DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) was submitted on 11/20/2024. 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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-15 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 1, the claim recites the limitation “a net probability of localizing AF source in the one or more atrial meshes” in lines 18-19. It is unclear whether the net probability is a probability of how likely an AF source can be located within the one or more atrial meshes or alternatively a probability of how likely any particular region within the atrial mesh can be identified as an AF source. The scope of the limitation is unclear because one of ordinary skill in the art would be unable to determine the interpretation to be either the single probability for an entire mesh or the regional probability for a region of AF source within an overall mesh. This renders the claim unclear and rejected for indefiniteness.
Regarding claim 1, the claim recites the limitation “wherein the one or more atrial meshes having a net probability exceeding a threshold of net probability indicate locations of source of atrial fibrillation” in lines 21-22. It is unclear whether the net probability is a probability of the overall atrial mesh or whether it is a net probability of a particular region of atrial fibrillation. If the limitation is directed to a probability of the overall atrial mesh, it is unclear how an overall probability would be used to indicate a particular source location within the atrial mesh. The scope of the limitation is unclear because one of ordinary skill in the art would be unable to determine the interpretation to be either the single probability for an entire mesh or the regional probability for a region of AF source within an overall mesh. This renders the claim unclear and rejected for indefiniteness.
Regarding claim 6, the claim recites the limitation “a net probability of localizing AF source in the one or more atrial meshes” in lines 19-20. It is unclear whether the net probability is a probability of how likely an AF source can be located within the one or more atrial meshes or alternatively a probability of how likely any particular region within the atrial mesh can be identified as an AF source. The scope of the limitation is unclear because one of ordinary skill in the art would be unable to determine the interpretation to be either the single probability for an entire mesh or the regional probability for a region of AF source within an overall mesh. This renders the claim unclear and rejected for indefiniteness.
Regarding claim 6, the claim recites the limitation “wherein the one or more atrial meshes having a net probability exceeding a threshold of net probability indicate locations of source of atrial fibrillation” in lines 21-23. It is unclear whether the net probability is a probability of the overall atrial mesh or whether it is a net probability of a particular region of atrial fibrillation. If the limitation is directed to a probability of the overall atrial mesh, it is unclear how an overall probability would be used to indicate a particular source location within the atrial mesh. The scope of the limitation is unclear because one of ordinary skill in the art would be unable to determine the interpretation to be either the single probability for an entire mesh or the regional probability for a region of AF source within an overall mesh. This renders the claim unclear and rejected for indefiniteness.
Regarding claim 11, the claim recites the limitation “a net probability of localizing AF source in the one or more atrial meshes” in lines 16-17. It is unclear whether the net probability is a probability of how likely an AF source can be located within the one or more atrial meshes or alternatively a probability of how likely any particular region within the atrial mesh can be identified as an AF source. The scope of the limitation is unclear because one of ordinary skill in the art would be unable to determine the interpretation to be either the single probability for an entire mesh or the regional probability for a region of AF source within an overall mesh. This renders the claim unclear and rejected for indefiniteness.
Regarding claim 11, the claim recites the limitation “wherein the one or more atrial meshes having a net probability exceeding a threshold of net probability indicate locations of source of atrial fibrillation” in lines 18-20. It is unclear whether the net probability is a probability of the overall atrial mesh or whether it is a net probability of a particular region of atrial fibrillation. If the limitation is directed to a probability of the overall atrial mesh, it is unclear how an overall probability would be used to indicate a particular source location within the atrial mesh. The scope of the limitation is unclear because one of ordinary skill in the art would be unable to determine the interpretation to be either the single probability for an entire mesh or the regional probability for a region of AF source within an overall mesh. This renders the claim unclear and rejected for indefiniteness.
Claims dependent upon rejected claims are also rejected for indefiniteness. Therefore, dependent claims 2-5, 7-10, and 12-15 are also rejected.
Claim Rejections - 35 USC § 103
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.
Claims 1, 6, and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Mihalef et al. (U.S. Pub. No. 20170255745) hereinafter Mihalef, in view of Mansi et al. (U.S. Pub. No. 20190223819) hereinafter Mansi, in view of Lo et al. (U.S. Pub. No. 20150230721) hereinafter Lo, in view of Atienza, F., et al. (“Real-time Dominant Frequency Mapping and Ablation of Dominant-Frequency Sites in Atrial Fibrillation with Left-to-Right Frequency Gradients Predicts Long-Term Maintenance of Sinus Rhythm,” Heart Rhythm. Vol 6(1), 2009. P. 33-40) hereinafter Atienza (see attached NPL reference for citations), in further view of Ghoraani et al. (U.S. Pub. No. 20190104962) hereinafter Ghoraani.
Regarding claim 1, primary reference Mihalef teaches:
A processor implemented method (abstract) comprising:
obtaining, via one or more hardware processors, a plurality of heart scan images and a plurality of torso scan images ([0017], medical image data forms clinical data that includes both heart and torso data ([0020]-[0021]); [0030]-[0033], torso model constructed from torso image data for patient specific torso mesh generation);
extracting, via the one or more hardware processors, a) one or more atrial meshes from the plurality of heart scan images, and b) one or more torso meshes from the plurality of torso scan images ([0020]-[0024], atrial mesh and cardiac mesh are generated for the patient; [0030]-[0033], torso model constructed from torso image data for patient specific torso mesh generation);
Primary reference Mihalef fails to teach:
sampling, via the one or more hardware processors, one or more Body Surface Potential (BSP) signals from the one or more torso meshes and the one or more atrial meshes;
determining, via the one or more hardware processors, a cardiac potential from the one or more BSP signals
However, the analogous art of Mansi of a non-invasive EP mapping generation method (abstract) teaches:
sampling, via the one or more hardware processors, one or more Body Surface Potential (BSP) signals from the one or more torso meshes and the one or more atrial meshes ([0054]-[0055], body surface potential map is generated from the 3D surface input, which in the combined invention with Mihalef would be the combined atrial and torso meshes generated from input image data; [0056]-[0066]; [0085], body surface potential map and projected to the heart mesh);
determining, via the one or more hardware processors, a cardiac potential from the one or more BSP signals ([0048]-[0057]; [0058], virtual heart model potentials generated from the map form a cardiac potential from the one or more BSP signals; [0061]-[0063]; [0085]);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the atrial and torso mesh generation for cardiac function analysis method of Mihalef to incorporate the generation of body surface potential signals and a cardiac potential as taught by Mansi because using a body surface potential map in combination with back projecting potentials to a heart surface increases the accuracy of a generated cardiac potential map, leading to higher quality clinical diagnostics (Mansi, [0057]).
Primary reference Mihalef further fails to teach:
identifying, via the one or more hardware processors, one or more probable rotor regions in the one or more atrial meshes based on the cardiac potential
However, the analogous art of Lo of an atrial fibrillation characterizing method (abstract) teaches:
identifying, via the one or more hardware processors, one or more probable rotor regions in the one or more atrial meshes based on the cardiac potential ([0087]-[0103], particularly [0088], predicting rotor location in critical regions based upon AF signals form probably rotor regions based upon atrial meshes of cardiac potential in the combined prior art invention of Mihalef and Mansi; [0108]-[0112]);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the atrial and torso mesh generation for cardiac function analysis method of Mihalef and Mansi to incorporate the identifying of rotor regions as taught by Lo because accurate identification of rotor regions in persistent AF assists in facilitating an electrophysiologist to search for the critical atrial substrate in maintaining AF (Lo, [0005]).
Primary reference Mihalef further fails to teach:
determining, via the one or more hardware processors, an Atrial Fibrillation-Dominant Frequency (AF-DF) probability based on the cardiac potential
However, the analogous art of Atienza of a localizing of high-frequency activity during atrial fibrillation method (abstract) teaches:
determining, via the one or more hardware processors, an Atrial Fibrillation-Dominant Frequency (AF-DF) probability based on the cardiac potential (pages 2-3, Methods; pages 6-7, Discussion, DFmax sites identified in AF patients form dominant frequency maximum sites based upon the measured cardiac potentials of the patient; page 5, Predictors of arrhythmia recurrence, DF sites are higher probability of remaining free of arrhythmias which forms a probability determined for the measured sites); and
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the atrial and torso mesh generation for cardiac function analysis method of Mihalef, Mansi, and Lo to incorporate the dominant frequency site analysis as taught by Atienza because ablation of the sites in a treatment shows better clinical outcomes than other regions (Atienza, Abstract, Results).
Primary reference Mihalef further fails to teach:
determining, via the one or more hardware processors, a net probability of localizing AF source in the one or more atrial meshes by combining the identified one or more probable rotor regions and the AF-DF probability, wherein the one or more atrial meshes having a net probability exceeding a threshold of net probability indicate locations of source of atrial fibrillation
However, the analogous art of Ghoraani of a system and method for guidance to a location of a propagating wave source (abstract) teaches:
determining, via the one or more hardware processors, a net probability of localizing AF source in the one or more atrial meshes by combining the identified one or more probable rotor regions and the AF-DF probability, wherein the one or more atrial meshes having a net probability exceeding a threshold of net probability indicate locations of source of atrial fibrillation ([0060]-[0062]; [0076]-[0078]; [0079], “The type of AF source(s) (e.g., rotor, foci or other type) and/or the probability of an AF source at each delineated region may be provided along with the AF ablation target map. The AF ablation target map may be a 2D or 3D map which is quickly and effectively generated via the present solution.” This includes rotor regions and the AF source, based upon probability and determines the net probability within the generated map; [0101]-[0103], figure 19 shows probability of points of the cluster points for the propagating wave source; This forms a net probability of the AF source within the atrial meshes in the combined prior art invention of Mihalef, Mansi, Lo, and Atienza).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the atrial and torso mesh generation for cardiac function analysis method of Mihalef, Mansi, Lo, and Atienza to incorporate the net probability of localizing an AF source as taught by Ghoraani because the enhanced accuracy in targeting of AF sources within the regions of interest lead to higher quality interventional procedures and improved clinical outcomes for procedures such as ablation catheter procedures (Ghoraani, [0077]-[0079]).
Regarding claim 6, primary reference Mihalef teaches:
A system comprising (abstract):
a memory storing instructions ([0044]); one or more communication interfaces ([0044]); and
one or more hardware processors coupled to the memory via the one or more communication interfaces, wherein the one or more hardware processors are ([0044]) configured by the instructions to:
obtain a plurality of heart scan images and a plurality of torso scan images ([0017], medical image data forms clinical data that includes both heart and torso data ([0020]-[0021]); [0030]-[0033], torso model constructed from torso image data for patient specific torso mesh generation);
extract a) one or more atrial meshes from the plurality of heart scan images, and b) one or more torso meshes from the plurality of torso scan images ([0020]-[0024], atrial mesh and cardiac mesh are generated for the patient; [0030]-[0033], torso model constructed from torso image data for patient specific torso mesh generation);
Primary reference Mihalef fails to teach:
sample one or more Body Surface Potential (BSP) signals from the one or more torso meshes and the one or more atrial meshes;
determine a cardiac potential from the one or more BSP signals
However, the analogous art of Mansi of a non-invasive EP mapping generation method (abstract) teaches:
sample one or more Body Surface Potential (BSP) signals from the one or more torso meshes and the one or more atrial meshes ([0054]-[0055], body surface potential map is generated from the 3D surface input, which in the combined invention with Mihalef would be the combined atrial and torso meshes generated from input image data; [0056]-[0066]; [0085], body surface potential map and projected to the heart mesh);
determine a cardiac potential from the one or more BSP signals ([0048]-[0057]; [0058], virtual heart model potentials generated from the map form a cardiac potential from the one or more BSP signals; [0061]-[0063]; [0085]);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the atrial and torso mesh generation for cardiac function analysis method of Mihalef to incorporate the generation of body surface potential signals and a cardiac potential as taught by Mansi because using a body surface potential map in combination with back projecting potentials to a heart surface increases the accuracy of a generated cardiac potential map, leading to higher quality clinical diagnostics (Mansi, [0057]).
Primary reference Mihalef further fails to teach:
identify one or more probable rotor regions in the one or more atrial meshes based on the cardiac potential
However, the analogous art of Lo of a atrial fibrillation characterizing method (abstract) teaches:
identify one or more probable rotor regions in the one or more atrial meshes based on the cardiac potential ([0087]-[0103], particularly [0088], predicting rotor location in critical regions based upon AF signals form probably rotor regions based upon atrial meshes of cardiac potential in the combined prior art invention of Mihalef and Mansi; [0108]-[0112]);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the atrial and torso mesh generation for cardiac function analysis method of Mihalef and Mansi to incorporate the identifying of rotor regions as taught by Lo because accurate identification of rotor regions in persistent AF assists in facilitating an electrophysiologist to search for the critical atrial substrate in maintaining AF (Lo, [0005]).
Primary reference Mihalef further fails to teach:
determine an Atrial Fibrillation-Dominant Frequency (AF-DF) probability based on the cardiac potential
However, the analogous art of Atienza of a localizing of high-frequency activity during atrial fibrillation method (abstract) teaches:
determine an Atrial Fibrillation-Dominant Frequency (AF-DF) probability based on the cardiac potential (pages 2-3, Methods; pages 6-7, Discussion, DFmax sites identified in AF patients form dominant frequency maximum sites based upon the measured cardiac potentials of the patient; page 5, Predictors of arrhythmia recurrence, DF sites are higher probability of remaining free of arrhythmias which forms a probability determined for the measured sites); and
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the atrial and torso mesh generation for cardiac function analysis method of Mihalef, Mansi, and Lo to incorporate the dominant frequency site analysis as taught by Atienza because ablation of the sites in a treatment show better clinical outcomes than other regions (Atienza, Abstract, Results).
Primary reference Mihalef further fails to teach:
determine a net probability of localizing AF source in the one or more atrial meshes by combining the identified one or more probable rotor regions and the AF-DF probability, wherein the one or more atrial meshes having a net probability exceeding a threshold of net probability indicate locations of source of atrial fibrillation
However, the analogous art of Ghoraani of a system and method for guidance to a location of a propagating wave source (abstract) teaches:
determine a net probability of localizing AF source in the one or more atrial meshes by combining the identified one or more probable rotor regions and the AF-DF probability, wherein the one or more atrial meshes having a net probability exceeding a threshold of net probability indicate locations of source of atrial fibrillation ([0060]-[0062]; [0076]-[0078]; [0079], “The type of AF source(s) (e.g., rotor, foci or other type) and/or the probability of an AF source at each delineated region may be provided along with the AF ablation target map. The AF ablation target map may be a 2D or 3D map which is quickly and effectively generated via the present solution.” This includes rotor regions and the AF source, based upon probability and determines the net probability within the generated map; [0101]-[0103], figure 19 shows probability of points of the cluster points for the propagating wave source; This forms a net probability of the AF source within the atrial meshes in the combined prior art invention of Mihalef, Mansi, Lo, and Atienza).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the atrial and torso mesh generation for cardiac function analysis method of Mihalef, Mansi, Lo, and Atienza to incorporate the net probability of localizing an AF source as taught by Ghoraani because the enhanced accuracy in targeting of AF sources within the regions of interest lead to higher quality interventional procedures and improved clinical outcomes for procedures such as ablation catheter procedures (Ghoraani, [0077]-[0079]).
Regarding claim 11, primary reference Mihalef teaches:
One or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors (abstract; [0044]) cause:
obtaining a plurality of heart scan images and a plurality of torso scan images ([0017], medical image data forms clinical data that includes both heart and torso data ([0020]-[0021]); [0030]-[0033], torso model constructed from torso image data for patient specific torso mesh generation);
extracting a) one or more atrial meshes from the plurality of heart scan images, and b) one or more torso meshes from the plurality of torso scan images ([0020]-[0024], atrial mesh and cardiac mesh are generated for the patient; [0030]-[0033], torso model constructed from torso image data for patient specific torso mesh generation);
Primary reference Mihalef fails to teach:
sampling one or more Body Surface Potential (BSP) signals from the one or more torso meshes and the one or more atrial meshes;
determining a cardiac potential from the one or more BSP signals
However, the analogous art of Mansi of a non-invasive EP mapping generation method (abstract) teaches:
sampling one or more Body Surface Potential (BSP) signals from the one or more torso meshes and the one or more atrial meshes ([0054]-[0055], body surface potential map is generated from the 3D surface input, which in the combined invention with Mihalef would be the combined atrial and torso meshes generated from input image data; [0056]-[0066]; [0085], body surface potential map and projected to the heart mesh);
determining a cardiac potential from the one or more BSP signals ([0048]-[0057]; [0058], virtual heart model potentials generated from the map form a cardiac potential from the one or more BSP signals; [0061]-[0063]; [0085]);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the atrial and torso mesh generation for cardiac function analysis method of Mihalef to incorporate the generation of body surface potential signals and a cardiac potential as taught by Mansi because using a body surface potential map in combination with back projecting potentials to a heart surface increases the accuracy of a generated cardiac potential map, leading to higher quality clinical diagnostics (Mansi, [0057]).
Primary reference Mihalef further fails to teach:
identifying one or more probable rotor regions in the one or more atrial meshes based on the cardiac potential;
However, the analogous art of Lo of a atrial fibrillation characterizing method (abstract) teaches:
identifying one or more probable rotor regions in the one or more atrial meshes based on the cardiac potential ([0087]-[0103], particularly [0088], predicting rotor location in critical regions based upon AF signals form probably rotor regions based upon atrial meshes of cardiac potential in the combined prior art invention of Mihalef and Mansi; [0108]-[0112]);
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the atrial and torso mesh generation for cardiac function analysis method of Mihalef and Mansi to incorporate the identifying of rotor regions as taught by Lo because accurate identification of rotor regions in persistent AF assists in facilitating an electrophysiologist to search for the critical atrial substrate in maintaining AF (Lo, [0005]).
Primary reference Mihalef further fails to teach:
determining an Atrial Fibrillation-Dominant Frequency (AF-DF) probability based on the cardiac potential
However, the analogous art of Atienza of a localizing of high-frequency activity during atrial fibrillation method (abstract) teaches:
determining an Atrial Fibrillation-Dominant Frequency (AF-DF) probability based on the cardiac potential (pages 2-3, Methods; pages 6-7, Discussion, DFmax sites identified in AF patients form dominant frequency maximum sites based upon the measured cardiac potentials of the patient; page 5, Predictors of arrhythmia recurrence, DF sites are higher probability of remaining free of arrhythmias which forms a probability determined for the measured sites); and
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the atrial and torso mesh generation for cardiac function analysis method of Mihalef, Mansi, and Lo to incorporate the dominant frequency site analysis as taught by Atienza because ablation of the sites in a treatment show better clinical outcomes than other regions (Atienza, Abstract, Results).
Primary reference Mihalef further fails to teach:
determining a net probability of localizing AF source in the one or more atrial meshes by combining the identified one or more probable rotor regions and the AF-DF probability, wherein the one or more atrial meshes having a net probability exceeding a threshold of net probability indicate locations of source of atrial fibrillation
However, the analogous art of Ghoraani of a system and method for guidance to a location of a propagating wave source (abstract) teaches:
determining a net probability of localizing AF source in the one or more atrial meshes by combining the identified one or more probable rotor regions and the AF-DF probability, wherein the one or more atrial meshes having a net probability exceeding a threshold of net probability indicate locations of source of atrial fibrillation ([0060]-[0062]; [0076]-[0078]; [0079], “The type of AF source(s) (e.g., rotor, foci or other type) and/or the probability of an AF source at each delineated region may be provided along with the AF ablation target map. The AF ablation target map may be a 2D or 3D map which is quickly and effectively generated via the present solution.” This includes rotor regions and the AF source, based upon probability and determines the net probability within the generated map; [0101]-[0103], figure 19 shows probability of points of the cluster points for the propagating wave source; This forms a net probability of the AF source within the atrial meshes in the combined prior art invention of Mihalef, Mansi, Lo, and Atienza).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the atrial and torso mesh generation for cardiac function analysis method of Mihalef, Mansi, Lo, and Atienza to incorporate the net probability of localizing an AF source as taught by Ghoraani because the enhanced accuracy in targeting of AF sources within the regions of interest lead to higher quality interventional procedures and improved clinical outcomes for procedures such as ablation catheter procedures (Ghoraani, [0077]-[0079]).
Allowable Subject Matter
Claims 2-5, 7-10, and 12-15 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims. The additional dependent claims include additional limitations, that would form a non-obvious combination of features over the prior art.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ferrer, A., (“Detailed Anatomical and Electrophysiological Models of Human Atria and Torso for the Simulation of Atrial Activation,” PLOS ONE. 2015. P. 1-29) teaches to an atrial fibrillation 3D atrial and torso model to determine the relationship between atrial activation and surface signals within a rhythm. The reference includes regional analysis of atrial structures and potential values across the surface.
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/SEAN A FRITH/Primary Examiner, Art Unit 3798
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