696DETAILED 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 .
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.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that use the word “means” or “step” but are nonetheless not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph because the claim limitation(s) recite(s) sufficient structure, materials, or acts to entirely perform the recited function. Such claim limitation(s) is/are: “an obtainer that obtains,” “a generator that generates,” and “an outputter that outputs” in claims 15-16.
One of ordinary skill in the art would understand that said units, elements, modules, etc. have sufficient structure, materials, or acts to perform the recited function because they belong to a medical image processing system implemented in a computing device.
Because this/these claim limitation(s) is/are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are not being interpreted to cover only the corresponding structure, material, or acts described in the specification as performing the claimed function, and equivalents thereof.
If applicant intends to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to remove the structure, materials, or acts that performs the claimed function; or (2) present a sufficient showing that the claim limitation(s) does/do not recite sufficient structure, materials, or acts to perform the claimed function.
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.
Claim(s) 1-12 and 15-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chenal et al. (US 2002/0072671 A1), in view of Min et al. (US 2021/0319558 A1), hereinafter referred to as Chenal and Min, respectively.
Regarding claim 1, Chenal teaches a wall thickness estimation method comprising:
obtaining behavioral information that is based on a video in which an organ wall or a blood vessel wall is captured, the behavioral information being numerical information about changes over time in a position of each of a plurality of predetermined points in the organ wall or the blood vessel wall (Chenal ¶¶0031: “Once these three major landmarks of the LV have been located, one of a number of predetermined standard shapes for the LV is fitted to the three landmarks and the endocardial wall … Such measurements are made along paths orthogonal to the shape and extending from points along the shape.”; Chenal ¶¶0044: “The walls of blood vessels such as the carotid artery can similarly be traced by identifying the center line of the vessel, then extending straight line shapes out from opposite sides of the center line to fit small line segments to the endothelial wall”; Chenal ¶¶0045: “FIG. 11 illustrates a technique for assessing regional wall motion using automated border detection. The drawing of FIG. 11 represents an ultrasound display in which the continuous motion of the endocardium or myocardium is shown over several complete heart cycles”; Chenal ¶¶0046: “This is overcome by tracking the anatomy from a baseline of control points over the heart cycle, as by speckle tracking each local point of the heart wall along the ABD trace from frame to frame”; Chenal ¶¶0058: “a video processor”);
generating estimation information using a model trained to take as an input an image indicating a physical parameter based on the behavioral information obtained in the obtaining and output an index indicating a thickness at each of the plurality of predetermined points in the organ wall or the blood vessel wall, the estimation information being information visualizing the thickness (Chenal ¶¶0050: “Automatically drawn cardiac borders may also be used to define the myocardial area in contrast-enhanced images or loops … Automatically drawn cardiac borders and perfusion information presented simultaneously in an image or loop is a powerful combination since the clinician can assess wall motion, thickening, and perfusion simultaneously. Given that the borders are known, the thickness of the myocardial walls between the endocardial and epicardial edges can be determined on a segment-by-segment basis as shown in FIG. 12”); and
outputting the estimation information generated in the generating (Chenal ¶¶0050 discussed above; Chenal Figs. 11, 12 & 14).
However, Chenal does not appear to explicitly teach using four-dimensional angiography.
Pertaining to the same field of endeavor, Min teaches using four-dimensional angiography (Min ¶¶1191: “the system can be configured to visualize plaque in 2D, 3D, and/or 4D”; ¶¶01241: “undergoing coronary CT angiography”).
Chenal and Min are considered to be analogous art because they are directed to medical image processing. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for automated border detection in diagnostic images (as taught by Chenal) to use 4D angiography (as taught by Min) because the combination enables continued personalized treatment for a subject with atherosclerotic cardiovascular disease (ASCVD) risk (Min ¶¶1633).
Regarding claim 2, Chenal, in view of Min, teaches the wall thickness estimation method according to claim 1, further comprising:
training the model using one or more datasets as training data, each of the datasets being constituted by a combination of (i) the image indicating the physical parameter based on the behavioral information at each predetermined point among the plurality of predetermined points and (ii) the index indicating the thickness at the predetermined point (Min ¶¶0187: “one or more AI and/or ML algorithms can be trained using a Convolutional Neural Network (CNN) on a set of medical images on which arteries or coronary arteries have been identified, thereby allowing the AI and/or ML algorithm automatically identify arteries or coronary arteries directly from a medical image. In some embodiments, the arteries or coronary arteries are identified by size and/or location”; Min ¶¶0231: “parameters associated with the left ventricle can include size, mass, volume, shape, eccentricity, surface area, thickness, and/or the like. Similarly, in some embodiments, parameters associated with the right ventricle can include size, mass, volume, shape, eccentricity, surface area, thickness, and/or the like. In some embodiments, parameters associated with the left atrium can include size, mass, volume, shape, eccentricity, surface area, thickness, pulmonary vein angulation, atrial appendage morphology, and/or the like. In some embodiments, parameters associated with the right atrium can include size, mass, volume, shape, eccentricity, surface area, thickness, and/or the like”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for automated border detection in diagnostic images (as taught by Chenal) to use a trained model (as taught by Min) because the combination can be configured to automatically and/or dynamically identify from raw medical images the presence and/or parameters of vessels, coronary arteries, and/or plaque (Min ¶¶0175).
Regarding claim 3, Chenal, in view of Min, teaches the wall thickness estimation method according to claim 2,
wherein in the training, the model is trained using machine learning (Min ¶¶0187 discussed above).
Regarding claim 4, Chenal, in view of Min, teaches the wall thickness estimation method according to claim 1,
wherein the estimation information is image information visualizing the thickness (Chenal Figs. 10, 12 & 14; Min ¶¶0353: “This system can display vessels in multi-planar formats, cross-sectional views, 3D coronary artery tree view, axial, sagittal, and coronal views based on a set of computerized tomography (CT) images, e.g., generated by a CT scan of a patient's vessels”).
Regarding claim 5, Chenal, in view of Min, teaches the wall thickness estimation method according to claim 1,
wherein the blood vessel wall is a wall of an arterial aneurysm or a varicose vein (Min ¶¶0985: “Vascular morphology—e.g., lumen volume, vessel volume, arterial remodeling, anomaly, aneurysm, bridging, dissection, etc.”; Min ¶¶1117: “the system can be configured to generate an assessment of other artery consequences, such as for example carotid (stroke), lower extremity (claudication, critical limb ischemia, amputation), aorta (dissection, aneurysm), renal artery (hypertension), cerebral artery (aneurysm, rupture), and/or the like”).
Regarding claim 6, Chenal, in view of Min, teaches the wall thickness estimation method according to claim 1,
wherein the blood vessel wall is a wall of a cerebral aneurysm (Min ¶¶1117 discussed above).
Regarding claim 7, Chenal, in view of Min, teaches the wall thickness estimation method according to claim 1,
wherein the blood vessel wall is a blood vessel wall of an artery or a vein (Min ¶¶0985 & ¶¶1117 discussed above).
Regarding claim 8, Chenal, in view of Min, teaches a non-transitory computer-readable recording medium having recorded thereon a computer program for causing a computer to execute the wall thickness estimation method according to claim 1 (Chenal Fig. 16).
Regarding claim 9, Chenal teaches a training method comprising:
obtaining behavioral information that is based on a video in which an organ wall or a blood vessel wall is captured, the behavioral information being numerical information about changes over time in a position of each of a plurality of predetermined points in the organ wall or the blood vessel wall (Chenal ¶¶0031, ¶¶0044-¶¶0046 & ¶¶0058 discussed above).
Chenal further teaches using a combination of (i) the image indicating a physical parameter based on the behavioral information at each predetermined point among the plurality of predetermined points, the behavioral information being the behavioral information obtained in the obtaining, and (ii) an index indicating a thickness at the predetermined point among the plurality of predetermined points (Chenal Figs. 11, 12, 14, & ¶¶0050).
However, Chenal does not appear to explicitly teach training a model using training data.
Pertaining to the same field of endeavor, Min teaches training a model using, as training data, one or more datasets constituted by a combination of (i) the image indicating a physical parameter based on the behavioral information at each predetermined point among the plurality of predetermined points, the behavioral information being the behavioral information obtained in the obtaining, and (ii) an index indicating a thickness at the predetermined point among the plurality of predetermined points (Min ¶¶0187 & ¶¶0231 discussed above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for automated border detection in diagnostic images (as taught by Chenal) to train a model (as taught by Min) because the combination can be configured to automatically and/or dynamically identify from raw medical images the presence and/or parameters of vessels, coronary arteries, and/or plaque (Min ¶¶0175).
Regarding claim 10, Chenal, in view of Min, teaches the training method according to claim 9,
wherein the video is obtained using four-dimensional angiography or a two-dimensional video capturing device (Chenal ¶¶0058 & Min ¶¶1191, ¶¶01241 discussed above).
Regarding claim 11, Chenal, in view of Min, teaches a model construction method comprising:
obtaining the estimation information generated in the generating according to claim 1 (Chenal ¶¶0050 discussed above); and
constructing a blood vessel model including the blood vessel wall according to claim 1, the blood vessel model being constructed based on the thickness visualized by the estimation information obtained in the obtaining of the estimation information to cause the blood vessel wall included in the blood vessel model to exhibit a different form according to the thickness (Min Fig. 6; Min ¶¶0197: “the system is configured to generate a quantized color mapping based on the analyzed and/or determined parameters … the system is configured to generate a visualization of the analyzed medical image by generating a quantized color mapping of calcified plaque, non-calcified plaque, good plaque, bad plaque, stable plaque, and/or unstable plaque as determined using any of the analytical techniques described herein … the quantified color mapping can also include arteries and/or epicardial fat, which can also be determined by the system, for example by utilizing one or more AI and/or ML algorithms”; Min ¶¶0212: “the system can be configured assign different colors to each of the different regions associated with different matters”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for automated border detection in diagnostic images (as taught by Chenal) to visualize differently based on thickness (as taught by Min) because the combination allows the physicians to quickly identify regions of interest, e.g., non-calcified plaque, good plaque, bad plaque, stable plaque, and/or unstable plaque, etc. (Min ¶¶0197).
Regarding claim 12, Chenal, in view of Min, teaches the model construction method according to claim 11,
wherein in the constructing of the blood vessel model, the blood vessel model is constructed such that the blood vessel wall exhibits a different color according to the thickness (Min ¶¶0197 & ¶¶0212 discussed above).
Regarding claim 15, Chenal, in view of Min, further teaches a wall thickness estimation device comprising an obtainer, a generator, and an outputter that perform the method described in claim 1 (Chenal Fig. 16; Min Fig. 19E). Therefore, claim 15 is rejected using the same rationale as applied to claim 1 discussed above.
Regarding claim 16, Chenal, in view of Min, further teaches a wall thickness estimation system comprising:
the wall thickness estimation device according to claim 15 (Chenal Fig. 16; Min Fig. 19E; refer to the rejection of claims 1 and 15 discussed above);
a video information processing device that obtains the video, generates the behavioral information, and outputs the behavioral information to the obtainer (Chenal ¶¶0031, ¶¶0044-¶¶0046, ¶¶0050, & ¶¶0058 discussed above); and
a display that displays the estimation information output by the outputter (Chenal Figs. 10 & 16; Min Fig. 6).
Claim(s) 13-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chenal et al. (US 2002/0072671 A1), in view of Min et al. (US 2021/0319558 A1), and further in view of Cornelissen et al. (“CT Imaging of Intracranial Vessels,” 2015, In: Trivedi, R., Saba, L., Suri, J. (eds) 3D Imaging Technologies in Atherosclerosis. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7618-5_4), hereinafter referred to as Chenal, Min, and Cornelissen, respectively.
Regarding claim 13, Chenal, in view of Min, teaches the model construction method according to claim 12,
wherein the blood vessel wall included in the blood vessel model constructed in the constructing of the blood vessel model is a wall of a cerebral aneurysm (Min ¶¶1117 discussed above).
However, Chenal, in view of Min, does not appear to explicitly teach constructing a brain model into which the blood vessel model constructed in the constructing of the blood vessel model is incorporated.
Pertaining to the same field of endeavor, Cornelissen teaches constructing a brain model into which the blood vessel model constructed in the constructing of the blood vessel model is incorporated (Cornelissen pg. 94: “Anatomy of the Intracranial Vessels”; Cornelissen Figs. 1, 8, 10-12, 15, 25, 30; Cornelissen pg. 109: “In the acute setting a non-contrast-enhanced CT (NECT) of the brain can reveal hemorrhage”).
Chenal, in view of Min, and Cornelissen are considered to be analogous art because they are directed to medical image processing. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for automated border detection in diagnostic images using machine learning (as taught by Chenal, in view of Min) to construct a brain model with blood vessels (as taught by Cornelissen) because the combination allows the physicians to locate hemorrhage (Cornelissen pg. 109).
Regarding claim 14, Chenal, in view of Min and Cornelissen, teaches the model construction method according to claim 13, further comprising:
constructing a skull model for containing the brain model constructed in the constructing of the brain model (Cornelissen Figs. 2, 5, 15, 25).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for automated border detection in diagnostic images using machine learning (as taught by Chenal, in view of Min) to construct a skull model with blood vessels (as taught by Cornelissen) because the combination allows the physicians to locate regions of interest within the cranial cavity (Cornelissen pg. 101, Fig. 15).
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-12 and 15-16 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-8 of U.S. Patent No. US 12,171,528 B2 and claims 1-11 of US 12,274,573 B2. Although the claims at issue are not identical, they are not patentably distinct from each other because the patents and the application are directed to estimating the thickness of a blood vessel or organ wall, e.g., vein, artery, etc. The patents and the application use behavioral information (i.e., changes in position over time) by tracking predetermined points over time and visualize the estimation by displaying the results.
Claims 13-14 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-8 of U.S. Patent No. US 12,171,528 B2 in view of Cornelissen et al. (“CT Imaging of Intracranial Vessels,” 2015, 3D Imaging Technologies in Atherosclerosis), and claims 1-11 of US 12,274,573 B2, in view of Cornelissen et al. (“CT Imaging of Intracranial Vessels,” 2015, 3D Imaging Technologies in Atherosclerosis), hereinafter referred to as the patents and Cornelissen, respectively.
Regarding claim 13, both patents teach the model construction method according to claim 12 (patents claim 8).
However, the patents do not appear to teach that the blood vessel wall included in the blood vessel model constructed in the constructing of the blood vessel model is a wall of a cerebral aneurysm and constructing a brain model into which the blood vessel model constructed in the constructing of the blood vessel model is incorporated.
Pertaining to the same field of endeavor, Cornelissen teaches the blood vessel wall included in the blood vessel model constructed in the constructing of the blood vessel model is a wall of a cerebral aneurysm constructing a brain model into which the blood vessel model constructed in the constructing of the blood vessel model is incorporated (Cornelissen pg. 94: “Anatomy of the Intracranial Vessels”; Cornelissen Figs. 1, 8, 10-12, 15, 25, 30; Cornelissen pg. 109: “In the acute setting a non-contrast-enhanced CT (NECT) of the brain can reveal hemorrhage”).
The patents and Cornelissen are considered to be analogous art because they are directed to medical image processing. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the blood vessel wall thickness estimation method and system (as taught by the patents) to construct a brain model with blood vessels (as taught by Cornelissen) because the combination allows the physicians to locate hemorrhage (Cornelissen pg. 109).
Regarding claim 14, the patents, in view of Cornelissen, teaches the model construction method according to claim 13, further comprising:
constructing a skull model for containing the brain model constructed in the constructing of the brain model (Cornelissen Figs. 2, 5, 15, 25).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the blood vessel wall thickness estimation method and system (as taught by the patents) to construct a skull model with blood vessels (as taught by Cornelissen) because the combination allows the physicians to locate regions of interest within the cranial cavity (Cornelissen pg. 101, Fig. 15).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SOO J SHIN whose telephone number is (571)272-9753. The examiner can normally be reached M-F; 10-6.
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/Soo Shin/Primary Examiner, Art Unit 2667 571-272-9753
soo.shin@uspto.gov