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 .
Notice to Applications
This communication is in response to the Application filed on August 28, 2023.
Claims 1-34 are pending.
Information Disclosure Statement
The information disclosure statement(s) (IDS(s)) submitted on October 31, 2023 and January 15, 2025 are in compliance with the provisions of 27 CFR 1.97. Accordingly, the information disclosure statements are being considered and attached by the examiner.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-9, 11, 14-26, 28, and 31-34 are rejected under 35 U.S.C. 103 as being unpatentable of Min et al., US 20210209757 A1, (hereinafter “Min”) in view of Ilegbusi et al., US 20080228086 A1, (hereinafter “Ilegbusi”) in further view of Wang et al., US 20190378312 A1 (hereinafter “Wang”).
Regarding claim 1, Min teaches a computer-implemented method of generating an immersive patient-specific report on cardiovascular disease state based on one or more plaque parameters derived from non-invasive medical image analysis, the method comprising:
accessing, by a computer system, a medical image of a subject, wherein the medical image of the subject is obtained non-invasively ([0220] “As such, in some embodiments, the system can provide an automated disease tracking tool using non-invasive raw medical images as an input, which does not rely on subjective assessment.”);
analyzing, by the computer system, the medical image of the subject to identify one or more arteries, wherein the one or more arteries comprise one or more regions of plaque ([0207] “In some embodiments, at block 354, the system is configured to identify one or more arteries, plaque, and/or fat in the medical image, for example using AI, ML, and/or other algorithms.”);
determining, by the computer system, one or more vascular parameters associated with the subject by analyzing the one or more identified arteries, wherein the one or more vascular parameters comprise one or more of vessel volume, diameter, area, cross-sectional area, surface area, length, location, or remodeling ([0129] “In particular, in some embodiments, the system can be configured to determine one or more vascular morphology parameters, such as for example arterial remodeling, curvature, volume, width, diameter, length, and/or the like.” wherein one or more vascular parameters are one or more vascular morphology parameters);
identifying, by the computer system, the one or more regions of plaque in the one or more arteries ([0207] “In some embodiments, at block 354, the system is configured to identify one or more arteries, plaque, and/or fat in the medical image, for example using AI, ML, and/or other algorithms.”);
determining, by the computer system, one or more plaque parameters associated with the one or more regions of plaque, wherein the one or more plaque parameters comprise one or more of plaque density, composition, calcification, radiodensity, location, volume, surface area, geometry, heterogeneity, diffusivity, or ratio between volume and surface area ([0210] “In some embodiments, the system can be configured to determine one or more vascular morphology and/or quantified plaque parameters at block 208. For example, in some embodiments, the system can be configured to determine a geometry and/or volume of a region of plaque and/or a vessel at block 201, a ratio or function of volume to surface area of a region of plaque at block 203, a heterogeneity or homogeneity index of a region of plaque at block 205, radiodensity of a region of plaque and/or a composition thereof by ranges of radiodensity values at block 207, a ratio of radiodensity to volume of a region of plaque at block 209, and/or a diffusivity of a region of plaque at block 211.”);
generating, by the computer system, an assessment of cardiovascular disease state of the one or more regions of plaque based at least in part on the determined one or more plaque parameters and the one or more vascular parameters ([0215] “In some embodiments, at block 366, the system can be configured to generate a risk assessment of cardiovascular disease or event for the subject. In some embodiments, the generated risk assessment can comprise a risk score indicating a risk of coronary disease for the subject. In some embodiments, the system can generate a risk assessment based on an analysis of one or more vascular morphology parameters, one or more quantified plaque parameters, one or more quantified fat parameters, calculated stenosis, risk of ischemia, CAD-RADS score, and/or the like.”);
generating, by the computer system, a of the one or more regions of plaque when the generated assessment of cardiovascular disease state of the one or more regions of plaque is above a pre-determined threshold level ([0139] “In some embodiments, the system can be configured to identify regions of plaque based on the radiodensity values typically associated with plaque, for example by setting a predetermined threshold or range of radiodensity values that are typically associated with plaque with or without normalizing using a normalization device.”);
([0210] “In some embodiments, the system can be configured to determine one or more vascular morphology and/or quantified plaque parameters at block 208. For example, in some embodiments, the system can be configured to determine a geometry and/or volume of a region of plaque and/or a vessel at block 201, a ratio or function of volume to surface area of a region of plaque at block 203, a heterogeneity or homogeneity index of a region of plaque at block 205, radiodensity of a region of plaque and/or a composition thereof by ranges of radiodensity values at block 207, a ratio of radiodensity to volume of a region of plaque at block 209, and/or a diffusivity of a region of plaque at block 211.”);
generating, by the computer system, an immersive three-dimensional graphical representation of the one or more arteries ([0342] “FIG. 6F illustrates additional information of the three-dimensional (3D) rendering of the coronary artery tree 602 on the first panel 601 that allows a user to view the vessels and modify the labels of a vessel.” wherein an immersive three-dimensional graphical representation is the three-dimensional rendering), wherein the immersive three-dimensional graphical representation of the one or more arteries comprises when the generated assessment of cardiovascular disease state of the one or more regions of plaque is above a pre-determined threshold level ([0139] “In some embodiments, the system can be configured to identify regions of plaque based on the radiodensity values typically associated with plaque, for example by setting a predetermined threshold or range of radiodensity values that are typically associated with plaque with or without normalizing using a normalization device.”); and
causing, by the computer system, transmission of the immersive three- dimensional graphical representation of the one or more arteries to a user computing device, wherein the immersive three-dimensional graphical representation of the one or more arteries is configured to allow a user to view the state of cardiovascular disease from a point of view positioned inside the one or more arteries ([0342] “FIG. 6F illustrates additional information of the three-dimensional (3D) rendering of the coronary artery tree 602 on the first panel 601 that allows a user to view the vessels and modify the labels of a vessel.” wherein an immersive three-dimensional graphical representation is the three-dimensional rendering) ([0298] “In some embodiments, the linear view of the artery vessels shows a cross-sectional view along a longitudinal axis (or the length of the vessel or a long axis) of the artery vessel. In some embodiments, the system can be configured to allow the user to rotate in a 360° fashion about the longitudinal axis of the substantially linear artery vessels in order for the user to review the vessel walls from various views and angles.”),
wherein the computer system comprises a computer processor and an electronic storage medium ([0012] “wherein the computer system comprises a computer processor and an electronic storage medium”).
Min does not specifically disclose a three-dimensional graphical representation of one or more plaque rupture scenarios of the one or more regions of plaque.
However, Ilegbusi teaches a three-dimensional graphical representation of one or more plaque rupture scenarios of the one or more regions of plaque ([0033] “As is also described below, the captured image data can be used to construct a three-dimensional reconstruction or model of the artery.”) ([0041] “Beginning with block 200, images of a vessel under evaluation are captured and stored. As described above, the vessel can, for example, comprise an artery which may have plaques that are vulnerable to rupture.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include a three-dimensional graphical representation of a plaque rupture scenario of Illegbusi in the cardiovascular disease assessment of Min to better characterize the rupture as well as high-risk plaques which aids in better assessment of clinical risks.
Min in view of Ilegbusi does not specifically disclose a three-dimensional multiplanar reformation of the one or more arteries.
However, Wang teaches a three-dimensional multiplanar reformation of the one or more arteries ([0199] “In some embodiments, the volume data may be generated by performing a three-dimensional reconstruction technique based on the images of the region of interest, and accordingly, the image(s) in the coronal plane and the image(s) in the sagittal plane may be obtained based on the volume data. The three-dimensional reconstruction technique may include multiplanar reconstruction (MPR).”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include a three-dimensional multiplanar reformation of an artery of Wang in the cardiovascular disease assessment of Min in view of Ilegbusi to obtain a true, anatomy-respecting view of the vessel which aids in accurately locating and characterizing plaques.
Regarding claim 2, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 1, wherein the user computing device comprises a virtual reality (VR) device (Min - [0276] “In some embodiments, the system is configured to insert into the patient-specific report dynamically generated illustrations or images of patient artery vessels in order to highlight specific vessels and/or portions of vessels that contain or are likely to contain vascular disease that require review or further analysis. In some embodiments, the dynamically generated patient-specific report is configured to show a user the vessel walls using AR and/or VR.”).
The motivation for combining Min, Ilegbusi, and Wang is the same motivation as used for claim 1.
Regarding claim 3, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 1, wherein the pre-determined threshold level is based at least in part on density of the one or more regions of plaque (Min - [0139] “In some embodiments, the system can be configured to identify regions of plaque based on the radiodensity values typically associated with plaque, for example by setting a predetermined threshold or range of radiodensity values that are typically associated with plaque with or without normalizing using a normalization device.”).
The motivation for combining Min, Ilegbusi, and Wang is the same motivation as used for claim 1.
Regarding claim 4, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 1, wherein the density of the one or more regions of plaque comprises absolute density (Min - [0181] “Further, in some embodiments, parameters associated with the aortic valve can include thickness, volume, mass, calcifications, three-dimensional map of calcifications and density, eccentricity of calcification, classification by individual leaflet, and/or the like.” wherein absolute density is density associated with the aortic valve).
The motivation for combining Min, Ilegbusi, and Wang is the same motivation as used for claim 1.
Regarding claim 5, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 1, wherein the density of the one or more regions of plaque comprises radiodensity (Min - [0120] “Based on the identified features, in some embodiments, the system can be configured to generate one or more quantified measurements from a raw medical image, such as for example radiodensity of one or more regions of plaque,”).
The motivation for combining Min, Ilegbusi, and Wang is the same motivation as used for claim 1.
Regarding claim 6, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 1, wherein the immersive three- dimensional graphical representation of the one or more arteries is configured to allow a user to move the point of view within the one or more arteries in six degrees of freedom (Min - [0298] “In some embodiments, the linear view of the artery vessels shows a cross-sectional view along a longitudinal axis (or the length of the vessel or a long axis) of the artery vessel. In some embodiments, the system can be configured to allow the user to rotate in a 360° fashion about the longitudinal axis of the substantially linear artery vessels in order for the user to review the vessel walls from various views and angles.”) (Ilegbusi - [0059] “The microtracker 422 provides real-time position and orientation information relating to the catheter 300 such that BCA is not required to determine the position and orientation of the images that are captured by the catheter. Such operation enables tracking of the catheter (e.g., catheter tip) in three-dimensional space in terms of X, Y, Z, yaw, pitch, and roll, thereby providing six degrees-of-freedom (6DOF).”).
The motivation for combining Min, Ilegbusi, and Wang is the same motivation as used for claim 1.
Regarding claim 7, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 1, wherein the immersive three- dimensional graphical representation of the one or more arteries is configured to allow a user to rotate the point of view within the one or more arteries in three degrees of freedom (Min - [0298 - 0299] “In some embodiments, the linear view of the artery vessels shows a cross-sectional view along a longitudinal axis (or the length of the vessel or a long axis) of the artery vessel. In some embodiments, the system can be configured to allow the user to rotate in a 360° fashion about the longitudinal axis of the substantially linear artery vessels in order for the user to review the vessel walls from various views and angles…In some embodiments, the system can be configured to show a cross-sectional view of an artery vessel along a latitudinal axis (or the width of the vessel or short axis). In contrast to the cross-sectional view along a longitudinal axis, in some embodiments, the system can allow a user to more clearly see the stenosis or vessel wall narrowing by viewing the artery vessel from a cross-sectional view across a latitudinal axis.” wherein three degrees of freedom is rotating along the longitudinal and latitudinal axis).
The motivation for combining Min, Ilegbusi, and Wang is the same motivation as used for claim 1.
Regarding claim 8, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 1, wherein the immersive three- dimensional graphical representation of the one or more arteries is configured to allow a user to move the point of view within the one or more arteries along a longitudinal axis of the one or more arteries (Min - [0342] “FIG. 6F illustrates additional information of the three-dimensional (3D) rendering of the coronary artery tree 602 on the first panel 601 that allows a user to view the vessels and modify the labels of a vessel.” wherein an immersive three-dimensional graphical representation is the three-dimensional rendering) (Min - [0298] “In some embodiments, the linear view of the artery vessels shows a cross-sectional view along a longitudinal axis (or the length of the vessel or a long axis) of the artery vessel. In some embodiments, the system can be configured to allow the user to rotate in a 360° fashion about the longitudinal axis of the substantially linear artery vessels in order for the user to review the vessel walls from various views and angles.”).
The motivation for combining Min, Ilegbusi, and Wang is the same motivation as used for claim 1.
Regarding claim 9, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 1, further comprising generating, by the computer system, a treatment for cardiovascular disease for the subject based at least in part on the determined assessment of the state of cardiovascular disease of the one or more regions of plaque (Min - [0149] “In some embodiments, at block 214, the system is configured to generate a proposed treatment plan for the subject based on the analysis, such as for example the classification of plaque derived automatically from a raw medical image. In particular, in some embodiments, the system can be configured to assess or predict the risk of atherosclerosis, stenosis, and/or ischemia of the subject based on a raw medical image and automated image processing thereof.”).
The motivation for combining Min, Ilegbusi, and Wang is the same motivation as used for claim 1.
Regarding claim 11, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 9, wherein the treatment for cardiovascular disease comprises medical intervention, medical treatment, or lifestyle change (Min - [0260] “For example, in some embodiments, the system can be configured to generate a proposed treatment plan for the subject based on the change in calcium score and/or characterization thereof for the subject. In some embodiments, the generated treatment plan can include use of statins, lifestyle changes, and/or surgery.”).
The motivation for combining Min, Ilegbusi, and Wang is the same motivation as used for claim 1.
Regarding claim 14, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 1, wherein the state of assessment of cardiovascular disease state of the one or more regions of plaque based at least in part on a weighted measure of the one or more plaque parameters and the one or more vascular parameters (Min - [0215] “In some embodiments, the system can be configured weight one or more of these parameters logarithmically, algebraically, and/or utilizing another mathematical transform. In some embodiments, the system is configured to generate a risk assessment of coronary disease or cardiovascular event for the subject at block 366 using the weighted measure and/or using only some of these parameters.”) (Min - [0197] “In some embodiments, the system can be configured to generate a weighted measure of one or more vascular morphology parameters and/or quantified plaque parameters determined and/or derived from raw medical images.”).
The motivation for combining Min, Ilegbusi, and Wang is the same motivation as used for claim 1.
Regarding claim 15, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 1, further comprising:
generating, by the computer system, a weighted measure of one or more of the one or more vascular parameters and the one or more plaque parameters (Min - [0197] “In some embodiments, the system can be configured to generate a weighted measure of one or more vascular morphology parameters and/or quantified plaque parameters determined and/or derived from raw medical images.”),
wherein the assessment of the state of cardiovascular disease of the one or more regions of plaque is further determined based at least in part on the generated weighted measure (Min - [0215] “In some embodiments, the system can be configured weight one or more of these parameters logarithmically, algebraically, and/or utilizing another mathematical transform. In some embodiments, the system is configured to generate a risk assessment of coronary disease or cardiovascular event for the subject at block 366 using the weighted measure and/or using only some of these parameters.”).
The motivation for combining Min, Ilegbusi, and Wang is the same motivation as used for claim 1.
Regarding claim 16, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 1, wherein the assessment of the state of cardiovascular disease of the one or more regions of plaque is further determined based at least in part on one or more of age or gender of the subject (Min - [0215] “In some embodiments, the system can be configured weight one or more of these parameters logarithmically, algebraically, and/or utilizing another mathematical transform. In some embodiments, the system is configured to generate a risk assessment of coronary disease or cardiovascular event for the subject at block 366 using the weighted measure and/or using only some of these parameters.”) (Min - [0172] “In some embodiments, the characterization of coronary atherosclerosis, stenosis and/or vascular morphology can enable relating a patient's biological age to their vascular age, when compared to a population-based cohort of patients who have undergone similar scanning.”).
The motivation for combining Min, Ilegbusi, and Wang is the same motivation as used for claim 1.
Regarding claim 17, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 1, wherein the medical image is obtained using an imaging technique comprising one or more of computed tomography (CT), x-ray, ultrasound, echocardiography, intravascular ultrasound (IVUS), MR imaging, optical coherence tomography (OCT), nuclear medicine imaging, positron-emission tomography (PET), single photon emission computed tomography (SPECT), or near-field infrared spectroscopy (NIRS) (Min - [0015] “In some embodiments of a computer-implemented method of quantifying and classifying coronary plaque within a coronary region of a subject based on non-invasive medical image analysis, the medical image is obtained using an imaging technique comprising one or more of CT, x-ray, ultrasound, echocardiography, intravascular ultrasound (IVUS), MR imaging, optical coherence tomography (OCT), nuclear medicine imaging, positron-emission tomography (PET), single photon emission computed tomography (SPECT), or near-field infrared spectroscopy (NIRS).”).
The motivation for combining Min, Ilegbusi, and Wang is the same motivation as used for claim 1.
Regarding claim 18, the claim recites similar limitations to claim 1 but in the form of a system. Therefore, claim 18 recites similar limitations to claim 1 and is rejected for similar rationale and reasoning (see the analysis for claim 1 above).
Regarding claim 19, the claim recites similar limitations to claim 2 but in the form of a system. Therefore, claim 19 recites similar limitations to claim 2 and is rejected for similar rationale and reasoning (see the analysis for claim 2 above).
Regarding claim 20, the claim recites similar limitations to claim 3 but in the form of a system. Therefore, claim 20 recites similar limitations to claim 3 and is rejected for similar rationale and reasoning (see the analysis for claim 3 above).
Regarding claim 21, the claim recites similar limitations to claim 4 but in the form of a system. Therefore, claim 21 recites similar limitations to claim 4 and is rejected for similar rationale and reasoning (see the analysis for claim 4 above).
Regarding claim 22, the claim recites similar limitations to claim 5 but in the form of a system. Therefore, claim 22 recites similar limitations to claim 5 and is rejected for similar rationale and reasoning (see the analysis for claim 5 above).
Regarding claim 23, the claim recites similar limitations to claim 6 but in the form of a system. Therefore, claim 23 recites similar limitations to claim 6 and is rejected for similar rationale and reasoning (see the analysis for claim 6 above).
Regarding claim 24, the claim recites similar limitations to claim 7 but in the form of a system. Therefore, claim 24 recites similar limitations to claim 7 and is rejected for similar rationale and reasoning (see the analysis for claim 7 above).
Regarding claim 25, the claim recites similar limitations to claim 8 but in the form of a system. Therefore, claim 25 recites similar limitations to claim 8 and is rejected for similar rationale and reasoning (see the analysis for claim 8 above).
Regarding claim 26, the claim recites similar limitations to claim 9 but in the form of a system. Therefore, claim 26 recites similar limitations to claim 9 and is rejected for similar rationale and reasoning (see the analysis for claim 9 above).
Regarding claim 28, the claim recites similar limitations to claim 11 but in the form of a system. Therefore, claim 28 recites similar limitations to claim 11 and is rejected for similar rationale and reasoning (see the analysis for claim 11 above).
Regarding claim 31, the claim recites similar limitations to claim 14 but in the form of a system. Therefore, claim 31 recites similar limitations to claim 14 and is rejected for similar rationale and reasoning (see the analysis for claim 14 above).
Regarding claim 32, the claim recites similar limitations to claim 15 but in the form of a system. Therefore, claim 32 recites similar limitations to claim 15 and is rejected for similar rationale and reasoning (see the analysis for claim 15 above).
Regarding claim 33, the claim recites similar limitations to claim 16 but in the form of a system. Therefore, claim 33 recites similar limitations to claim 16 and is rejected for similar rationale and reasoning (see the analysis for claim 16 above).
Regarding claim 34, the claim recites similar limitations to claim 17 but in the form of a system. Therefore, claim 34 recites similar limitations to claim 17 and is rejected for similar rationale and reasoning (see the analysis for claim 17 above).
Claims 12 and 29 are rejected under 35 U.S.C. 103 as being unpatentable of Min et al., US 20210209757 A1, (hereinafter “Min”) in view of Ilegbusi et al., US 20080228086 A1, (hereinafter “Ilegbusi”) in further view of Wang et al., US 20190378312 A1 (hereinafter “Wang”) in further view of Nickisch et al., US 20210110543 A1, (hereinafter “Nickisch”).
Regarding claim 12, Min in view of Ilegbusi and Wang teaches the computer-implemented method of Claim 9, further comprising tracking, by the computer system, (Min - [0260] “For example, in some embodiments, the system can be configured to generate a proposed treatment plan for the subject based on the change in calcium score and/or characterization thereof for the subject. In some embodiments, the generated treatment plan can include use of statins, lifestyle changes, and/or surgery.”).
Min in view of Ilegbusi and Wang does not specifically disclose tracking efficacy of the treatment by determining assessment at a later point in time after treatment.
However, Nickisch teaches tracking efficacy of the treatment by determining assessment at a later point in time after treatment ([0035] “Documented patient outcome such as cardiac events or survival data can be used in a similar way to adapt parameters taking the previously obtained model prediction and the medical treatment into account. For example, if a lesion was considered insignificant via a CT-FFR assessment and that lesion caused a major cardiac event, then the assessment can be reconsidered and parameters such as the FFR threshold can be updated to better match the outcome.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to track the efficacy of the treatment plan of Nickisch to confirm the effectiveness of the generated treatment plan, thereby improving the accuracy of the overall cardiovascular disease assessment of Min in view of Ilegbusi and Wang.
Regarding claim 29, the claim recites similar limitations to claim 12 but in the form of a system. Therefore, claim 29 recites similar limitations to claim 12 and is rejected for similar rationale and reasoning (see the analysis for claim 12 above).
Allowable Subject Matter
Claims 10, 13, 27, and 30 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
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/AMANDA H PEARSON/Examiner, Art Unit 2666
/MING Y HON/Primary Examiner, Art Unit 2666