The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Response to Arguments
Applicant's arguments filed June 15, 2026 have been fully considered but they are not persuasive.
First, it is noted that on page 1 of the remarks, the applicant states “In the approach of claim 1, the FMM-LU approach computes a strength of the electrical energy at the position from the electric field at the position, based on the scanned image of the treatment region.” Then on page 2, the applicant states that “The Office Action appears to acknowledge this the distinction of the FMM-LU approach at page 4, however looks to Soin'701 for this deficiency in the rejection.” The examiner notes that claim 1 does not require the FMM-LU approach, as this was amended into the other independent claims, but not into claim 1. Therefore, this argument is moot.
On page 2 of the remarks, the applicant argues that Soin fails to teach suggest computing a strength of the electrical. The examiner respectfully disagrees. One of ordinary skill in the art, upon reading the disclosure of Soin would understand that Soin does, or at least that it would be obvious to, calculate the strength of the electric field in the target tissue 12.
In paragraph 90, Soin discussing that “The shapes, sizes, and arrangements of the electrodes 30 and the spacing between electrodes 30 can be selected in order to generate one or more electric fields in and around the target tissue 12 having desired properties” and that “In addition, and as described further below, a specific electrode 30 and/or one or more pairs or combinations of electrodes 30 can be selected to optimize and maximize the strength … of the electric field in the target tissue 12 to provide optimal therapeutic results”. Then, in paragraph 138 Soin continues this discussion of and states “the controller 50 can be configured to control the electrode interface 54 to select a first electrode 30 or combination of electrodes 30 from the plurality of electrodes 30 and plurality of possible combinations of electrodes 30 as described above.” Soin then continues to state that “The controller 50 can further be configured to monitor the sensor data, make a determination regarding the characteristics of the electric field produced in the target tissue 12…The controller 50 can be configured to continue to select additional electrodes 30 or combinations of electrodes 30 to deliver the electrical noise stimulation signals to the target tissue until the most optimized electric field… is produced in the target tissue 12”. These paragraphs would imply to one of ordinary skill in the art that electric field strength, which is to be optimized according to paragraph 90, would be determined as one of the “characteristics of the electric field produced in the target tissue 12”, as stated in paragraph 138. Without determining the strength of the electric field, one would not be capable of optimizing it.
Near the bottom of page 2, the applicant argues that “One of skill in the art would not look to Soin '701 to modify McIntyre '749 because there is no mention of an imaged target region, nor of any kind of medical imaging in conjunction with electrode introduction” and that the result of combining Soin with the primary reference would be inoperable because Soin relies only on closed-loop electrical probe feedback, or ‘feedback optimized’ operation, as disclosed at [0129].” The examiner notes that MPEP 2145(III) states that "The test for obviousness is not whether the features of a secondary reference may be bodily incorporated into the structure of the primary reference.... Rather, the test is what the combined teachings of those references would have suggested to those of ordinary skill in the art." In re Keller, 642 F.2d 413, 425, 208 USPQ 871, 881 (CCPA 1981), and "Combining the teachings of references does not involve an ability to combine their specific structures." In re Nievelt, 482 F.2d 965, 179 USPQ 224, 226 (CCPA 1973). Here, the teachings relied upon within the Soin reference is a processor that selects various combinations of electrodes and determines electric field characteristics in order to optimize the electric field strength in the target tissue. This is directly applicable to the teachings of McIntyre, who also provides teachings of electric field optimization. The fact that Soin does not mention imaging of the target region, nor of any kind of medical imaging does not take away from the fact that Soin teaches the determination of electric field characteristics, and therefore implies and/or would suggest to one of ordinary skill in the art to determine the strength as such a characteristic, merely means this reference is applicable under 35 USC 102. Since the rejection is under 35 USC 103, this is not persuasive.
For at least this reason, the applicant’s arguments against the Soin reference is not persuasive.
Claim Rejections - 35 USC § 112
Second Paragraph
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 22-23 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.
Claim 22 is rejected because it recites “computing the strength of the electrical energy occurs in less than a minute”. The constraint of “in less than a minute” is a result-effective variable. Specifically, whether or not this can effectively be computed in “less than a minute” relies on numerous constraints that are not mentioned in the claim, nor in the specification. The specification merely states that “The BEM-based FMM-LU approach herein, on the other hand, takes less than a minute to solve the same problem” (see paragraph 20 of the PGPUB 2024/0278016). This is merely a conclusory statement, and is not supported by any factual evidence that this is true. Whether or not this is true would depend on numerous factors, such as what processor is being used, how much RAM the system contains, the size of the data set being processed, etc. As such, the claims is indefinite.
Claim 23 is rejected because it recites “computing the strength of the electrical energy includes computing a derivative of an electric field at the position.” This is indefinite because “an electric field” is not a characteristic/parameter. The specification states in paragraph 24 of the PGPUV 2024/0278016 “In contrast to conventional approaches, this may involve computing a strength of the electrical energy at the position based on a derivative of the value representing the electric field at the position.” Therefore, this claim is indefinite. It is also noted that claim 14, which also depends from claim 1, is nearly identical to the subject matter of new claim 23, except it actually states “of a value of the electric field”.
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 and 3-6 are rejected under 35 U.S.C. 103 as being unpatentable over McIntyre et al. (US Patent Pub. No. 2006/0017749) in view of Soin (US Patent Pub. No. 2021/0346701).
Regarding claim 1, McIntyre discloses “brain stimulation models, systems, devices, and methods, such as for deep brain stimulation (DBS)” (see Abstract). The system and methods of McIntyre create a patient-specific neural stimulation modeling system (PSNSMS) (see paragraph 76, where it states that “The PSNSMS allows interactive manipulation of patient-specific electrical models of the brain for analysis of brain stimulation methods. This provides a virtual laboratory for surgeons, technicians, or engineers to optimize or otherwise adjust neural stimulation treatment, such as by varying electrode position, stimulation protocol, or electrode design”). “[T]he PSNSMS includes the following components: … (3) integration of functional or anatomical imaging data into a visualization platform that can be combined with the electric field modeling results” (see paragraph 83). Therefore, this requires “receiving a scan image of a treatment region” prior to integrating the functional or anatomical imaging data into the PSNSMS (see also paragraph 79-81 where diffusion tensor imaging and MR imaging data is discussed). Paragraph 85 provides details of an example method in which “The example of FIG. 6 also includes stored volumetric imaging data 610 and volumetric anatomic atlas data 612. Using a computer FEM solver to solve the electric field model 602, together with the neuron or axon model 608 … a volume of influence 614 is calculated. …a correlation between the two is computed at 618. In a further example, several model-computed volumes of influence (e.g., using different electrode locations or parameter settings) are computed and correlated to the target volume of influence, such as to optimize or otherwise select a desirable electrode location or stimulation parameter settings.” This reads on “determining a purported location of a stimulation probe inserted within the scan image; determining a position of a target region within the scan image relative to the purported location”. Additionally, paragraph 101 discusses that “One purpose of the PSNSMS is to determine optimal or desirable preoperative electrode locations… This typically involves determining a target volume of tissue that should be activated by the stimulation… For example, in the case of STN DBS for Parkinson's disease, current anatomical and physiological knowledge indicate that the target volume of tissue is the dorsal half of the STN. Therefore, in this example, for each patient-specific 3D brain atlas we determine a target VOA defined by the dorsal half of the STN. We then determine test VOAs generated by a range of electrode positions within the STN and/or a range of stimulation parameter settings for each of those electrode locations. These test VOAs are then compared to the target VOA. The electrode position and/or stimulation parameter setting that generates a test VOA that most closely matches the target VOA is provided as the model-selected electrode position and/or stimulation parameter setting.” This also reads on “determining a position of a target region within the scan image relative to the purported location” as it is explicitly stated that this is done and that the subthalamic nucleus is the target region. Additionally, this also teaches “determining a purported location of a stimulation probe inserted within the scan image” in that the entire purpose of this method in paragraph 101 is to determine an optimal electrode location by iterating through multiple positions within the model (i.e., simulation). Also of note, this teaches “concluding an efficacy resulting from activation of an electrode delivering the electrical energy resulting from the stimulation probe at the purposed location” since it teaches “These test VOAs are then compared to the target VOA. The electrode position … that generates a test VOA that most closely matches the target VOA is provided as the model-selected electrode position.”
It is noted that McIntyre states in paragraph 102 that “In one variant of this selection process, engineering optimization is used to assist the selection process. Examples of possible constraints on the selection process include one or more of … limiting the stimulus amplitude to being greater than -10 V and less then 10V.” However, there is not an explicit teaching of “computing a strength of the electrical energy at the position based on the electric field at the position”.
Soin teaches a neuromodulation system and method with feedback optimized electrical field generation for stimulating target tissue of a patient to treat neurological and non-neurological conditions (see Abstract). Soin teaches that “The shapes, sizes, and arrangements of the electrodes 30 and the spacing between electrodes 30 can be selected in order to generate one or more electric fields in and around the target tissue 12 having desired properties, depending at least in part on the nature and location of the target tissue, the condition being treated, and treatment being provided” (see paragraph 90; also see paragraph 138). Paragraph 90 also states that “a specific electrode 30 and/or one or more pairs or other combinations of electrodes 30 can be selected to optimize and maximize the strength or intensity of the electric field in the target tissue 12 to provide optimal therapeutic results and/or to control the strength of the electric field in the target tissue 12 to prevent discomfort to the patient 14 and damage to the target tissue 12. For example, specific electrodes 30 or pairs or other combinations of electrodes 30 having different distances from and/or different orientations, e.g., angles, with respect to the target tissue 12 can be selected”.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to consider not only whether or not the test VOAs match the target VOAs (see paragraph 103 of McIntyre), but also to consider if the strength or intensity of the electric field in the target tissue is at a desired strength, as taught by Soin, in order “to provide optimal therapeutic results” and/or “to prevent discomfort to the patient 14 and damage to the target tissue 12” (see paragraph 90 of Soin). Doing so would further improve the simulations of McIntyre to provide further optimized electrode locations and stimulation parameters pre-operatively.
Regarding claim 3, McIntyre states that “Diffusion tensor imaging (DTI) characterizes the diffusional behavior of water in tissue on a voxel-by-voxel basis” (see paragraph 28). It is noted that voxels are simply three-dimensional pixels.
Regarding claim 4, McIntyre states in paragraph 101 that, with emphasis added, “One purpose of the PSNSMS is to determine optimal or desirable preoperative electrode locations… This typically involves determining a target volume of tissue that should be activated by the stimulation… For example, in the case of STN DBS for Parkinson's disease, current anatomical and physiological knowledge indicate that the target volume of tissue is the dorsal half of the STN. Therefore, in this example, for each patient-specific 3D brain atlas we determine a target VOA defined by the dorsal half of the STN. We then determine test VOAs generated by a range of electrode positions within the STN and/or a range of stimulation parameter settings for each of those electrode locations. These test VOAs are then compared to the target VOA. The electrode position and/or stimulation parameter setting that generates a test VOA that most closely matches the target VOA is provided as the model-selected electrode position and/or stimulation parameter setting.”
Regarding claim 5, it is re-iterated that the above rejection of claim 4 relies on the teaching of McIntyre that states “We then determine test VOAs generated by a range of electrode positions within the STN”. This teaches “adjusting the purported location of the stimulation probe to an alternate purposed location”. Additionally, this same quote in the rejection of claim 4 states “These test VOAs are then compared to the target VOA. The electrode position … that generates a test VOA that most closely matches the target VOA is provided as the model-selected electrode position”, which reads on re-evaluating the efficacy based on the stimulation probe being disposed in the alternate purported location.
Regarding claim 6, it is noted that paragraph 95 of McIntyre teaches that a 5.7 µm diameter double cable myelinated axon model was incorporated into their STN DBS FEM “to quantify the neural response to stimulation. By positioning the axon in different locations relative to the electrode and modulating the stimulation parameters one can determine the threshold stimulus necessary to activate the neuron.” Therefore, this teaches that the electrode is simulated to stimulate an axon within the subthalamic nucleus.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over McIntyre in view of Soin as applied to claim 1 above, and further in view of Goetz et al. (US Patent Pub. No. 2011/0093030).
McIntyre in combination with Soin is described above with regard to claim 1. Although claim Figure 3 of Soin illustrates multiple electrodes per DBS probe, neither reference clearly teaches determination of strengths per electrode.
Goetz teaches managing electrical stimulation therapy based on variable electrode combinations (see Title). Within the system and methods of Goetz, the system is used in “determining the variable electrical stimulation contributions of each electrode to the stimulation or shielding zone” (see paragraph 35). “A stimulation zone is an area of stimulation defined by a collection of electrodes, their contributions, and an intensity” (see paragraph 96). “A zone shape, or indication of zone extent, is a graphical indication used to show which electrodes are recruited by a stimulation zone and their relative contributions to that zone” (see paragraph 98). Paragraph 122 teaches that field strength may also be displayed.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to calculation the contribution of each electrode, as taught by Goetz, and to use this in determining field strength within the activation zone (i.e,. the volume of activation) in McIntyre as combined with Soin in order to no only optimize lead placement but to optimize the volume of activation of the multi-electrode lead, thereby improving beyond the methods of MyIntyre.
Claims 12 and 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over McIntyre in view of Soin as applied to claim 1 above, and further in view of Makarov et al. (US Patent Pub. No. 2022/0088404).
McIntyre in combination with Soin is described above with regard to claim 1. While Soin teaches to optimize and maximize the strength or intensity of the electric field in the target tissue 12 to provide optimal therapeutic results, there is no explicit teaching that the strength is determined by surface charge density, as claimed.
Makarov teaches methods and system for modeling EM brain stimulation and brain recordings with boundary element approach with fast multipole acceleration (see Title). Specifically regarding claim 12, Makarov teaches that “This problem is equivalent to finding the electric field at target points rm generated by the point charges located at source points rn. The accuracy of the FMM (the number of levels) is conventionally estimated for arbitrary volumetric charge distributions. However, for surface-based charge distributions, a much better relative accuracy is observed. For example, with the intrinsic method accuracy set as ε=0.1, the mean error for the pial cortical surface (GM shell) may be as low as 0.1% with respect to the electric field amplitude and 0.08 deg with respect to the field angle deviation as compared to the most accurate solution (i.e., the solution where FMM precision is set to maximum)” (see paragraph 59, after equation 6; also see paragraphs 11-12).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to utilize surface-based charge distributions in finding the electric field at target points, as taught by Makarov, with the system and methods of the combination of McIntyre with Soin in order to optimize the field strength at the location by calculating it. In other words, although Soin does not expressly teach calculating the strength via surface-based charge distributions, the reference does generally teach optimizing field strength at a target location, and determination of electric field strength is well known in the art with the use of fast multipole methods; accordingly, thus the use this relationship to perform the method taught by McIntyre as combined with Soin would amount to choosing from a finite number of electric field strength computational methods available in the art at the time of the invention, which has previously been held as unpatentable (KSR v. Teleflex).
Regarding claim 21, it is re-iterated that the title of Makarov is methods and system for modeling EM brain stimulation and brain recordings with boundary element approach with fast multipole acceleration (emphasis added).
Regarding claim 22, it is noted that in paragraph 6, Makarov discusses that “The fast multipole method (FMM) … its faster speed and better accuracy for piecewise homogeneous tissues.” In this regard, and in view of the indefinite rejection above under 35 USC 112(b), it would have been obvious to one of ordinary skill in the art at the time of the invention to compute the strength fast/quickly, such as in less than one minute, assuming processing power, size of the data, etc. allow for this time frame.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over McIntyre in view of Soin as applied to claim 1 above, and further in view of Arnholt et al. (US Patent Pub. No. 2023/0414161, effectively filed June 27, 2022, therefore being prior art under 102(a)(2)).
McIntyre in combination with Soin is described above with regard to claim 1. While Soin teaches to optimize and maximize the strength or intensity of the electric field in the target tissue 12 to provide optimal therapeutic results, there is no explicit teaching that the strength is determined by faceted volumetric representations, as claimed.
Arnholt teaches an interactive medical visualization system and methods for visualizing stimulation lead placement (see Title). Specifically with regard to claim 13, Arnholt teaches that “The medical visualization system herein can be configured to provide optimal placement of one or more cancer therapy stimulation leads and can provide a graphic representation of an electric field zone overlaid at the site of lead placement on the three-dimensional model. FIG. 2 includes a graphic representation of electric field strength zone 208 as associated with cancer therapy stimulation leads 204 and 206. The graphic representation of the electric field strength zone 208 can include one or more gradients of electric field strengths as represented by electric field strengths 210, 212, 214, 216, 218, and 220 that decrease in intensity in a radial direction away from the center of the cancer therapy stimulation lead 204” (see paragraph 155).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to represent the electric field strength graphically and volumetrically in a lead placement tool, as taught by Arnholt, and to include this feature into the system and methods of McIntyre with Soin because it can “provide a user with interactive capabilities to identify how different possible placements of the virtual stimulation leads can focus a therapy on a desired target area while sparing tissue damage to healthy tissues” and can improve “safety of the subject” (see paragraph 141 for both quotes).
Claims 14 and 23 are rejected under 35 U.S.C. 103 as being unpatentable over McIntyre in view of Soin as applied to claim 1 above, and further in view of Tol et al. (EP 2656876).
McIntyre in combination with Soin is described above with regard to claim 1. While Soin teaches to optimize and maximize the strength or intensity of the electric field in the target tissue 12 to provide optimal therapeutic results, there is no explicit teaching that the strength be determined by a derivative of a value of the electric field.
Tol teaches systems and methods related to DBS (see Figure 1). “Figure 6 shows the field distribution near a standard distal end of lead with electrodes… The equipotential lines cannot enter such a material and thus the region 410 and are bent around its shape. Therefore, the density of the equipotential lines at the left-hand side of the bar 400 around region 410 is relatively high. This results in high electric field strength there because the electric field strength is proportional to the density of the equipotential lines or in other words the electric field equals the space derivative of the electric potential field” (emphasis added).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to utilize the relationship between the strength of the electric field and the space derivative of the electric potential field, as taught by Tol, with the system and methods of the combination of McIntyre with Soin in order to optimize the field strength at the location by calculating it. In other words, although Soin does not expressly teach calculating the strength via a derivative, the reference does generally teach optimizing field strength at a target location, and determination of electric field strength is well known in the art as it being the space derivative of the electric potential field is a known natural phenomenon; accordingly, thus the use this relationship to perform the method taught by McIntyre as combined with Soin would amount to choosing from a finite number of electric field strength computational methods available in the art at the time of the invention, which has previously been held as unpatentable (KSR v. Teleflex).
Allowable Subject Matter
Claims 15-18 and 20 are allowed.
Claims 2 and 8-11 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The following prior art is herein made of record is considered pertinent to applicant's disclosure, but not relied upon in the rejections above:
Young et al. (EP 2656875) states “This results in high electric field strength there because the electric field strength is proportional to the density of the equipotential lines or in other words the electric field equals the space derivative of the electric potential field.”
Gutbrod et al. (US Patent Pub. No. 2021/0369341)
In paragraph 83, Gutbrod teaches the following (emphasis added):
To aid in planning and to improve planning procedures for ablation by electroporation, the console 130 is configured to:
determine the location of the electrodes 314 and 316 in the patient in relation to the cardiac tissue 302, after the catheter 300 has been inserted into the patient; model electric fields that can be generated by different combinations of the electrodes 314 and 316 on the catheter 300;
determine characteristics of the cardiac tissue 302 near or surrounding the catheter 300 in the patient;
determine the surface area and depth of the cardiac tissue 302 that will be or would be affected by an electric field, including determining the strength of the electric field in different portions of the cardiac tissue 302;
generate a graphical representation of the electric field of interest; and
overlay the graphical representation of the electric field on an anatomical map of the heart. In embodiments, the displayed electric field can be dynamically updated based on which electrodes and vectors are selected to be used for ablation.
Also, in embodiments, the displayed electric field can be dynamically updated based on changes in selectable parameters, such as voltage amplitude.
Wasserman et al. (US Patent Pub. No. 2024/0081939)
In paragraph 122, Wasserman teaches the following (emphasis added):
In one embodiment, measuring one or more sensor 102a-n to determine at least one field property (step 312) includes measuring one or more of an alternating electric field strength, or intensity, a voltage, an amperage, or other electrical property, a magnetism or magnetic property, or a temperature, or some combination thereof. In one embodiment, the applied alternating electric field is the TTField and the target region is the target treatment area.
THIS ACTION IS MADE FINAL. 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES KISH whose telephone number is (571)272-5554. The examiner can normally be reached M-F 10:00a - 6p EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Unsu Jung can be reached at (571) 272-8506. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JAMES KISH/Primary Examiner, Art Unit 3792
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