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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 06/17/2026 has been entered.
Response to Arguments
Applicant’s arguments in Applicant’s remarks filed 06/17/2026 with respect to the rejection of claims 1-20 under 35 U.S.C. 101 have been fully considered but they are not persuasive.
Applicant remarks on page 5 that the claims are tied to a particular machine, that is an ultrasound transducer. However, Examiner notes that the ultrasound transducer and its use as recited in the claims do not amount to a particular machine. It is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine. See MPEP 2106.05(b)(I).
Applicant also argues on pages 5-6 that the output of the claims is a meaningful measurement of physical tissue properties (that is, “a concrete diagnostic measurement of the internal pressure of a biological compartment”. However, Examiner contends that a mere output of physical tissue property does not impart a practical application upon the abstract idea of determining pressure from the pressure calculations. Such an output comprises insignificant post-extra-solution activity. See MPEP 2106.05(g).
Applicant further alleges on page 6 that the frequency-resolved wave speed data determination requires analyzing complex waveform data from Lamb wave propagation – a process which cannot practically be performed in the human mind. However, Examiner contends that Applicant’s assertion amounts to analyzing data acquired through propagated Lamb waves. The acquisition of the data from the lamb wave propagation is conventional and routine and amounts to data collection which does not confer a practical application upon the mental step of data analysis.
Applicant further remarks on pages 6-7 that the pressure determining step is not a simple mental calculation and also that claim requires a computer system for such calculation. Examiner notes, however, that Applicant’s assertion describe computer implementation of the abstract idea which the courts have deemed to be abstract. See MPEP 2106.04(a)(2)(III).
Applicant further asserts on page 7 that the claim as a whole is not abstract and that the additional elements are not well-understood, routine and conventional due to the use of radiation force in generating Lamb waves is not generic as it confers a technological improvement to the problem of non-invasive pressure measurement. However, generating lamb waves through radiation force itself does not confine the claim to a particular useful application of the recited judicial exception of determining pressure from the speed data.
Applicant further asserts on page 8 that the claims address a particular solution (non-invasive determination of pressure) to a particular problem (invasive determination of pressure). However, the technological improvements identified are in fact technological improvements identified by the prior art as having become routine and conventional aspect of Lamb wave based pressure or elasticity measurements.
Applicant’s arguments in Applicant’s remarks filed 06/17/2026 with respect to the rejection of claims 1 and 11 under 35 U.S.C. 102(a)(1) have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Newly found prior art Firouzi, et al. (US 20210000444 A1) teaches intracranial pressure calculation directly from lamb waves phase velocities as a function of frequency.
Therefore, the claims stand rejected.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Statutory Category: YES – Claim 1 recites A method for determining a kinetic value of a tissue volume and, therefore, is a process.
Step 2A, Prong 1, Judicial Exception: YES - The claim recites the following limitations:
determining frequency-resolved wave speed data for the generated Lamb waves from the ultrasonic echo data; and determining pressure of the tissue volume directly from the determined frequency-resolved wave speed data.
This limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is, nothing in the claim element precludes the step from practically being performed in the mind. For example, the claim encompasses a user simply calculating the wave speed data in her/his mind or by hand and then using that to calculate the pressure. Thus, the claim recites a mental process.
Step 2A, Prong 2, Integrated into Practical Application: No - The claim recites additional elements: “with a transducer, generating Lamb waves in a tissue wall of the tissue volume using radiation force, wherein the tissue volume is formed by the tissue wall that spatially separates a fluid material from a rigid material; forming ultrasonic echo data by detecting ultrasonic energy reflected by multiple locations along the tissue volume that is subject to the radiation force”. The Lamb wave generating and the ultrasonic echo data forming steps are recited at a high level of generality (i.e., as a general means of acquiring ultrasound data), and amounts to mere data gathering, which is a form of insignificant pre-extra-solution activity. Each of the additional limitations is no more than mere instructions to apply the judicial exception.
The combination of these additional elements is no more than mere instructions to apply the exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to the abstract idea.
Step 2B, Inventive Concept: No - As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the Lamb wave generating and the ultrasonic echo data forming steps were considered to be extra-solution activity in Step 2A, and thus it is re-evaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The Symantec, TLI, and OIP Techs. court decisions cited in MPEP 2106.05(d)(II) indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). Accordingly, a conclusion that the collecting and comparing step is well-understood, routine, conventional activity is supported under Berkheimer Option 2. For these reasons, there is no inventive concept in the claim, and thus it is ineligible.
Claim 2 recites “wherein determining the kinetic value includes determining pressure and includes optimization-based curve fitting a dispersion relation that includes the frequency-resolved wave speed data”, which merely specifies the parameter being measured and hence fails to integrate the judicial exception into a practical application.
Claim 3 recites wherein the dispersion relation includes a geometry of the tissue volume, which merely specifies the variables required for the calculation and hence fails to incorporate the judicial exception into a practical application.
Claim 4 recites wherein the geometry is at least one of a sphere or cylinder which merely specifies the region of interest and hence fails to integrate the judicial exception into a practical application.
Claim 5 recites wherein an undeformed inner volume of the at least one sphere or cylinder is determined from a wall thickness of the tissue wall of the tissue volume, which merely specifies the region of interest and hence fails to integrate the judicial exception into a practical application.
Claim 6 recites determining axial particle velocities in the tissue wall using a phase-based autocorrelation technique, which comprise further calculations from the echo data and hence fails to integrated the judicial exception into a practical application.
Claim 7 recites wherein determining frequency-resolved wave speed data includes performing a 2D Fourier transformation of the determined axial particle velocities, which merely includes further calculations in the frequency domain, without integrating the judicial exception into a practical application.
Claim 8 recites determining signal to noise ratios (SNRs) for axial particle velocity data and rejecting axial particle velocity data with SNRs below a determined threshold signal to noise ratio (SNR), which is merely filtering steps applied to the axial particle velocity data which is further data processing that fails to integrate the judicial exception into a practical application.
Claim 9 recites wherein the tissue volume is a bladder, and the tissue wall is a wall of the bladder, which merely specifies the tissue to which the data gathering steps are applied and thence fails to integrate the judicial exception into a practical application.
Claim 10 recites adjusting a dispersion relation for a curvature of the bladder wall, which forms part of optimizing the data gathering step and therefore fails to integrate the judicial exception into a practical application.
Step 1: Statutory Category: YES – Claim 11 recites A system for determining a kinetic value of a tissue volume and, therefore, is a device.
Step 2A, Prong 1, Judicial Exception: YES - The claim recites the following limitations:
i) determine frequency-resolved wave speed data from the generated Lamb waves from the ultrasonic echo data; and ii) determine a kinetic value of the tissue volume directly from the determined frequency-resolved wave speed data.
This limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “computer system”, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “computer system” language, the claim encompasses a user simply calculating the wave speed data in her/his mind or by hand and then using that to calculate the pressure. The mere nominal recitation of a generic network appliance does not take the claim limitation out of the mental processes grouping. Thus, the claim recites a mental process.
Step 2A, Prong 2, Integrated into Practical Application: No - The claim recites additional elements: a transducer configured to generate Lamb waves in a tissue wall of the tissue volume using radiation force and detect ultrasonic energy reflected by multiple locations along the tissue volume that is subject to the radiation force to form ultrasonic echo data, wherein the tissue volume is formed by the tissue wall that spatially separates a fluid material from a rigid material;. The Lamb wave generating and the ultrasonic echo data forming steps are recited at a high level of generality (i.e., as a general means of acquiring ultrasound data), and amounts to mere data gathering, which is a form of insignificant pre-extra-solution activity. The computer system that performs the Lamb wave generating and the ultrasonic echo data forming steps is also recited at a high level of generality, and merely automates the Lamb wave generating and the ultrasonic echo data forming steps. Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer component (the computer system).
The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer component (computer system). Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to the abstract idea.
Step 2B, Inventive Concept: No - As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the Lamb wave generating and the ultrasonic echo data forming steps were considered to be extra-solution activity in Step 2A, and thus it is re-evaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The background of the example does not provide any indication that the computer system is anything other than a generic, off-the-shelf computer component, and the Symantec, TLI, and OIP Techs. court decisions cited in MPEP 2106.05(d)(II) indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). Accordingly, a conclusion that the collecting and comparing step is well-understood, routine, conventional activity is supported under Berkheimer Option 2. For these reasons, there is no inventive concept in the claim, and thus it is ineligible.
Claim 12 recites “wherein determining the kinetic value includes determining pressure and includes optimization-based curve fitting a dispersion relation that includes the frequency-resolved wave speed data”, which merely specifies the parameter being measured and hence fails to integrate the judicial exception into a practical application.
Claim 13 recites wherein the dispersion relation includes a geometry of the tissue volume, which merely specifies the variables required for the calculation and hence fails to incorporate the judicial exception into a practical application.
Claim 14 recites wherein the geometry is at least one of a sphere or cylinder which merely specifies the region of interest and hence fails to integrate the judicial exception into a practical application.
Claim 15 recites wherein the computer system is further configured to determine an undeformed inner volume of the at least one sphere or cylinder from a wall thickness of the tissue wall of the tissue volume, which merely specifies the region of interest and hence fails to integrate the judicial exception into a practical application.
Claim 16 recites wherein the computer system is further configured to determine axial particle velocities in the tissue wall using a phase-based autocorrelation technique, which comprise further calculations from the echo data and hence fails to integrated the judicial exception into a practical application.
Claim 17 recites wherein the computer system is further configured to determine frequency-resolved wave speed data by performing a 2D Fourier transformation of the determined axial particle velocities, which merely includes further calculations in the frequency domain, without integrating the judicial exception into a practical application.
Claim 18 recites wherein the computer system is further configured to determine signal to noise ratios (SNRs) for axial particle velocity data and reject axial particle velocity data with SNRs below a determined threshold signal to noise ratio (SNR), which is merely filtering steps applied to the axial particle velocity data which is further data processing that fails to integrate the judicial exception into a practical application.
Claim 19 recites wherein the tissue volume is a bladder, and the tissue wall is a wall of the bladder, which merely specifies the tissue to which the data gathering steps are applied and thence fails to integrate the judicial exception into a practical application.
Claim 20 recites wherein the computer system is further configured to adjust a dispersion relation for a curvature of the bladder wall, which forms part of optimizing the data gathering step and therefore fails to integrate the judicial exception into a practical application.
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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-7, 9-17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Fatemi, et al., US 20140296709 A1 (disclosed in IDS filed 04/01/2024) in view of Firouzi, et al., US 20210000444 A1.
Regarding claim 1, Fatemi teaches a method for determining a kinetic value of a tissue volume (see fig. 5 and [0051] for the method 500), the method comprising:
with a transducer, generating Lamb waves in a tissue wall of the tissue volume using radiation force ([0051] states “UBV uses focused ultrasound to produce a radiation force 604 (push beam) to excite impulsive Lamb waves (200-600 .mu.s in length) in the medium of interest. The radiation force excitation 604 can be, for example, of 600 .mu.s toneburst”),
wherein the tissue volume is formed by the tissue wall that spatially separates a fluid material from a rigid material ([0051]-[0053] describe applying focused ultrasound radiation force to bladder wall filled with fluid);
forming ultrasonic echo data by detecting ultrasonic energy reflected by multiple locations along the tissue volume that is subject to the radiation force ([0041] states “echoes from multiple focused locations can be received to measure vibration information from several points of the tissue. The limitation of the lateral resolution of the transducer for two closely located points can be improved by assigning different transmitting codes for different locations”);
determining frequency-resolved wave speed data for the generated Lamb waves from the ultrasonic echo data ([0056] discloses step 508 which includes calculating change of Lamb wave velocity as a function of time that yields the k-space whose coordinates are frequency, f, and wave number, k using a two-dimensional fast Fourier transform (2D-FFT) of the bladder wall motion).
Fatemi does not determining pressure of the tissue volume directly from the determined frequency-resolved wave speed data.
However, within the same field of endeavor, Firouzi teaches measurement and monitoring of intracranial pressure ([0003]), by exciting and listening to guided waves (also called Lamb waves) in the skull and monitor the behavior of these Lamb waves in response to changes in the brain conditions such as intracranial pressure ([0142]-[0143]), with [0145] stating that FIGS. 5A-5B show illustrations 500 and 510 of Lamb waves phase velocities as a function of frequency and the corresponding schematic of the modal deformation of the lowest order symmetric and asymmetric modes: (a) Lamb waves phase-velocities' dispersion curves (FIG. 5A), (b) S0 and A0 mode-shapes (FIG. 5B). As it can be seen by the examples of the mode-shape in FIG. 5B, Lamb waves couple the displacement of the upper and lower surfaces (outer and inner in the case of the skull), unlike the surface waves or bulk waves, [0147] stating that a method, a system, and/or a device for a skull Lamb waves intracranial pressure monitor transmits acoustic signals to the skull using one or more transducers. The transducers receives data acquired from the skull, including information related to guided waves, distribution of acoustic modes, frequency response, and/or impulse/transient response, and [0148] stating that the intracranial pressure is determined from the acquired data. For example, determining the intracranial pressure may include assessing changes in amplitude, bandwidth, and/or frequency of the guided waves. Additionally or alternatively, the acquired data may be transmitted to an external device with a processor to determine the intracranial pressure, hence teaching determining pressure of the tissue volume directly from the determined frequency-resolved wave speed data.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Fatemi, for determining pressure of the tissue volume directly from the determined frequency-resolved wave speed data, as taught by Firouzi, as such modification would allow obtaining strong signal due to significantly reduced attenuation of the propagated waves ([0144]) and hence improve detection of pressure ([0143]).
Regarding claim 2, Fatemi in view of Firouzi teaches all the limitations of claim 1 above.
Fatemi further teaches wherein determining the kinetic value includes determining pressure and includes optimization-based curve fitting a dispersion relation that includes the frequency-resolved wave speed data ([0078] discloses fitting the Lamb wave dispersion equation for a flat plate 700 can then be fit to the dispersion data to measure bladder elasticity and viscosity, as well as the estimated thickness of the bladder from the B-mode. Also refer to fig. 9).
Regarding claim 3, Fatemi in view of Firouzi teaches all the limitations of claim 2 above.
Fatemi further teaches wherein the dispersion relation includes a geometry of the tissue volume (see fig. 7b and [0071] stating finite element analysis of Lamb wave propagation in a bladder wall, modeled by a flat viscoelastic plate 700 and a curved viscoelastic plate 702, shown in FIGS. 7A and 7B, can be designed to study the effect of curvature on Lamb wave dispersion).
Regarding claim 4, Fatemi in view of Firouzi teaches all the limitations of claim 3 above.
Fatemi further teaches wherein the geometry is at least one of a sphere or cylinder (abstract indicates that the curved viscoelastic plate 702 correlates to a curved bladder wall).
Regarding claim 5, Fatemi in view of Firouzi teaches all the limitations of claim 4 above.
Fatemi further teaches wherein an undeformed inner volume of the at least one sphere or cylinder is determined from a wall thickness of the tissue wall of the tissue volume ([0070] discloses bladder wall thickness calculations for the eventual determination of the bladder volume. See figs. 10 and 11 and [0083]).
Regarding claim 6, Fatemi in view of Firouzi teaches all the limitations of claim 1 above.
Fatemi further teaches determining axial particle velocities in the tissue wall using a phase-based autocorrelation technique ([0056] disclose steps 508 and 510 which includes calculating change of Lamb wave velocity as a function of time that yields the k-space whose coordinates are frequency, f, and wave number, k using a two-dimensional fast Fourier transform (2D-FFT) of the bladder wall motion. Also see [0093] which states that “the complex propagation of a mechanical wave in a soft tissue can be approximated with a shear-wave model (based on consideration of a wave for which the displacement of object particles is perpendicular to the direction of wave propagation, and by definition there are no boundaries in the medium that would affect such propagation) or with a wave model based on the Lamb wave (which is defined for the wave propagates along a plate, or parallel to the surface, with particles moving perpendicularly to the plate surface and, therefore, perpendicularly to the wave propagation direction).”);.
Regarding claim 7, Fatemi in view of Firouzi teaches all the limitations of claim 6 above.
Fatemi further teaches wherein determining frequency-resolved wave speed data includes performing a 2D Fourier transformation of the determined axial particle velocities ([0056] disclose steps 508 and 510 which includes calculating change of Lamb wave velocity as a function of time that yields the k-space whose coordinates are frequency, f, and wave number, k using a two-dimensional fast Fourier transform (2D-FFT) of the bladder wall motion).
Regarding claim 9, Fatemi in view of Firouzi teaches all the limitations of claim 1 above.
Fatemi further teaches wherein the tissue volume is a bladder, and the tissue wall is a wall of the bladder (abstract).
Regarding claim 10, Fatemi in view of Firouzi teaches all the limitations of claim 9 above.
Fatemi further teaches adjusting a dispersion relation for a curvature of the bladder wall (see [0078] and fig. 9 for the plotting of the dispersion distribution data).
Regarding claim 11, Fatemi a system for determining a kinetic value of a tissue volume, the system ([0033]-[0034]) comprising:
a transducer configured to generate Lamb waves in a tissue wall of the tissue volume using radiation force and detect ultrasonic energy reflected by multiple locations along the tissue volume that is subject to the radiation force to form ultrasonic echo data ([0051] states “UBV uses focused ultrasound to produce a radiation force 604 (push beam) to excite impulsive Lamb waves (200-600 .mu.s in length) in the medium of interest. The radiation force excitation 604 can be, for example, of 600 .mu.s toneburst”),
wherein the tissue volume is formed by the tissue wall that spatially separates a fluid material from a rigid material ([0051]-[0053] describe applying focused ultrasound radiation force to bladder wall filled with fluid);
a computer system ([0092]) configured to:
determine frequency-resolved wave speed data from the generated Lamb waves from the ultrasonic echo data ([0056] discloses step 508 which includes calculating change of Lamb wave velocity as a function of time that yields the k-space whose coordinates are frequency, f, and wave number, k using a two-dimensional fast Fourier transform (2D-FFT) of the bladder wall motion).
Fatemi does not teach ii) determine a kinetic value of the tissue volume directly from the determined frequency-resolved wave speed data.
However, within the same field of endeavor, Firouzi teaches measurement and monitoring of intracranial pressure ([0003]), by exciting and listening to guided waves (also called Lamb waves) in the skull and monitor the behavior of these Lamb waves in response to changes in the brain conditions such as intracranial pressure ([0142]-[0143]), with [0145] stating that FIGS. 5A-5B show illustrations 500 and 510 of Lamb waves phase velocities as a function of frequency and the corresponding schematic of the modal deformation of the lowest order symmetric and asymmetric modes: (a) Lamb waves phase-velocities' dispersion curves (FIG. 5A), (b) S0 and A0 mode-shapes (FIG. 5B). As it can be seen by the examples of the mode-shape in FIG. 5B, Lamb waves couple the displacement of the upper and lower surfaces (outer and inner in the case of the skull), unlike the surface waves or bulk waves, [0147] stating that a method, a system, and/or a device for a skull Lamb waves intracranial pressure monitor transmits acoustic signals to the skull using one or more transducers. The transducers receives data acquired from the skull, including information related to guided waves, distribution of acoustic modes, frequency response, and/or impulse/transient response, and [0148] stating that the intracranial pressure is determined from the acquired data. For example, determining the intracranial pressure may include assessing changes in amplitude, bandwidth, and/or frequency of the guided waves. Additionally or alternatively, the acquired data may be transmitted to an external device with a processor to determine the intracranial pressure, hence teaching ii) determine a kinetic value of the tissue volume directly from the determined frequency-resolved wave speed data.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Fatemi, to ii) determine a kinetic value of the tissue volume directly from the determined frequency-resolved wave speed data, as taught by Firouzi, as such modification would allow obtaining strong signal due to significantly reduced attenuation of the propagated waves ([0144]) and hence improve detection of pressure ([0143]).
Regarding claim 12, Fatemi in view of Firouzi teaches all the limitations of claim 11 above.
Fatemi further teaches wherein the kinetic value is a pressure and the computer system is further configured to determine the pressure using an optimization- based curve fitting of a dispersion relation that includes the frequency-resolved wave speed data ([0078] discloses fitting the Lamb wave dispersion equation for a flat plate 700 can then be fit to the dispersion data to measure bladder elasticity and viscosity, as well as the estimated thickness of the bladder from the B-mode. Also refer to fig. 9).
Regarding claim 13, Fatemi in view of Firouzi teaches all the limitations of claim 12 above.
Fatemi further teaches wherein the dispersion relation includes a geometry of the tissue volume (see fig. 7b and [0071] stating finite element analysis of Lamb wave propagation in a bladder wall, modeled by a flat viscoelastic plate 700 and a curved viscoelastic plate 702, shown in FIGS. 7A and 7B, can be designed to study the effect of curvature on Lamb wave dispersion).
Regarding claim 14, Fatemi in view of Firouzi teaches all the limitations of claim 13 above.
Fatemi further teaches wherein the geometry is at least one of a sphere or cylinder (abstract indicates that the curved viscoelastic plate 702 correlates to a curved bladder wall).
Regarding claim 15, Fatemi in view of Firouzi teaches all the limitations of claim 14 above.
Fatemi further teaches wherein the computer system is further configured to determine an undeformed inner volume of the at least one sphere or cylinder from a wall thickness of the tissue wall of the tissue volume ([0070] discloses bladder wall thickness calculations for the eventual determination of the bladder volume. See figs. 10 and 11 and [0083]).
Regarding claim 16, Fatemi in view of Firouzi teaches all the limitations of claim 11 above.
Fatemi further teaches wherein the computer system is further configured to determine axial particle velocities in the tissue wall using a phase-based autocorrelation technique ([0056] disclose steps 508 and 510 which includes calculating change of Lamb wave velocity as a function of time that yields the k-space whose coordinates are frequency, f, and wave number, k using a two-dimensional fast Fourier transform (2D-FFT) of the bladder wall motion. Also see [0093] which states that “the complex propagation of a mechanical wave in a soft tissue can be approximated with a shear-wave model (based on consideration of a wave for which the displacement of object particles is perpendicular to the direction of wave propagation, and by definition there are no boundaries in the medium that would affect such propagation) or with a wave model based on the Lamb wave (which is defined for the wave propagates along a plate, or parallel to the surface, with particles moving perpendicularly to the plate surface and, therefore, perpendicularly to the wave propagation direction).”).
Regarding claim 17, Fatemi in view of Firouzi teaches all the limitations of claim 16 above.
Fatemi further wherein the computer system is further configured to determine frequency-resolved wave speed data by performing a 2D Fourier transformation of the determined axial particle velocities ([0056] disclose steps 508 and 510 which includes calculating change of Lamb wave velocity as a function of time that yields the k-space whose coordinates are frequency, f, and wave number, k using a two-dimensional fast Fourier transform (2D-FFT) of the bladder wall motion).
Regarding claim 19, Fatemi in view of Firouzi teaches all the limitations of claim 11 above.
Fatemi further teaches wherein the tissue volume is a bladder, and the tissue wall is a wall of the bladder (abstract).
Regarding claim 20, Fatemi in view of Firouzi teaches all the limitations of claim 19 above.
Fatemi further teaches wherein the computer system is further configured to adjust a dispersion relation for a curvature of the bladder wall (see [0078] and fig. 9 for the plotting of the dispersion distribution data).
Claims 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Fatemi in view of Firouzi, as applied to claims 6 and 16, respectively above, and further in view of Urban, et al., US-20200163649-A1.
Regarding claim 8, Fatemi in view of Firouzi teaches all the limitations of claim 6.
Fatemi in view of Firouzi fails to teach determining signal to noise ratios (SNRs) for axial particle velocity data and rejecting axial particle velocity data with SNRs below a determined threshold signal to noise ratio (SNR).
However, within the same field of endeavor, Urban teaches methods for estimating the phase velocity of a shear wave from ultrasound data including determining signal to noise ratios (SNRs) for axial particle velocity data and rejecting axial particle velocity data with SNRs below a determined threshold signal to noise ratio (SNR) ([0021] describes, with reference to figs. 10A-10C, determination of spatiotemporal particle velocity with a specific SNR value with a polynomial fit).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Fatemi, as modified by Firouzi, for determining signal to noise ratios (SNRs) for axial particle velocity data and rejecting axial particle velocity data with SNRs below a determined threshold signal to noise ratio (SNR), as taught by Urban, for accurate and robust characterization of viscoelastic media using algorithms to reliably extract the phase velocity dispersion and reduce experimental noise in phase gradient and 2D-FT methods ([0009]).
Regarding claim 18, Fatemi in view of Firouzi teaches all the limitations of claim 16.
Fatemi in view of Firouzi fails to teach wherein the computer system is further configured to determine signal to noise ratios (SNRs) for axial particle velocity data and reject axial particle velocity data with SNRs below a determined threshold signal to noise ratio (SNR).
However, within the same field of endeavor, Urban teaches methods for estimating the phase velocity of a shear wave from ultrasound data wherein the computer system is further configured to determine signal to noise ratios (SNRs) for axial particle velocity data and reject axial particle velocity data with SNRs below a determined threshold signal to noise ratio (SNR) ([0021] describes, with reference to figs. 10A-10C, determination of spatiotemporal particle velocity with a specific SNR value with a polynomial fit).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to configure Fatemi, as modified by Firouzi, wherein the computer system is further configured to determine signal to noise ratios (SNRs) for axial particle velocity data and reject axial particle velocity data with SNRs below a determined threshold signal to noise ratio (SNR), as taught by Urban, for accurate and robust characterization of viscoelastic media using algorithms to reliably extract the phase velocity dispersion and reduce experimental noise in phase gradient and 2D-FT methods ([0009]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Farouk A Bruce whose telephone number is (408)918-7603. The examiner can normally be reached Mon-Fri 8-5pm PST.
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/FAROUK A BRUCE/ Examiner, Art Unit 3797
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