhythm 400 is configured similarly to CV algorithm 200, conduction velocity data 12 It can be configured to determine 2.

[0212] In step 410, the set of active peaks is based on anatomical data 110 and activation timing. This is determined using the 121 data.

[0213] In step 420, for each active vertex of the anatomical structure (of the current frame), A vertex neighborhood can be defined around that vertex (for example, the central vertex of that neighborhood). Figure 5 As shown in A, for each neighborhood, the ring of vertices around the central vertex is the vertex of the neighborhood boundary. It can be defined by a point.

[0214] In step 430, for each neighborhood, the LIA algorithm 400 determines the central vertex An activation time shorter than the activation time (within the maximum conduction velocity, e.g., 0.3 m / s to 3 m / s) Having a conduction velocity direction toward the central vertex, the plane of all nearby activations They can be configured to determine the direction of the uniform conduction velocity. In some embodiments, these activities Only a subset of the chemicals is included in the calculation of the mean conduction velocity direction.

[0215] In step 440, for each neighborhood, the LIA algorithm 400 determines the central vertex Activation time slower than the activation time (within the maximum conduction velocity, e.g., 0.3 m / s to 3 m / s) For all nearby activations that have a conduction velocity direction away from the central vertex They can be configured to determine the mean conduction velocity direction. In some embodiments, these active Only a subset of the curing properties is included in the calculation of the mean conduction velocity direction.

[0216] In step 450, the LIA algorithm 400 determines the direction of the average conduction velocity entering the vicinity. Determine the angle between the direction of the mean conduction velocity leaving the vicinity.

[0217] In step 460, the LIA algorithm 400 was determined in step 450. If the angle exceeds a threshold (for example, a threshold defined by the operator), the central vertex is marked as "irregular". It is classified as "sex". The LIA algorithm 400 generates a set of data (for example, (Create new data and / or modify existing data), and it is classified as activation data Data 140 (e.g., filtering, categorizing, identifying, and / or classifying and activating) This is data that identifies the irregularity in an essential way. In some embodiments, the vertices are It may be classified as rotational (for example, the LRA algorithm 300 is pre-programmed) If executed, the LIA algorithm 400 reclassifies the vertices as irregularities, or adds Do not classify additively. Alternatively or additionally, the classified activation data 140 is assigned to each vertex. This can enable multiple classifications. In these embodiments, system 100 is a weighting agent. It may be configured to add numbers or to prioritize a particular classification, for example, rotational classification This may be considered more important than classification of irregularities.

[0218] Next, referring to Figure 6A, we see a propagating wave that exhibits activation of disorder, consistent with the concept of the present invention. Let's look at an example. Figure 6A shows the propagating wave PW1 entering a small region called dot CV. By averaging these conduction velocities, the direction of the average conduction velocity entering region CV can be determined. Figure 6A also shows The propagating wave PW2 leaving region CV is shown. The conduction velocity from PW2 is averaged and the wave leaves region CV. The direction of the average conduction velocity can be determined. The LIA algorithm 400 determines the direction of conduction approaching the CV. It can be configured to determine the angle β between the direction of conduction and the direction of conduction away from CV. (As mentioned above). The LIA algorithm 400 uses an angle threshold (for example, as also mentioned above). If it exceeds a user-defined threshold, the central peak of the activation time is divided as an irregularity. They are similar.

[0219] Next, referring to Figure 7, we see an A for determining localized activation that is consistent with the concept of the present invention. A schematic diagram of Gorhythm is shown. System 100 is localized activation (also called localized activity). This may include the FA algorithm 500, which is an algorithm for determining the above complex The sex algorithm 600 can include the FA algorithm 500. Zoom 500 indicates that the activation at the peak originates from a previous cardiac wavefront, or that the activation originates from the peak. It may be configured to determine whether it was initiated spontaneously (known as localized activation). Sexual activation is detected at the vertex if its activation occurs earlier than the activation of nearby vertices, and conduction is It spreads outward from the apex. Localized activity from the pulmonary veins plays a central role in the persistence of paroxysmal AF. It has been shown that localized activity is associated with the persistence of cardiac arrhythmias, including AF. More generally, localized activity is associated with the persistence of cardiac arrhythmias. It is also thought to play a significant role in this regard.

[0220] In some embodiments, the FA algorithm 500 is used by the system 100 Collected anatomical data 110 and electrical activity data 120 (e.g., activation timing) Process each frame of data 121). Steps 510 to 510 are described below. In step 60, processing of a single frame of data is performed. Multiple frames are processed in subsequent frames. This can be processed by repeating steps 510 to 560 in a system. In the embodiment, the FA algorithm 500 also includes conduction velocity data 122 in its analysis. Additionally or alternatively, FA algorithm 500 may be, for example, FA algorithm 500 may be C When configured similarly to the V algorithm 200, the conduction velocity data 122 is determined It can be configured as follows. In some embodiments, the FA algorithm 500 is defined as follows: To that end, the analysis includes conducted divergence data 123. Conducted divergence data 123 is FA A Another algorithm for Gorhythm 500 and / or System 100 (e.g., FA Algorithm) It can be generated by (generated before the application of M500).

[0221] In some embodiments, the conducted divergence data 123 is obtained from each vertex of the anatomical data 110. This includes the divergence of the conduction velocity. The divergence of the conduction velocity field can be defined as follows:

number

number

[0222] For all activations at all vertices, the divergence of the conduction velocity has a positive value that exceeds the threshold. If determined to be so, the vertex is classified as "clearly defined" in the conducted divergence data 123. In some embodiments, vertices in a neighborhood connected by multiple edges (e.g., five) If half of the conduction velocity is within the minimum conduction velocity range, the divergence is classified as clearly defined. A positive divergence threshold of 0.05 can be used.

[0223] In step 510, the set of active vertices is based on anatomical data 110 and activation timing. This is determined using the 121 data.

[0224] In step 520, the set of diverging active vertices is determined in step 510. Identified from a set of dynamic vertices.

[0225] In step 530, for each diverging active vertex, the neighborhood of the vertex is that vertex (e.g., For example, it is defined around the central vertex of that neighborhood. For each neighborhood, around the central vertex The ring of vertices can be defined by the vertices of the neighboring boundary, as shown in Figure 5A.

[0226] Step 540 defines a set of "boundary vertices," where each neighboring boundary is defined. Includes neighborhoods connected to the vertices of the boundary by a single edge.

[0227] In step 550, the activation time of each boundary vertex defined in step 540 is determined. It will be done.

[0228] In step 560, the FA algorithm 500 activates each vertex of its boundary. If the time is slower than the activation time of each central vertex, the central vertex is considered "localized". The FA algorithm 500 generates a set of data (for example, a new data (Create a new one, and / or modify existing data), and it is classified as activated data 140 (For example, filtering, categorizing, identifying, and / or classifying and activating essentially This is data identified as locality. In some embodiments, the vertices are rotated beforehand. It may be classified as sex and / or irregularity (for example, LRA algorithm 300) (and / or if LIA algorithm 400 has been performed beforehand), FA algorithm 5 00 does not reclassify or additionally classify the vertex as locality. Alternatively or additionally, classify The activated data 140 may allow for multiple classifications for each vertex. These implementations In terms of form, system 100 either adds weighting coefficients or prioritizes a particular classification. It can be constructed in such a way (as described above), for example, rotational classification is irregular and / or localized classification It can be considered more important than its class.

[0229] Referring to Figures 7A and 7B, representative examples of localized activation consistent with the concept of the present invention are shown. The diagram shows both the typical anatomical structure and representative anatomical structures that exhibit localized and passive activation. As shown in Figure 7A, the dot CV indicates the vertices currently being evaluated. The boundary vertices Point BV is shown enclosing the propagating wavefront PW3 extending from dot CV, as shown in Figure 7B. Dot CV1 indicates the first vertex, and dot CV2 indicates the second vertex. Zoomed in on Figure 7B. Window (i) shows the neighborhood of vertices around CV1, and the zoom window (i) in Figure 7B i) shows the neighborhood of vertices around CV2. In the zoom window of Figure 7B, the neighborhood is a plane. It is projected onto and interpolated onto a standard grid. As mentioned above, the complexity algorithm 600 is a supervised learning algorithm, for example, a well-labeled training set This may include a learning algorithm trained on a 3D model. (e.g., vertex CV) The neighborhood of the region around the can be interpolated into a standard grid of nxm, with each grid point having a value The activation time is included and is shown in the zoom windows (i) and (ii) of Figure 7B. The time information is included. This can be added by concatenating multiple images. When the activation time becomes standard grid, Learning algorithms (feedforward neural networks, convolutional neural networks) Training (networks, support vector machines, etc.) on a large patient set, The image of the conduction pattern allows for the identification of the conduction pattern of interest. Activation time data The conduction pattern of interest is evaluated and simultaneously converted into an image space, and then labeled. Deleted output can be restored and displayed (for example, in 3D anatomical space). How many In that embodiment, the complexity algorithm 600 is selected from the group consisting of the following electrical It can be configured to identify specific patterns, and the group may include LIA, LRA, locality, and delayed conduction velocity. , isthmus-like conduction, figure-eight conduction, for example, double, triple, or multi-loop conduction It consists of loop drive, swirling re-entry, and combinations thereof. For example, the zoom in Figure 7B As shown in (i), localized conduction is in the region of interest, for example, by algorithm 600. Localized conduction identified as a region is shown. As shown in the zoom (ii) of Figure 7B, passive Passive conduction is, for example, identified as a "non-interested" domain by algorithm 600. Conduction is demonstrated.

[0230] Next, referring to Figure 8, cardiac data (e.g., activation and / or) consistent with the concept of the present invention. Implementation of a display capable of rendering other bioelectric potentials and / or anatomical data. The form is shown. Cardiac data is a set of data that can be dynamically displayed as a function of time. It can be composed of the following. The display 1400 in Figure 8 uses the same processor and module as above. and can be generated using a database, and on other displays, for example, the display in Figure 1 Render I27a. In some embodiments, system 100 and / or D Spray 1400 is "CARDIAC INFORMATION DYNAMIC D Released on May 3, 2017, under the title "ISPLAY SYSTEM AND METHOD" The applicant's concurrently pending international PCT patent application number PCT / US2017 / 03 The display may have the same construction and arrangement as described in issue 0915, and its contents may be all For the purposes of this document, the entire document is incorporated herein by reference.

[0231] Window 1405 is within the main cardiac information display window or area (for example) (Part of the display 1400) Digital model of the anatomical structure of the heart 1402 Cardiac activation data is superimposed or superimposed on it. In terms of form, cardiac activation data is rendered, and the activation state is represented by the digital cardiac model 1. It is represented by a series of colors superimposed on 402.

[0232] Display 1400 is represented by the displayed digital heart model 1402. To that end, two or more unique values ​​representing different physiological parameters of one or more parts of the heart. Graphical representations can be displayed simultaneously. These are used to represent physiological parameters. The various graphic displays can be selected from the following groups, which are: color, color range, and pattern. Symbols, shapes, opacity levels, stippling, hues, and geometric shapes of 2D or 3D objects. Consists of shape and combinations thereof. Graphics used to represent physiological properties. The display can be static and / or dynamic.

[0233] Simultaneous display of multiple physiological properties (e.g., distinguished through various graphic displays) ) superimposes one or more combinations onto one or more digital models of cardiac anatomical structures It is possible to do this using various physiological parameters, such as minimum reactivation time, conduction velocity, and vorticity threshold. The number of occurrences and / or other physiological parameters that exceeded the value during the period are each unique to the group. It can be represented in rough notation. It has discrete levels of hatch density and / or line thickness. The cross-hatch pattern is superimposed on the digital model, and different categories of conduction velocities are used. It is possible to identify regions classified as "Ri". Surface spheroids are those where the vorticity is greater than the threshold. The spheroid can be superimposed around the center, and the diameter of the spheroid is such that the vorticity threshold is maintained during the duration of cardiac activity. The number of occurrences during the period is displayed in proportion to the number of times it exceeds the limit. The hatch pattern and spheroids are displayed in the graph. Provided herein are non-exclusive examples of fictitious representations.

[0234] In some embodiments, the display of the electrocardiogram EGM1410 shows the reconstructed heart 1 The auxiliary heart information display window below the main heart information display window 1405, which displays 402. It will be presented in Dou 1415.

[0235] Control 1420, a set of user-interactive controls, is the main cardiac information table. In window 1405, the user can specify the duration of the display (for example, the duration of the displayed calculated data). This includes a window width control 1422 configured to allow setting the duration. This can be done, and here it is shown set to 30 milliseconds. The window width (duration) is half Shown in window 1412, which is a transparent sliding window, to EGM1410 Superimposed. Scale 1424 is a user-selectable and / or configurable display scale. Furthermore, a time scale called t is established and used with it. SCALE This can be set. is, t SCALE It is set to 3 milliseconds. Therefore, the horizontal axis of the EGM1410 is 3 milliseconds. Includes increments of seconds. Control 14 is the control for play, rewind, and fast forward. 26 is also included, as shown in the diagram.

[0236] In some embodiments, the diagnostic result 1100 is displayed in the main cardiac information display window 140. Displayed in 5, for example, the graphical representation of the complexity assessment is the reconstructed heart 1402 It can be displayed superimposed on (for example, the calculated complexity of each vertex of the reconstructed heart 1402) (including the evaluation of complexity). In these embodiments, the window width of window 1412 is The portion of the recorded data analyzed in the complexity assessment shown (for example, the complexity assessment shown) It can indicate the period represented by. For example, the complexity assessment displayed is an assessment of several complexities. It can include the average (over two or more periods shorter than within a window of 1412) (Calculated). The calculation of the evaluation of various complexities is described above. The width of window 1412 is, The user may be able to select and / or adjust data from longer or shorter periods. Generates complexity assessments that include [specific elements]. Two or more complexity assessments are displayed in a frame-by-frame manner. It can be done (for example, in a movie), and window 1412 "rolls" across EGM1410. (For example, "rolling window"), the segment of the data analyzed for each frame This indicates the ment. Alternatively or additionally, the user can manually position or adjust window 1412. This generates an assessment of the complexity of a desired segment of the recorded data.

[0237] The translucent sliding window 1412 is superimposed on the reconstructed heart 1402. It synchronizes with the cardiac activation data shown. Therefore, the translucent sliding win Cardiac activation data superimposed on Dou 1412 and the reconstructed heart 1402 are shared It can change dynamically with respect to the time scale. The display is time-linked, and their output Because they are based on the same time-dependent data, they change together.

[0238] Control 1428, which is a set of display modes or layer controls, allows the user to... It has been specifically restructured to allow control over at least part of the display of the main window 1405. It is provided that at least a portion of the display of cardiac activation data for heart 1402 can be controlled. In this embodiment, a separate "button" (e.g., an electromechanical switch, a touchscreen) may be used. Lean icons and / or other user-interactive controls) are "color maps", "Texture Map," "Shade Map," and "Pattern Map" graphical options It is provided as a control 1428 for selecting the option. In some embodiments, One or more such controls are provided. All such controls are implemented in all implementations. It does not need to be arranged in a specific form. In some embodiments, any of the controls 1428 There is no need to install them.

[0239] In Figure 8, the reconstructed cardiac chamber 1402 changes color (for example, on the color map button). This is shown along with cardiac activation data represented as a responsive, changing grayscale. For demonstration purposes, a portion of the reconstructed cardiac chamber 1402 responds to the texture map button. Texture map 1404, shade map 1406 that responds to the shade map button, And it is shown together with pattern map 1408 which responds to the pattern map button. In some embodiments, such buttons (or similar controls) are used. Selectively turn on each map.

[0240] For example, graphics that indicate a uniform size (e.g., roughness, texture, etc.) Graphics (and / or graphics indicating direction, e.g., wood grain, line segments, spikes) These particles may be directional and superimposed on the anatomical structure of the surface, conducting or substrate-specific particles. The properties can be visualized. The "roughness" of the z-height of the graphic indicating size is a characteristic that is displayed. It can be increased or decreased in proportion to the degree of (for example, the magnitude of the characteristic). Also, the direction of the block is the direction Graphics that show this (for example, the spikes shown in texture map 1404 in Figure 8) It can be shown.

[0241] Continuing with the above example, shading and / or a clear fixed color palette or Gradation (different from other color palettes used), for example, using grayscale. And various blocks such as fixed blocks, directional blocks, and / or functional blocks have conditions It is possible to identify the degree of the problem.

[0242] The multidirectional region of activation has different unidirectional textures, as shown in pattern map 1408. It can display by overlapping lines or shapes, generating a "hatch" pattern. Fibrosis The calculation of indicators and / or other physiological state indicators characterizing the surface / substrate is performed using a uniform texture. For example, fine patterns such as those resembling cement, or patterns resembling pebbles. It can be displayed as a coarse pattern such as a pattern. Obstacles or lines indicating obstacles in the conduction pattern. Indicators of vascular disorders or other physiological conditions include velocity, directional uniformity, and / or other conduction patterns. It can be determined by the combination of characteristics.

[0243] By incorporating textures, patterns, shading, etc., into the surface of cardiac chamber 1402 , providing more information in conjunction with other types of cardiac activity information (e.g., visually). A method is provided to do this. This configuration is a visual "layer" of the map display. This is an extended implementation of "[ ]", which can be used individually or in any combination, and is a user-interactive controller Information related to multiple variables can be provided simultaneously through the use of methods such as 1420.

[0244] In some embodiments, one or more of the vertex classifications described herein are reconstructed. It is shown on the constructed cardiac chamber 1402. In these embodiments, the classification is color overlay. It may be shown as described above using (i) and / or other graphic representations, etc. In application, colored or otherwise distinguishable "dots" are used to indicate specific properties. This indicates the vertices that are classified as such (referred to as “classified” in this specification). Using a set and / or other indicators, multiple classifications (e.g., multiple similar and / or These can indicate different classifications. Overlapping indicators can show different radii and anatomical structures. Height from the surface of the structure, and / or offset along the surface of the anatomical structure in different directions. It can be displayed in the same position using a graphic indicator. In some embodiments, The vertex is displayed "persistently," for example, if a vertex is classified in the first frame, the classification will remain. The indicator may persist on the display for one or more subsequent frames. Additional or Alternatively, the classification indicator could be for multiple vertices, for example, two of the classified vertices This can be displayed for vertices connected by edges.

[0245] Referring to Figures 9 and 9A, we see a schematic diagram of the mapping catheter and the mapping... The oblique anatomical diagrams of the cardiac chambers into which the catheter is inserted are consistent with the concept of the present invention. The catheter 10' includes one, two, three, or more electrodes 12a. It includes an electrode array 12'. In some embodiments, the electrode array 12' has fewer than 24 electrodes. The electrodes, for example, fewer than 12 electrodes such as 10, 8, 6, 4, or 3 electrodes. Includes. The electrode array 12' is an array of expandable splines to which electrodes 12a are attached. This may include: The catheter 10' is inserted percutaneously into the patient, and the electrode array 12' is placed in the cardiac chambers ( It can be delivered percutaneously to HC, and can be constructed and distributed similarly to catheter 10 described above, as shown in Figure 1. It can be placed in this position. Figure 9A shows an electrode array 12' inserted percutaneously into the cardiac chamber (HC). This shows that electrode 12a is positioned in contact with a portion of the heart wall, and as a result, electrical activity data The data 120a can be recorded, for example, by the system 100 described herein. The data can be recorded. The area of ​​analysis is indicated by surrounding the tissue adjacent to the contact point of electrode 12a. In some embodiments, the recorded electrical activity data 120a is used by the system 100. For example, refer to Figure 3 and perform a complexity analysis using the algorithm 600 described above. The diagnostic results 1100, which are processed and generated, are "assigned" to the area of ​​analysis. " (For example, the diagnostic result can be at the apex of the anatomical model represented within the region of analysis) (Recorded in relation to). In some embodiments, the diagnostic result 1100 for the area of ​​analysis This is in the realm of analysis (for example, along with the collection and / or analysis of data from other areas of the cardiac chambers). (or without), it shows the potential therapeutic effect from the intervention (e.g., tissue excision). In the embodiment, some areas of analysis are, for example, when the electrode array 12' detects differences in cardiac chambers (HC). When the catheter 10 is repositioned to a specific area and additional data is recorded and analyzed, It can be investigated by '.

[0246] The embodiments described above should be understood to serve only as illustrative examples, and further implementation is not permitted. A form is assumed. Any feature described herein with respect to any one embodiment is, It can be used alone or in combination with other features described, and in any other implementation. One or more features of the form, or any combination of any other embodiment, can be used in combination with Furthermore, equivalents and modifications not described above also deviate from the scope of the present invention. It may be used without being used, as defined in the attached claims.

Claims

1. It is a cardiac diagnostic system, A diagnostic catheter configured to be inserted into a patient's heart, and configured to record the patient's electrical activity data at multiple recording locations, At least one processing unit, Associating the aforementioned electrical activity data with the location of the heart, Using the aforementioned electrical activity data, a complexity assessment is performed to identify substrate-mediated complexity, and diagnostic results related to the cardiac state are generated based on the complexity assessment. A processing unit containing an executable algorithm, Includes, The aforementioned complexity assessment indicates variations in one or more characteristics of the heart, including its electrical, mechanical, functional, and / or physiological properties, which vary in time, space, size, and / or state. The algorithm is configured to process the diagnostic results and evaluate the variation in complexity between complex activation patterns. Cardiac diagnostic system.

2. In the system described in claim 1, The aforementioned algorithm is configured to evaluate the changes in complexity over time. Cardiac diagnostic system.

3. In the system described in claim 1, The aforementioned algorithm is configured to evaluate variations in complexity across space. Cardiac diagnostic system.

4. In the system described in claim 1, The algorithm is configured to evaluate variations in complexity according to a transmission pattern selected from a group consisting of locality, re-entry, rotation, rotation, directional irregularity, velocity irregularity, functional blocks, permanent blocks, and combinations thereof. Cardiac diagnostic system.

5. In the system described in claim 1, The algorithm is configured to evaluate variations in complexity according to spatiotemporal patterns selected from a group consisting of analytical divergence, Hilbert transform, phase analysis, and combinations thereof. Cardiac diagnostic system.

6. In the system described in claim 1, This complexity assessment represents an assessment of a portion of the cardiac chambers, Multiple recording locations include at least three recording locations within the cardiac chambers. The at least one processing unit is configured to calculate electrical activity data relating to at least three vertices on the heart wall, and this calculation is performed based on the electrical activity data recorded at the at least three recording locations. Cardiac diagnostic system.

7. In the system described in claim 1, Complexity assessment represents the evaluation of a portion of the cardiac chambers. Multiple recording locations include at least 24 recording locations within the cardiac chambers. At least one processing unit is configured to calculate electrical activity data for at least 64 vertices on the heart wall, and this calculation is performed based on electrical activity data recorded at at least 24 recording locations. Cardiac diagnostic system.

8. In the system according to any one of claims 1 to 7, The at least one processing unit is configured to calculate electrical activity data relating to a plurality of vertices on the heart wall, and this calculation is performed based on the electrical activity data recorded at the at least three recording locations. Cardiac diagnostic system.

9. In the system described in claim 8, The aforementioned at least one processing unit further includes a second algorithm, The recorded electrical activity data includes recorded voltage data. The second algorithm can be executed to calculate surface charge data and / or dipole density data for each of the multiple vertices based on the recorded voltage data. Complexity assessment is performed based on surface charge data and / or dipole density data. Cardiac diagnostic system.

10. In the system described in claim 9, The aforementioned at least one processing unit further includes a third algorithm, A third algorithm is executable to convert surface charge data and / or dipole density data into surface voltage data. Complexity assessment is performed based on surface voltage data. Cardiac diagnostic system.

11. In the system described in claim 1, The complexity assessment is based on electrical activity data, including 3 to 3,000 activations. Cardiac diagnostic system.

12. In the system described in claim 1, The complexity assessment is based on electrical activity data recorded over a period of 0.3 seconds to 500 seconds. Cardiac diagnostic system.

13. In the system described in claim 1, Complexity assessment is performed based on electrical activity data recorded over a period of 5 minutes to 8 hours. Cardiac diagnostic system.

14. In the system described in claim 1, The diagnostic results include an assessment of complexity at a single cardiac wall location. Cardiac diagnostic system.

15. In the system described in claim 1, The diagnostic results include an assessment of complexity at multiple cardiac wall locations, as part of a cardiac diagnostic system.

16. In the system described in claim 1, A diagnostic catheter includes at least one electrode. Cardiac diagnostic system.

17. In the system described in claim 1, The diagnostic catheter includes at least one ultrasound transducer. Cardiac diagnostic system.

18. In the system described in claim 1, The diagnostic catheter includes multiple splines, each spline including at least one electrode and at least one ultrasound transducer. Cardiac diagnostic system.

19. In the system according to claim 1, the cardiac state includes a state selected from the group consisting of atrial fibrillation, atrial flutter, atrial tachycardia, atrial bradycardia, ventricular tachycardia, ventricular bradycardia, ectopic heart failure, congestive heart failure, angina pectoris, arterial stenosis, and combinations thereof. Cardiac diagnostic system.

20. A system according to any one of claims 1 to 7, Further includes an ablation catheter for insertion into the patient's heart, The ablation catheter is configured to supply ablation energy to at least one location on the heart wall. Cardiac diagnostic system.

21. In the system described in claim 20, The algorithm is configured to determine at least one ablation site, the at least one ablation site including one or more cardiac wall locations for receiving ablation energy from an ablation catheter, and the at least one ablation site is determined based on complexity assessment and / or diagnostic results. Cardiac diagnostic system.

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