DETAILED CORRESPONDANCE
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of claims
This final office action on merits is in response to the communication received on 02/17/2026. Claims 2 and 10 are cancelled. Amendments to claims 1 and 9 are acknowledged and have been carefully considered. Claims 1, 3-9, and 11-16 are pending and considered below.
Information Disclosure Statement
The information disclosure statement (IDS) filed on 01/13/2026 has been acknowledged. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 3-9, and 11-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Under step 1, the analysis is based on MPEP 2106.03, and claims 1, and 3-8 are drawn to a method and claims 9, 11-16 are drawn to a system. Thus, each claim, on its face, is directed to one of the statutory categories (i.e., useful process, machine, manufacture, or composition of matter) of 35 U.S.C. 101.
Step 2A Prong One
Claim 9 recites the limitations of defining a nonconductive zone around each ablation tag for at least some of the ablation tags, to calculate block areas; receiving from a user, markings on the map of a starting point and an ending point of a potential conduction flow; searching for one or more possible conduction flow paths from the starting point to the ending point, the one or more existing paths taking into consideration the block areas. These limitations, as drafted, are processes that, under their broadest reasonable interpretations, cover performance of the limitations in the mind or by using a pen and paper. Even when considering the “using a search algorithm” language, the claim encompasses a user evaluating possible paths between two points based on known blocked regions in their mind or by using a pen and paper. The nominal recitation of using a search algorithm do not take the claim limitations out of the mental processes grouping. Thus, the claim recites a mental process which is an abstract idea.
Independent claim 1 recites identical or nearly identical steps with respect to claim 9 (and therefore also recite limitations that fall within this subject matter grouping of abstract ideas), and this claim is therefore determined to recite an abstract idea under the same analysis.
Under Step 2A Prong Two
The claimed limitations, as per claim 9, include:
an interface configured to receive an anatomical map of wall tissue of at least a portion of a cardiac chamber, the map superimposed with ablation tags; and
a processor, which is configured to:
define a nonconductive zone around each ablation tag for at least some of the ablation tags, to calculate block areas;
receive from a user, markings on the map of a starting point and an ending point of a potential conduction flow;
using a search algorithm, search for one or more possible conduction flow paths from the starting point to the ending point, the one or more existing paths taking into consideration the block areas;
in response to identifying the one or more possible conduction flow paths from the starting point to the ending point, hiding the ablation tags and overlaying the one or more conduction flow paths, found by the search algorithm, on the anatomical map in real time during an ongoing ablation procedure; and
receive from the user, an instruction to ablate tissue at a location along the one or more conduction flow paths.
Examiner Note: underlined elements indicate additional elements of the claimed invention identified as performing the steps of the claimed invention.
The judicial exception expressed in claim 9 is not integrated into a practical application. The claim as a whole merely describes how to generally “apply” the concept of determining possible paths between points based on spatial constraints in a computer environment. The claimed computer components (i.e., an interface configured to; a processor, which is configured to; using a search algorithm; and found by the search algorithm) are recited at a high level of generality and are invoked as tools to perform an existing process of evaluating whether a viable path exists between two locations while accounting for intervening blocked regions. Simply implementing the abstract idea on a generic computer is not a practical application of the abstract idea. Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application.
The judicial exception expressed in claim 9 is not integrated into a practical application. The claim recites the additional elements receiving an anatomical map of wall tissue of at least a portion of a cardiac chamber, the map superimposed with ablation tags; in response to identifying the one or more possible conduction flow paths from the starting point to the ending point, hiding the ablation tags and overlaying the one or more conduction flow paths on the anatomical map in real time during an ongoing ablation procedure; and receiving from the user, an instruction to ablate tissue at a location along the one or more conduction flow paths. These limitations are recited at a high level of generality (i.e., as a general means of gathering data, displaying the data and outputting an instruction), and amounts to merely data gathering, presenting results, and insignificant application, which are forms of insignificant extra-solution activities. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
Therefore, under step 2A, the claims are directed to the abstract idea, and require further analysis under Step 2B.
Under step 2B
Claim 9 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A, the claim as a whole merely describes how to generally “apply” the concept of determining possible paths between points based on spatial constraints in a computer environment. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
For claim 1, under step 2B, the additional elements of receiving an anatomical map of wall tissue of at least a portion of a cardiac chamber, the map superimposed with ablation tags; in response to identifying the one or more possible conduction flow paths from the starting point to the ending point, hiding the ablation tags and overlaying the one or more conduction flow paths on the anatomical map in real time during an ongoing ablation procedure; and receiving from the user, an instruction to ablate tissue at a location along the one or more conduction flow paths have been evaluated. The system comprising at a processor performs a general function of receiving patient data for subsequent processing, which represents a well-understood, routine, and conventional activity in the field of medical data processing and visualization systems. The specification discloses that the processor is used in its ordinary capacity as a data input device and does not describe any improvement to the computer itself or to the functioning of the overall computer system. Also noted in Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016), merely collecting information for analysis without a technological improvement does not add significantly more to an abstract idea. The use of the system is no more than collecting information before analyzing the information to determine possible conduction paths and displaying results does not integrate the abstract idea into a practical application. Additionally, as noted in In re Brown, 645 Fed. App'x 1014, 1016-1017 (Fed. Cir. 2016), merely providing or outputting an instruction based on the determined result represents an insignificant application of the underlying mental process, as the instruction simply communicates the result of the determination and does not impose any meaningful limitation or add any technological improvement. Therefore, the claim does not recite an inventive concept and is not patent eligible.
Claims 3-4, 7-8, 11, and 16 recite no further additional elements, and only further narrow the abstract idea. The previously identified additional elements, individually and as a combination, do not integrate the narrowed abstract idea into a practical application for reasons similar to those explained above, and do not amount to significantly more than the narrowed abstract idea for reasons similar to those explained above.
Claims 5-6, and 12-15 recite the additional element of using a first search algorithm (claim 5-6, 13-14), and the processor (claims 12-15). However, these additional element amount to implementing an abstract idea on a generic computing device. As such, these additional elements, when considered individually or in combination with the prior devices, do not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Thus, as the dependent claims remain directed to a judicial exception, and as the additional elements of the claims do not amount to significantly more, the dependent claims are not patent eligible.
Therefore, the claims here fail to contain any additional element(s) or combination of additional elements that can be considered as significantly more and the claims are rejected under 35 U.S.C. 101 for lacking eligible subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3-9, and 11-16 are rejected under 35 U.S.C. 103 as being unpatentable over Blake et al. (U.S. Patent Publication 2016/0022375 A1), referred to hereinafter as Blake, in view of Spector et al. (U.S. Patent Publication 2014/0200429 A1), referred to hereinafter as Spector.
Regarding claim 9, Blake teaches a system, comprising (Blake [0081] “Cardiac mapping and navigation system 300 may include, for example, the CARTO™ system by Johnson & Johnson or EnSite™ NAVX™ by St. Jude Medical.”):
an interface configured to receive an anatomical map of wall tissue of at least a portion of a cardiac chamber, the map superimposed with ablation tags (Blake [0081] “Cardiac mapping and navigation system 300 may include, for example, the CARTO™ system by Johnson & Johnson or EnSite™ NAVX™ by St. Jude Medical. Cardiac mapping and navigation systems 300 provide to a clinician the ability to map cardiac electrical potentials via a catheter inserted into the heart.” and Blake [0085] “In some embodiments, additional registration methods may include automatic integration with existing registration markers in a cardiac mapping and navigation system 300, automatic fitting to scar maps created during the ablation procedure, automatic fitting to other measurements made during the ablation procedure, integration with live imaging (echo, MRI, CT, fluoroscopy), and/or integration with other fiduciary markers such as those integrated in the Mediguide™ system.”); and
a processor, which is configured to (Blake [0034] “At import step 101, cardiac imaging data may be imported or received into a processing machine including at least one processing device configured to receive the cardiac imaging data. The at least one processing device may be part of, for example, a personal computer, a computer cluster, and a cardiac mapping and ablation system.”):
define a nonconductive zone around each ablation tag for at least some of the ablation tags, to calculate block areas (Blake [0087] “After completion of an initial registration in target map data registration step 801, registration verification step 802 may be performed. During registration verification step 802, mapping of the scar regions may be done to verify the registration as well as scar shape and location. A mapping catheter may be advanced to the location of scar tissue as identified by the fused map. This area may be electrically mapped and to ensure that these areas are indeed scar tissue. Thus, the registration may be verified and the fused map data confirmed. If the tissue that is mapped shows not to be scar tissue, but, for example, border zone tissue or healthy heart tissue, then a user can attempt to automatically refuse the images. Alternatively if the shape, size, or location of the fused map scar region does not match the electrically mapped region, the user may manually alter the target treatment map data to match the empirical results taken via electrical mapping.”, Blake [0094] “In other embodiments, treatment target sites 901 may be displayed as a series of concentric rings. In some embodiments, progressively larger concentric rings may represent increased probability of ablation success if the ablation lesion envelopes that ring. Due to potential errors in registration and catheter location, a clinician may be unable to precisely locate an ablation catheter tip at treatment target site 901. Thus, an ablation lesion may have a greater chance of successfully treating the treatment target site 901 if it is large enough to ablate surrounding tissue. A series of increasingly larger concentric rings may be sized based on these potential errors, and used to convey to an operator information about how the probability of ablation success corresponds to lesion size. If the potential errors associated with the equipment being used are small, a smaller lesion may have a higher probability of success, and the size of the concentric rings would increase in relatively small amounts. If the potential errors associated with the equipment being used are large, a larger lesion may be required to have a high probability of success, and the size of the concentric rings would increase by relatively larger amounts. This type of display may facilitate the use of different mapping, navigation, and ablation equipment with the systems and methods disclosed herein.”, Blake [0063] “Process metrics may further include propagation dynamics, such as conduction velocity or channel width. Conduction velocity may be calculated from data similar to that used to produce activation maps. Conduction velocity may be calculated as an average, e.g., a velocity of signal propagation from one point to another distant point, and as a discrete measure, e.g., a velocity of signal propagation between two adjacent nodes in the mesh. Channel width may be understood as a width of a channel through which a signal wavefront propagates. For example, if the signal wavefront is viewed as a surface that moves through space, its path can be used to create a tunnel or channel, extruded as the wavefront moves. The width of this channel may illustrate “critical pathways,” which may be blocked with a small number of ablation lesions. A channel may be display in a still image, a wavefront over time may be displayed in an animation, or the system may simply highlight locations where the width of the tunnel or channel is of a certain size, with or without numerical callouts indicating the size.”, and Blake [0102] “Following target treatment step 805, treated target display step 806 may be performed to display the treatment area, for example, an ablated region, on the fused map. A size and depth of the ablated region may be estimated based on at least one of a catheter 1010 that is used, parameters of the therapy delivery, and heart properties including thermal conductivity or resistance. Ablation size and depth estimates may be based on empirical and theoretical formulas. FIG. 11 illustrates an exemplary display of treated target 1101 along with target treatment sites 901 on fused map 900. The ablated region may be shown on the display as a specific color, e.g., a red dot. The user interface may also display an overlap of target treatment sites 901 and the treated target 1101 in several additional ways. Overlap may be displayed, for example, in a color that is different than both the target treatment site 901 and the treated target 1101. It may also be shown as the same color as one of the target treatment site 901 and the treated target 1101 with at least one different visual property including, but not limited to transparency, hue, intensity, glow, or other visual properties. Treated target display step 806 may illustrate a need to conduct multiple ablations in order to fully ablate target treatment site 901. A user may repeatedly return to target location step 804 and target treatment step 805 in order to fully treat the first target treatment site 901 as well as additionally identified target treatment sites 901.”);
receive from a user, markings on the map of a starting point and an ending point of a potential conduction flow (Blake [0071] “Following safety analysis, lesion site user analysis step 602 may be conducted to receive a user's input. A user may make custom maps either preferring or avoiding certain lesion sites, by marking such locations on a generic atlas heart, by marking such locations on the patient's medical images used for mesh generation, or by providing any other indication to the system of locations that the user would prefer to use or avoid. In some embodiments, a plurality of potential targets may be displayed, including redundant locations. As a user selects target locations for therapy, the displayed target locations may be dynamically altered based on the users selection. For example, where the simulation has determined that a lesion placed in a first location would obviate the need for a lesion in a second location, the second lesion location may be removed after the first is selected.”, and Blake [0063] “Process metrics may further include propagation dynamics, such as conduction velocity or channel width. Conduction velocity may be calculated from data similar to that used to produce activation maps. Conduction velocity may be calculated as an average, e.g., a velocity of signal propagation from one point to another distant point, and as a discrete measure, e.g., a velocity of signal propagation between two adjacent nodes in the mesh. Channel width may be understood as a width of a channel through which a signal wavefront propagates. For example, if the signal wavefront is viewed as a surface that moves through space, its path can be used to create a tunnel or channel, extruded as the wavefront moves. The width of this channel may illustrate “critical pathways,” which may be blocked with a small number of ablation lesions. A channel may be display in a still image, a wavefront over time may be displayed in an animation, or the system may simply highlight locations where the width of the tunnel or channel is of a certain size, with or without numerical callouts indicating the size.”);
conduction flow paths and the one or more existing paths taking into consideration the block areas (Blake [0063] “Process metrics may further include propagation dynamics, such as conduction velocity or channel width. Conduction velocity may be calculated from data similar to that used to produce activation maps. Conduction velocity may be calculated as an average, e.g., a velocity of signal propagation from one point to another distant point, and as a discrete measure, e.g., a velocity of signal propagation between two adjacent nodes in the mesh. Channel width may be understood as a width of a channel through which a signal wavefront propagates. For example, if the signal wavefront is viewed as a surface that moves through space, its path can be used to create a tunnel or channel, extruded as the wavefront moves. The width of this channel may illustrate “critical pathways,” which may be blocked with a small number of ablation lesions.” and Blake [0087] “After completion of an initial registration in target map data registration step 801, registration verification step 802 may be performed. During registration verification step 802, mapping of the scar regions may be done to verify the registration as well as scar shape and location. A mapping catheter may be advanced to the location of scar tissue as identified by the fused map. This area may be electrically mapped and to ensure that these areas are indeed scar tissue. Thus, the registration may be verified and the fused map data confirmed. If the tissue that is mapped shows not to be scar tissue, but, for example, border zone tissue or healthy heart tissue, then a user can attempt to automatically refuse the images. Alternatively if the shape, size, or location of the fused map scar region does not match the electrically mapped region, the user may manually alter the target treatment map data to match the empirical results taken via electrical mapping.”);
in response to identifying the one or more possible conduction flow paths from the starting point to the ending point, hiding the ablation tags and overlaying the one or more conduction flow paths, found by the search algorithm, on the anatomical map in real time during an ongoing ablation procedure (Blake [0095] “Treatment target sites 901 may be displayed in conjunction with other features of the fused map 901, including but not limited to the scar tissue, border zone tissue, activation maps, conduction pathways, resting membrane potential, local conduction velocity, activation delay, block lines, or a movie of activation. Any of these may also be displayed with or without treatment target sites 901.”, Blake [0097] “Following treatment target display at step 803, a treatment target may be located during target location step 804. During target location step 804, cardiac mapping system 300 may guide a treatment catheter ablation tip 1040 to a target treatment site 901. The following description of target location step 804 and following steps pertains to the use of a catheter ablation system 1000, such as that shown in FIG. 10, to perform treatment. Additional embodiments consistent with the present disclosure may utilize other suitable treatment modalities. During target location step 804, ablation catheter 1010 may be guided into the heart. An intracardiac location of an ablation tip 1040 of ablation catheter 1010 may be displayed on a cardiac mapping and navigation system 300. Ablation tip 1040 may be displayed on the fused map of the patient's heart, showing treatment targets 901. As ablation tip 1040 nears a selected treatment target 901, the user may be provided feedback indicating a proximity of ablation tip 1040 to the treatment target.”, Blake [0073] “In some embodiments, when selecting target locations for therapy, a user may prioritize or rank the locations. For example, a user may select a specific order in which locations should be targeted for ablation. In other embodiments, a user may provide specific rankings, e.g., on a 1-10 scale, of how important the target location is for ablative therapy. Automated analysis and simulation step 603 may be conducted after the lesion sites have been finalized. A clinician may optionally choose to re-run the simulation protocols to examine if the given lesions terminate arrhythmia within the simulation. During automated analysis and simulation step 603, a user may instruct the system to update the cardiac model based on the expected treatment of one or more of the identified target treatment sites and resimulate cardiac activity based on the updated model. The model may also be updated based on an expected outcome of treatment, where the expected outcome is based on a mode of treatment or device used for treatment. Predictions of expected outcomes are explained in greater detail below. A user may further iterate between designating ablation sites and visualizing the simulated effects of those ablation sites until they feel satisfied with the result. Changes to treatment targets may be marked in maps provided to the clinician, or left out of the information shown to the clinician. A user may set a threshold to limit the number of attempts to re-simulate the patient's heart iteratively in this process, based on, for example, clock time, computational cost, or number of attempts.”); and
receive from the user, an instruction to ablate tissue at a location along the one or more conduction flow paths (Blake [0097] “Following treatment target display at step 803, a treatment target may be located during target location step 804. During target location step 804, cardiac mapping system 300 may guide a treatment catheter ablation tip 1040 to a target treatment site 901. The following description of target location step 804 and following steps pertains to the use of a catheter ablation system 1000, such as that shown in FIG. 10, to perform treatment. Additional embodiments consistent with the present disclosure may utilize other suitable treatment modalities. During target location step 804, ablation catheter 1010 may be guided into the heart. An intracardiac location of an ablation tip 1040 of ablation catheter 1010 may be displayed on a cardiac mapping and navigation system 300. Ablation tip 1040 may be displayed on the fused map of the patient's heart, showing treatment targets 901. As ablation tip 1040 nears a selected treatment target 901, the user may be provided feedback indicating a proximity of ablation tip 1040 to the treatment target.” and Blake [0073] “In some embodiments, when selecting target locations for therapy, a user may prioritize or rank the locations. For example, a user may select a specific order in which locations should be targeted for ablation. In other embodiments, a user may provide specific rankings, e.g., on a 1-10 scale, of how important the target location is for ablative therapy. Automated analysis and simulation step 603 may be conducted after the lesion sites have been finalized. A clinician may optionally choose to re-run the simulation protocols to examine if the given lesions terminate arrhythmia within the simulation. During automated analysis and simulation step 603, a user may instruct the system to update the cardiac model based on the expected treatment of one or more of the identified target treatment sites and resimulate cardiac activity based on the updated model. The model may also be updated based on an expected outcome of treatment, where the expected outcome is based on a mode of treatment or device used for treatment. Predictions of expected outcomes are explained in greater detail below. A user may further iterate between designating ablation sites and visualizing the simulated effects of those ablation sites until they feel satisfied with the result. Changes to treatment targets may be marked in maps provided to the clinician, or left out of the information shown to the clinician. A user may set a threshold to limit the number of attempts to re-simulate the patient's heart iteratively in this process, based on, for example, clock time, computational cost, or number of attempts.”).
Blake fails to explicitly teach using a search algorithm, search for one or more possible paths from the starting point to the ending point.
Spector teaches using a search algorithm, search for one or more possible paths from the starting point to the ending point (Spector [0362] “The efficiency of ablation lesions can be maximized by making use of the previously identified locations of high circuit core density. Because high circuit density sites can be distributed throughout the surface of the atrial tissue in complex arrangements that vary by patient, finding a distribution of ablations that overlaps the largest number of high circuit density sites and connects to the tissue edge with the smallest total lesion length is an important optimization question.”, Spector [0363] “The connection of multiple sites using the shortest possible distance is as a combinatorial optimization problem that can be solved using a number of computer-based algorithmic solutions. For a small number of sites, the problem can be solved by exact algorithms, comparing every possible permutation to find the optimal solution. The complexity of the problem rises at the rate of O(n!). Thus, as the number of sites n increases, solving the problem by exact algorithms become increasingly inefficient and impractical.”, and Spector [0364] “Instead, heuristics or approximation algorithms can be used to reach a solution very quickly for large numbers of sites, although the solution may not be optimal and complete. Heuristics algorithms iteratively improve a solution until search termination criteria are met, rather than exploring every permutation. Different algorithms have different methods for choosing permutations on their iterations. The termination criteria can include the number of iterations, a threshold value, the speed at which a solution is improving, or a number of iterations without improvement. Some examples of heuristics algorithms include greedy algorithm, genetic algorithm, simulated annealing, particle swarm optimization, and ant colony optimization.”).
A person of ordinary skill in the art (PHOSITA) at the time of the invention would have found it obvious to combine the teachings of Blake and Spector to arrive at the claimed system. Blake teaches a cardiac mapping and navigation system that receives anatomical maps of cardiac tissue, identifies and displays scar or ablated regions, and presents conduction features (conduction pathways and block lines) on an electroanatomical map. Blake further teaches user interaction with the map, including marking or selecting treatment locations, and dynamically updating displayed information during an ablation procedure. These teachings collectively establish a system environment in which cardiac tissue regions are classified (scar vs. viable tissue), displayed, and used to guide ablation decisions.
Spector supports Blake by teaching the use of computer search and optimization algorithms to determine efficient connections among spatially distributed cardiac sites, particularly in the context of ablation planning. Spector teaches that identifying optimal paths or connections among cardiac regions, while accounting for constraints such as minimizing distance or maximizing therapeutic effectiveness, can be formulated as a combinatorial optimization problem and solved using heuristic or search-based algorithms. A PHOSITA would have recognized that these known algorithmic techniques are readily applicable to determining possible conduction pathways between user selected points on a cardiac map, particularly when certain regions (car tissue) function as nonconductive or blocked areas.
It would therefore have been obvious to incorporate Spector’s search based pathfinding techniques into Blake’s cardiac mapping system to enable automatic determination of possible conduction flow paths between selected start and end points while accounting for nonconductive (scar and ablated) regions identified in the map. The combination represents a predictable use of prior art elements according to their established functions, specifically applying known computational search techniques to known cardiac mapping data to improve visualization and planning of ablation procedures. Additionally, it would have been obvious to overlay the resulting conduction paths on the anatomical map and to selectively display or omit other map elements (ablation tags), as Blake teaches dynamic and selective visualization of different cardiac features. This modification would have been motivated by the well-understood goal of reducing visual clutter and enhancing the clinician’s ability to interpret relevant conduction information in real time during an ablation procedure.
Accordingly, the combined teachings of Blake and Spector render obvious the recited system, including defining nonconductive zones, receiving user identified locations, applying a search algorithm to determine possible conduction paths that account for blocked regions, and displaying the resulting paths on the anatomical map for use in guiding ablation. The claimed invention therefore represents no more than the predictable application of known techniques to improve cardiac ablation planning and visualization.
Regarding claim 11, Blake and Spector teach the invention in claim 9, as discussed above, and further teach wherein the nonconductive zone around a given ablation tag is a sphere of a given size derived from an ablation index value of the given ablation tag (Blake [0101] “When target location step 804 is complete, and ablation tip 1040 has reached an appropriate target treatment site 901, target treatment may be delivered during target treatment step 805. In some embodiments, target treatment delivery may include ablation of target treatment site 901. RF generator 1030 may deliver radiofrequency energy to ablation tip 1040 in order to ablate target treatment site 901. Any suitable ablation catheter 1010 and RF generator 1030 may be used for target treatment step 805. Based on the known characteristics of the ablation catheter 1010 and RF generator 1030 that are used, appropriate parameters for ablation of target treatment site 901 may be determined. For example, wattage, therapy duration, irrigation rate, target site temperature, tip pressure (contact force), etc., may be selected to produce a lesion of an appropriate size to fully ablate target treatment site 901. In some embodiments, ablation parameters may be suggested, for example by the cardiac mapping and navigation system 300 or by any suitable associated processing device, based on the selected target treatment site 901 and the catheter 1010 being used. In some embodiments, based on the selected target treatment site 901, the use of a particular type of catheter 1010 may be suggested.”, and Blake [0102] “Following target treatment step 805, treated target display step 806 may be performed to display the treatment area, for example, an ablated region, on the fused map. A size and depth of the ablated region may be estimated based on at least one of a catheter 1010 that is used, parameters of the therapy delivery, and heart properties including thermal conductivity or resistance. Ablation size and depth estimates may be based on empirical and theoretical formulas. FIG. 11 illustrates an exemplary display of treated target 1101 along with target treatment sites 901 on fused map 900. The ablated region may be shown on the display as a specific color, e.g., a red dot. The user interface may also display an overlap of target treatment sites 901 and the treated target 1101 in several additional ways. Overlap may be displayed, for example, in a color that is different than both the target treatment site 901 and the treated target 1101. It may also be shown as the same color as one of the target treatment site 901 and the treated target 1101 with at least one different visual property including, but not limited to transparency, hue, intensity, glow, or other visual properties. Treated target display step 806 may illustrate a need to conduct multiple ablations in order to fully ablate target treatment site 901. A user may repeatedly return to target location step 804 and target treatment step 805 in order to fully treat the first target treatment site 901 as well as additionally identified target treatment sites 901.”).
It would have been obvious to a person having ordinary skill in the art at the time of the invention to represent the nonconductive zone around an ablation tag as a sphere having a size derived from an ablation index value in view of Blake. Blake teaches that ablation lesions are produced using controllable parameters such as wattage, duration, irrigation rate, and contact force, and that these parameters are selected to achieve a lesion of an appropriate size. Blake further teaches that the resulting ablated region has a quantifiable size and depth that can be estimated using empirical and theoretical formulas and displayed on a cardiac map. A person of ordinary skill in the art would have recognized that these multiple ablation parameters may be combined or abstracted into a single representative value (an ablation index) for purposes of simplifying computation and visualization of lesion extent. Additionally, because ablation lesions propagate outward from a treatment site in a generally radial manner, it would have been a predictable and well known design choice to approximate the resulting nonconductive region using a simple geometric shape such as a sphere centered at the ablation location, with the radius corresponding to the estimated lesion size. This representation would have facilitated efficient computation, visualization, and integration into mapping systems, while maintaining sufficient clinical accuracy. Accordingly, representing the nonconductive zone as a sphere of a size derived from an ablation index value constitutes the predictable use of known techniques and design choices, and therefore would have been obvious.
Regarding claim 12, Blake and Spector teach the invention in claim 11, as discussed above, and further teach wherein the processor is configured to calculate the block areas by calculating an intersection of the sphere and a surface of the anatomical map (Blake [0102] “Following target treatment step 805, treated target display step 806 may be performed to display the treatment area, for example, an ablated region, on the fused map. A size and depth of the ablated region may be estimated based on at least one of a catheter 1010 that is used, parameters of the therapy delivery, and heart properties including thermal conductivity or resistance. Ablation size and depth estimates may be based on empirical and theoretical formulas. FIG. 11 illustrates an exemplary display of treated target 1101 along with target treatment sites 901 on fused map 900. The ablated region may be shown on the display as a specific color, e.g., a red dot. The user interface may also display an overlap of target treatment sites 901 and the treated target 1101 in several additional ways. Overlap may be displayed, for example, in a color that is different than both the target treatment site 901 and the treated target 1101. It may also be shown as the same color as one of the target treatment site 901 and the treated target 1101 with at least one different visual property including, but not limited to transparency, hue, intensity, glow, or other visual properties. Treated target display step 806 may illustrate a need to conduct multiple ablations in order to fully ablate target treatment site 901. A user may repeatedly return to target location step 804 and target treatment step 805 in order to fully treat the first target treatment site 901 as well as additionally identified target treatment sites 901.”) and Blake [0086] “In some embodiments, target map data may be registered to other heart models used for the navigation of the ablation catheter, including but not limited to models created by CartoMerge and the endocardial surface maps created by the mapping and navigation system(s).”).
It would have been obvious to a person having ordinary skill in the art at the time of the invention to calculate block areas by determining an intersection between a lesion region and a surface of an anatomical map in view of Blake. Blake teaches that an ablated region has a quantifiable size and depth and is displayed on a fused anatomical map, which establishing that the lesion occupies a defined spatial region relative to the anatomy. Blake further teaches that target map data is registered to anatomical heart models, including endocardial surface maps, indicating that the system operates on a defined surface representation of cardiac tissue. A person of ordinary skill in the art would have recognized that, when a volumetric lesion region is represented within a registered anatomical surface model, determining the portion of the lesion that affects the tissue surface implicitly involves identifying where that region intersects the surface geometry. Performing such an intersection would have been a routine and predictable computational step in integrating lesion geometry with anatomical surface models for visualization, analysis, and treatment planning. Accordingly, calculating block areas by determining an intersection between a lesion region and the anatomical surface represents the predictable use of known geometric modeling techniques within Blake’s system and would have been obvious.
Regarding claim 13, Blake and Spector teach the invention in claim 9, as discussed above, and further teach wherein the processor is configured to search for the one or more conduction flow paths by using a first search algorithm (Blake [0034] “At import step 101, cardiac imaging data may be imported or received into a processing machine including at least one processing device configured to receive the cardiac imaging data. The at least one processing device may be part of, for example, a personal computer, a computer cluster, and a cardiac mapping and ablation system.”, and Blake [0063] “Process metrics may further include propagation dynamics, such as conduction velocity or channel width. Conduction velocity may be calculated from data similar to that used to produce activation maps. Conduction velocity may be calculated as an average, e.g., a velocity of signal propagation from one point to another distant point, and as a discrete measure, e.g., a velocity of signal propagation between two adjacent nodes in the mesh. Channel width may be understood as a width of a channel through which a signal wavefront propagates. For example, if the signal wavefront is viewed as a surface that moves through space, its path can be used to create a tunnel or channel, extruded as the wavefront moves. The width of this channel may illustrate “critical pathways,” which may be blocked with a small number of ablation lesions.” and
Spector [0362] “The efficiency of ablation lesions can be maximized by making use of the previously identified locations of high circuit core density. Because high circuit density sites can be distributed throughout the surface of the atrial tissue in complex arrangements that vary by patient, finding a distribution of ablations that overlaps the largest number of high circuit density sites and connects to the tissue edge with the smallest total lesion length is an important optimization question. [0363] The connection of multiple sites using the shortest possible distance is as a combinatorial optimization problem that can be solved using a number of computer-based algorithmic solutions. For a small number of sites, the problem can be solved by exact algorithms, comparing every possible permutation to find the optimal solution. The complexity of the problem rises at the rate of O(n!). Thus, as the number of sites n increases, solving the problem by exact algorithms become increasingly inefficient and impractical. [0364] Instead, heuristics or approximation algorithms can be used to reach a solution very quickly for large numbers of sites, although the solution may not be optimal and complete. Heuristics algorithms iteratively improve a solution until search termination criteria are met, rather than exploring every permutation. Different algorithms have different methods for choosing permutations on their iterations. The termination criteria can include the number of iterations, a threshold value, the speed at which a solution is improving, or a number of iterations without improvement. Some examples of heuristics algorithms include greedy algorithm, genetic algorithm, simulated annealing, particle swarm optimization, and ant colony optimization.”).
It would have been obvious to a person having ordinary skill in the art at the time of the invention to configure the processor of Blake to search for one or more conduction flow paths using a first search algorithm in view of Spector. Blake teaches a cardiac mapping and ablation system that models cardiac tissue, evaluates propagation dynamics (conduction velocity and channel width), and identifies conduction pathways and regions relevant to ablation therapy, which establish that determining conduction pathways through cardiac tissue is a key analytical objective. However, Blake does not explicitly describe the use of a formal search algorithm to identify such pathways. Spector teaches that spatially distributed cardiac sites and conduction structures can be analyzed using computer algorithmic solutions, including heuristic and optimization algorithms, to efficiently identify paths or connections that satisfy particular constraints (minimizing distance or maximizing coverage). A person of ordinary skill in the art would have recognized that identifying conduction flow paths between locations in cardiac tissue, specifically in the presence of constraints such as nonconductive regions, constitutes a known computational search or optimization problem, and would have been motivated to apply Spector’s taught search algorithms within Blake’s system to automate and improve the identification of such pathways. This combination represents the predictable use of known algorithmic techniques to enhance an existing cardiac mapping system by enabling efficient and systematic determination of conduction paths, and therefore renders the claimed use of a first search algorithm obvious.
Regarding claim 14, Blake and Spector teach the invention in claim 13, as discussed above, and further teach wherein the processor is configured to use a first search algorithm by using an A* path search algorithm (Blake [0034] “At import step 101, cardiac imaging data may be imported or received into a processing machine including at least one processing device configured to receive the cardiac imaging data. The at least one processing device may be part of, for example, a personal computer, a computer cluster, and a cardiac mapping and ablation system.” Blake [0063] “Process metrics may further include propagation dynamics, such as conduction velocity or channel width. Conduction velocity may be calculated from data similar to that used to produce activation maps. Conduction velocity may be calculated as an average, e.g., a velocity of signal propagation from one point to another distant point, and as a discrete measure, e.g., a velocity of signal propagation between two adjacent nodes in the mesh. Channel width may be understood as a width of a channel through which a signal wavefront propagates. For example, if the signal wavefront is viewed as a surface that moves through space, its path can be used to create a tunnel or channel, extruded as the wavefront moves. The width of this channel may illustrate “critical pathways,” which may be blocked with a small number of ablation lesions. A channel may be display in a still image, a wavefront over time may be displayed in an animation, or the system may simply highlight locations where the width of the tunnel or channel is of a certain size, with or without numerical callouts indicating the size.” and
Spector [0362] “The efficiency of ablation lesions can be maximized by making use of the previously identified locations of high circuit core density. Because high circuit density sites can be distributed throughout the surface of the atrial tissue in complex arrangements that vary by patient, finding a distribution of ablations that overlaps the largest number of high circuit density sites and connects to the tissue edge with the smallest total lesion length is an important optimization question. Spector [0363] “The connection of multiple sites using the shortest possible distance is as a combinatorial optimization problem that can be solved using a number of computer-based algorithmic solutions. For a small number of sites, the problem can be solved by exact algorithms, comparing every possible permutation to find the optimal solution. The complexity of the problem rises at the rate of O(n!). Thus, as the number of sites n increases, solving the problem by exact algorithms become increasingly inefficient and impractical.”, Spector [0364] “Instead, heuristics or approximation algorithms can be used to reach a solution very quickly for large numbers of sites, although the solution may not be optimal and complete. Heuristics algorithms iteratively improve a solution until search termination criteria are met, rather than exploring every permutation. Different algorithms have different methods for choosing permutations on their iterations. The termination criteria can include the number of iterations, a threshold value, the speed at which a solution is improving, or a number of iterations without improvement. Some examples of heuristics algorithms include greedy algorithm, genetic algorithm, simulated annealing, particle swarm optimization, and ant colony optimization.”).
It would have been obvious to a person having ordinary skill in the art at the time of the invention to implement the recited “first search algorithm” as an A* path search algorithm in the system of Blake in view of Spector. Blake teaches a cardiac mapping and ablation system that processes cardiac data and analyzes propagation dynamics, including conduction paths and channels through cardiac tissue between locations, which establish that identifying pathways through a spatial domain is a central computational task. Spector further teaches that determining connections between spatially distributed sites while minimizing distance or satisfying constraints constitutes a computational optimization problem that can be solved using computer search and heuristic algorithms. A person of ordinary skill in the art would have recognized that identifying conduction flow paths between points in cardiac tissue, particularly while accounting for constraints such as blocked regions, corresponds to a well-known shortest-path problem in a graph-like spatial model. It would have been further obvious to select a known heuristic pathfinding algorithm, such as A*, as one of a finite number of predictable solutions for efficiently solving such shortest-path problems, given its widespread use in computing for determining optimal paths using cost and heuristic functions. Accordingly, configuring the processor to use an A* path search algorithm represents the predictable application of a known algorithmic technique to improve the efficiency and automation of pathway identification in Blake’s system, and therefore would have been obvious.
Regarding claim 15, Blake and Spector teach the invention in claim 9, as discussed above, and further teach and the processor is further configured to provide a graphical user interface (GUI) configured to allow the user to select at least one of (i) whether to show the ablation tags on the overlayed anatomical map, and (ii) whether to calculate sizes of nonconductive zones according to a level of existing ablation therein (Blake [0095] “Treatment target sites 901 may be displayed in conjunction with other features of the fused map 901, including but not limited to the scar tissue, border zone tissue, activation maps, conduction pathways, resting membrane potential, local conduction velocity, activation delay, block lines, or a movie of activation. Any of these may also be displayed with or without treatment target sites 901.” Blake [0091] “FIG. 9a illustrates a fused map 900 with treatment target sites 901 shown as outlines. FIG. 9b illustrates a fused map 900 with treatment target sites 901 tagged with text markers. FIG. 9c illustrates a fused map 900 with treatment target sites 901 marked with spires. FIG. 9d illustrates a fused map 900 with treatment target sites 901 tagged with text markers, and an overlay of identified tissue zones. This overly may permit a user to understand how potential lesion placement and identified tissue zones coincide. and Blake [0089] “In some embodiments, a user interface (UI) of the system may show both the original and new target locations. The UI may distinguish between the new and the old target locations by one of color, intensity, hue, transparency, or other methods. The target locations may also be labeled with words, numbers or symbols.”).
It would have been obvious to a person of ordinary skill in the art (PHOSITA) at the time of the invention to provide a graphical user interface (GUI) that allows a user to selectively control the display of ablation features, such as ablation tags, on an anatomical map. Blake teaches a cardiac mapping system with a user interface that presents treatment target sites and other cardiac features using various visual representations, including color, transparency, and labeling. Blake further teaches that such features may be displayed “with or without” other map features, which indicates that the system supports selective inclusion or omission of specific visual elements. A PHOSITA would have recognized that this capability inherently involves user-selectable display options within the GUI. In view of these teachings, it would have been a predictable and routine design choice to allow a user to toggle the visibility of specific elements (ablation tags) on the anatomical map in order to manage visual clutter and enhance interpretability during a cardiac ablation procedure. Providing such user selectable display controls represents nothing more than the application of well-known GUI techniques to a known medical visualization system, yielding the expected benefit of improved usability. Accordingly, the claimed limitation of a GUI configured to allow the user to select whether to show ablation tags on the overlayed anatomical map would have been obvious over Blake.
Regarding claim 16, Blake and Spector teach the invention in claim 9, as discussed above, and further teach wherein the anatomical map is an electroanatomical (EA) map (Blake [0096] “Either while the simulations described above are running, or after the simulations have been run, data from the simulations may be displayed interactively to the user. In some embodiments, the user may view static mesh geometry overlaid with electro-anatomical maps of the patient's cardiac geometry recorded in real time by the clinician.”).
It would have been obvious to a person of ordinary skill in the art (PHOSITA) at the time of the invention for the anatomical map used in the system to be an electroanatomical (EA) map, as recited in claim 16. Blake teaches the use and display of electro-anatomical maps of a patient’s cardiac geometry in a cardiac mapping and ablation system, which are standard tools in electrophysiology procedures for visualizing electrical activity in conjunction with anatomical structure. Given that Blake’s system is directed to cardiac mapping, simulation, and ablation guidance, a PHOSITA would have understood that implementing the claimed system using an EA map represents a well-known and conventional mapping technique. Therefore, specifying that the anatomical map is an EA map amounts to a predictable design choice and does not impart patentable distinction over the prior art.
Claims 1-8 are analogous to claims 9-16, thus claims 1-8 are similarly analyzed and rejected in a manner consistent with the rejection of claims 9-16.
Response to Arguments
Applicant’s arguments and amendments, see Remarks/Amendments submitted on 02/17/2026 with respect to the rejection of the claims have been carefully considered and is addressed below.
Claim Rejections - 35 USC § 101
Applicant’s arguments regarding eligibility are not persuasive. Applicant states that the amended claims are no longer directed to an abstract idea because they recite an ablative treatment step and therefore integrate any judicial exception into a practical application. However, the claims do not recite performing an ablative treatment or controlling a medical device to affect the treatment. Instead, the claims recite “receiving from the user, an instruction to ablate tissue at a location along the one or more conduction flow paths.” This limitation involves the receipt of information or an instruction and does not itself cause or implement any physical treatment of tissue. Therefore, the claim does not apply the alleged abstract idea to affect a particular treatment of a disease or medical condition.
MPEP 2106.04(d)(2) applies where a claim meaningfully limits a judicial exception by using it to perform a specific therapeutic or prophylactic action. In this case, the claims are focused on determining possible conduction flow paths using a search algorithm based on spatial constraints and then presenting or receiving information related to that determination. The additional limitation of receiving an instruction to ablate does not integrate the abstract idea into a practical application, but is instead a post-solution activity that merely communicates or records a decision based on the abstract analysis. Consistent with Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350 (Fed. Cir. 2016), the claims are directed to collecting data, analyzing it, and presenting results, which does not amount to significantly more than the abstract idea.
Also, as noted in In re Brown, 645 F. App’x 1014 (Fed. Cir. 2016), merely providing or outputting a result or instruction based on an abstract determination does not render a claim patent eligible. The claimed receipt of an instruction to ablate tissue similarly represents an insignificant application of the underlying abstract idea, as it does not impose any meaningful limitation on how the analysis is performed nor does it improve any technological process or system. Accordingly, the amendment does not overcome the rejection under 35 U.S.C. § 101, and the claims remain directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
Applicant’s arguments have been fully considered but are not persuasive. The rejection of the claims under 35 U.S.C. § 103 over Blake in view of Spector is maintained because the cited combination teaches or at least renders obvious the claimed features. With respect to the limitation “receive from a user, markings on the map of a starting point and an ending point of a potential conduction flow,” Blake teaches receiving user input in the form of markings or selections on a cardiac map, including user-defined locations for treatment planning. Blake further teaches modeling propagation dynamics and conduction pathways. A person of ordinary skill in the art would have understood that identifying conduction pathways implicitly involves defining spatial points (endpoints or regions of interest) within the mapped cardiac tissue. Thus, it would have been an obvious design choice to allow a user to designate specific start and end points for evaluating conduction paths, as this represents a predictable use of user input to constrain or guide the underlying conduction analysis performed by Blake.
Regarding the “search algorithm” limitation and identification of conduction flow paths “taking into consideration the block areas,” Blake teaches modeling of conduction pathways and identification of regions that may be blocked by ablation lesions. Spector further teaches the use of computer-based optimization and search algorithms, including heuristic approaches, to determine efficient paths or connections across cardiac tissue in view of ablation constraints. It would have been obvious to incorporate such known search and optimization techniques into Blake’s system in order to analyze possible conduction paths in the presence of ablation induced block regions, because doing this applies known algorithmic tools to improve analysis of cardiac conduction, which is an application within the ordinary skill in the art.
Applicant’s statement regarding “hiding the ablation tags and overlaying the one or more conduction flow paths, found by the search algorithm, on the anatomical map in real time during an ongoing ablation procedure” is also unpersuasive. Blake teaches that different map features (including treatment target sites) may be displayed “with or without” other features on a fused map, and that visualization is interactive and occurs during the procedure with real-time catheter guidance. This teaching reasonably suggests selective display or suppression of certain visual elements (ablation tags) while emphasizing others (conduction pathways or activation maps) to improve clinician interpretation. It would have been obvious to a person of ordinary skill in the art to hide ablation tags when overlaying other diagnostically relevant information, such as computed conduction paths, as a matter of routine visualization optimization to reduce clutter and enhance usability during a live procedure.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure.
Afonso et al. (U.S. Patent 2017/0311833) teaches a system that uses medical devices and an electronic control unit to collect and analyze electrophysiological data to generate and update detailed spatial maps that assist in diagnosing arrythmias and guiding catheter therapy.
Passerini et al. (U.S. Patent 2015/0294082A1) teaches a system of patient specific guidance of cardiac arrythmia therapies in which the anatomical heart model is generated from medical imaging data, and the cardiac electrophysiological model is produced using the anatomical model and patient electrophysiological measurements, and ablation targets are displayed on the model.
Boveja et al. (U.S. Patent 10413185 B1) teaches a system and method for atrial fibrillation ablation using cardiac mapping that overlays and aligns multiple medical images to mark ablation sites in 3D imaging.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/K.R.L./Examiner, Art Unit 3685
/KAMBIZ ABDI/Supervisory Patent Examiner, Art Unit 3685
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