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 .
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.
Claim(s) 1-13 is/are rejected under 35 U.S.C. 101 because the claimed invention, considering all claim elements both individually and in combination as a whole, do not amount to significantly more than a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea).
Claim 1 is a claim to a process, machine, manufacture, or composition of matter and therefore meets one of the categorical limitations of 35 U.S.C. 101. However, claim 1 meets the first prong of the step 2A analysis because it is directed to a/an abstract idea, as evidenced by the claim language of “compute a microcirculatory resistance value for the vessel based on a transit time taken for an injected bolus to travel between a proximal position in the vessel and a distal position in the vessel;”, and “divide the computed microcirculatory resistance value by a transit length representing a length of the vessel between the proximal position and the distal position to provide the normalised microcirculatory resistance value”. This claim language, under the broadest, reasonable interpretation, encompasses subject matter that may be performed by a human using mental steps or with pen and paper that can involve basic critical thinking, which are types of activities that have been found by the courts to represents abstract ideas (i.e., the mental comparison in Ambry Genetics, or the diagnosing an abnormal condition by performing clinical tests and thinking about the results in Grams). The steps recited include a mathematic formula that may be performed by a human using a pen/paper. Furthermore, the use of a processor to perform these tasks does not contribute significantly because they are well-known, routine, and/or conventional and a generic computer structure such as “processor” is not significantly more according to Alice v. CLS.
The claim language also meets prong 2 of the step 2A analysis because the above-recited claim language does not integrate the abstract idea into a practical application. The disclosed technologies do not improve a technical field (see MPEP 2106.05(a)), affect a particular treatment for a disease or medical condition (see MPEP 2106.04(d)(2)), effect a transformation or reduction of a particular article to a different state or thing (see MPEP 2106.04(d)(2)), apply the judicial exception with, or by use of, a particular machine (see MPEP 2106.05(b)), or apply the judicial exception in some meaningful way beyond generally linking the use of the abstract idea to a particular technological environment (MPEP 2106.04(d)(2) and 2106.05(e)). As a result, step 2A is satisfied and the second step, step 2B, must be considered.
With regard to the second step, the claim does not appear to recite additional elements that amount to significantly more. The additional elements are “a processor”. A generic computer structure such as “a processor” is not significantly more according to Alice v. CLS. Therefore, these elements do not add significantly more and thus the claim as a whole does not amount to significantly more than a judicial exception.
Additionally, the ordered combination of elements do not add anything significantly more to the claimed subject matter. Specifically, the ordered combination of elements do not have any function that is not already supplied by each element individually. That is, the whole is not greater than the sum of its parts.
In view of the above, independent claim 1 fails to recite patent-eligible subject matter under 35 U.S.C. 101. Dependent claim(s) 2-13 fail to cure the deficiencies of independent claim 1 by merely reciting additional abstract ideas, further limitations on abstract ideas already recited, and/or additional elements that are not significantly more. Claim 6 recites the limitation “temperature sensor” and claim 13 recites the limitation “X-ray imaging system”. However, these elements are not “significantly more” because they are well-known, routine, and/or conventional as evidenced by para [0065] of Govari et al. (US 20110152856 A1) and para [0007] of Yoshimura et al. (US 20080232540 A1) respectively. Thus, claim(s) 1-13 is/are rejected under 35 U.S.C. 101.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 4 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 4 recites the limitation “multiply the computed microcirculatory resistance value by a reference vessel length to provide the normalised microcirculatory resistance value.”. However, claim 1 recites the limitation “divide the computed microcirculatory resistance value by a transit length representing a length of the vessel between the proximal position and the distal position to provide the normalised microcirculatory resistance value.”. It is unclear if the multiplication occurs after the division of the microcirculatory resistance or instead of it. If the former, it is unclear how the value is “normalized” as multiplying the obtained normalized value via division by another length would result in the same microcirculatory resistance value without normalization.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-3, 5, and 7-10 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by De Maria et al. (“Angiography-derived index of microcirculatory resistance as a novel, pressure-wire-free tool to assess coronary microcirculation in ST elevation myocardial infarction”)
Regarding claim 1, De Maria discloses a system for providing a normalised microcirculatory resistance value for a vessel (abstract), the system comprising: one or more processors (Index of Microcirculatory Resistance Measurement para 1: “CoroFlow system (Coroventis, Uppsala Sweden)”) configured to: compute a microcirculatory resistance value for the vessel based on a transit time taken for an injected bolus to travel between a proximal position in the vessel and a distal position in the vessel (Index of Microcirculatory Resistance Measurement para 1 “, mean aortic pressure (Pa), mean distal pressure (Pd) and mean transit time (tTmean) were measured both at baseline and at hyperaemia, achieved with intravenous infusion of adenosine at a rate of 140 µg/kg/min. Mean transit time was calculated as the average of three transit time measurements during three separate injections of 3 ml of room temperature 0.9% saline solution. IMR was then calculated as follows IMR = Pd(hyperaemia) × tTmean(hyperaemia)”); and divide the computed microcirculatory resistance value by a transit length representing a length of the vessel between the proximal position and the distal position to provide the normalised microcirculatory resistance value (Angiography-derived index of microcirculatory resistance para 2: “tTmean(hyperaemia) can be expressed as the ratio between the number of frames (Nframes) for contrast dye to travel, during hyperaemia, from the guiding catheter to a distal reference (corresponding to the position of the distal marker of the pressure wire) divided by the acquisition rate (fps). MRangio = Pa(hyperaemia) × QFR × Nframes(hyperaemia)/fps”).
Regarding claim 2, De Maria discloses wherein the one or more processors are configured to compute the microcirculatory resistance value for the vessel by multiplying the transit time by a distal intraluminal pressure value, the distal intraluminal pressure value representing a pressure in the vessel at the distal position in the vessel ( Angiography-derived index of microcirculatory resistance para 1: “where Pd(hyperaemia) is distal pressure at hyperaemia”,
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Regarding claim 3, De Maria discloses wherein the microcirculatory resistance value is an index of microcirculatory resistance value (abstract: “measure the index of microcirculatory resistance (IMR)”).
Regarding claim 5, De Maria discloses receiving intraluminal sensor data comprising at least one of pressure data and temperature data (Quantitative flow ratio measurement para 3: "exactly at the site of the distal pressure/temperature transducer."), and determine at least one of the distal intraluminal pressure value and the transit time from the received intraluminal sensor data (Quantitative flow ratio measurement para 3).
Regarding claim 7, De Maria discloses wherein the one or more processors are further configured to: receive X-ray angiographic image data comprising a temporal sequence of images representing a flow of the injected bolus through the vessel (Quantitative flow ratio measurement para 1:“angiographic images were acquired at 15 frame/second with manual injection of contrast dye during maximal hyperaemia, using a monoplane radiographic system (Siemens Healthcare, Germany)”; and analyse the X-ray image data to determine the transit time and an estimate of the transit length (Angiography-derived index of microcirculatory resistance para 8: “being fps set at 15 frame/second for QFR measurement.”).
Regarding claim 8, De Maria further discloses the injected bolus comprises an injected contrast agent bolus, and the one or more processors are further configured to: identify the proximal position and the distal position in the vessel in the X-ray image data (Angiography-derived index of microcirculatory resistance para 4: “from the guiding catheter to a distal reference (corresponding to the position of the distal marker of the pressure wire”); and determine the transit time based on the time taken for the injected contrast agent bolus to travel between the identified proximal position in the vessel, and the identified distal position in the vessel, in the X-ray image data (Angiography-derived index of microcirculatory resistance para 4: “Since QFR is a surrogate of Pd(hyperaemia)/Pa(hyperaemia) ratio, (QFR ~ ), QFR can be used to replace in the formula. Similarly, tTmean(hyperaemia) can be expressed as the ratio between the number of frames (Nframes) for contrast dye to travel, during hyperaemia, from the guiding catheter to a distal reference (corresponding to the position of the distal marker of the pressure wire) divided by the acquisition rate (fps).”); and compute the estimate of the transit length based on a length of the vessel between the proximal position and the distal position, in the X-ray image data (Angiography-derived index of microcirculatory resistance para 4).
Regarding claim 9, De Maria discloses wherein the proximal position corresponds to a position of a detected front of the injected contrast agent bolus in the vessel in an earlier X-ray image in the temporal sequence, and wherein the distal position corresponds to a position of the detected front in a later X-ray image in the temporal sequence (Angiography-derived index of microcirculatory resistance para 4: “from the guiding catheter to a distal reference (corresponding to the position of the distal marker of the pressure wire”); and wherein the transit time corresponds to a time difference between the earlier X-ray image and the later X-ray image (Angiography-derived index of microcirculatory resistance para 7: “frame/second”); and wherein the estimate of the transit length is computed by: mapping the proximal position from the earlier image to the later image to provide a mapped proximal position in the later image, or by mapping the distal position from the later image to the earlier image to provide a mapped distal position in the earlier image (Angiography-derived index of microcirculatory resistance para 4: “number of frames (Nframes) for contrast dye to travel”); and determining a length of the vessel between the mapped proximal position and the distal position in the later image, or between the proximal position and the mapped distal position in the earlier image, respectively (Angiography-derived index of microcirculatory resistance para 6: “Nframes/fps”).
Regarding claim 10, wherein the distal position corresponds to one of: the most distal position in the vessel in the X-ray image data away from the proximal position(Angiography-derived index of microcirculatory resistance para 4: “from the guiding catheter to a distal reference (corresponding to the position of the distal marker of the pressure wire”); or a position in the distal two-thirds of the vessel in the X-ray image data; or a position in the vessel in the X-ray image data providing an estimate of the transit length that exceeds a reference transit length; or the most distal identifiable position in the vessel providing an estimate of the transit length that is not locally foreshortened above a predetermined reference foreshortening value.
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.
Claim(s) 4 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over De Maria in view of in view of in view of Liu et al. (CN 110384494 A).
Regarding claim 4, De Maria discloses the system according to claim 1, but fails to disclose wherein the one or more processors are further configured to multiply the computed microcirculatory resistance value by a reference vessel length to provide the normalised microcirculatory resistance value.
Liu discloses wherein the one or more processors are further configured to multiply the computed microcirculatory resistance value by a reference vessel length to provide the normalised microcirculatory resistance value ([0058-0060]: “calculating instantaneous no wave microcirculation resistance index iFMR, calculating formula is as follows: iFMR = (Pa ' -Δ ') * L/Vf; wherein, L represents a length of the blood vessel, N represents the frame number of the partial region image of coronary angiography image is divided into,”).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the system disclosed by De Maria to include the multiplication of the computed microcirculatory resistance value by a reference vessel length as disclosed by Liu in order to improve the accuracy of the assessment (Liu [0170]). Furthermore, it would have been obvious to substitute the known method of normalization disclosed by De Maria with the known method of normalization via multiplication disclosed by Liu for the predictable result of obtaining a normalized IMR value.
Regarding claim 12, De Maria discloses wherein the injected bolus passes the proximal position in the vessel at a proximal time, and the injected bolus passes the distal position in the vessel at a distal time, and wherein the injected bolus has an average transit velocity defined as a ratio of the transit length to the transit time, and wherein the one or more processors are further configured to correct the transit time such that the normalised microcirculatory resistance value is provided based on a corrected transit time (Angiography-derived index of microcirculatory resistance paras 1-4 “where Pd(hyperaemia) is distal pressure at hyperaemia and tTmean(hyperaemia) is mean transit time at hyperaemia. By multiplying and dividing by hyperaemic aortic pressure (Pa(hyperaemia)), the formula becomes: Since QFR is a surrogate of Pd(hyperaemia)/Pa(hyperaemia) ratio, (QFR ~ ), QFR can be used to replace in the formula. Similarly, tTmean(hyperaemia) can be expressed as the ratio between the number of frames (Nframes) for contrast dye to travel, during hyperaemia, from the guiding catheter to a distal reference (corresponding to the position of the distal marker of the pressure wire) divided by the acquisition rate (fps)”).
De Maria fails to disclose wherein the one or more processors are configured to provide the corrected transit time by: receiving measured cardiac cycle data for a heart fluidically coupled to the vessel, the measured cardiac cycle data comprising a measured cardiac period, and a time of a signature of each of one or more cardiac states within the cardiac cycle; mapping the time of the one or more signatures, and the proximal time, and the distal time, to corresponding times within the measured cardiac period; receiving reference fluid velocity data comprising a time-dependent reference fluid velocity curve representing a fluid velocity in the vessel over a reference cardiac cycle having a reference cardiac period; Identifying in the reference fluid velocity curve, a time of a reference signature corresponding to each of the one or more cardiac states in the measured cardiac cycle data; transforming a time axis of the reference fluid velocity curve such that the reference cardiac period matches the measured cardiac period, and such that the time of the reference signature of each of the one or more cardiac states identified in the reference fluid velocity curve corresponds to the time of the signature of each of the one or more corresponding cardiac states in the measured cardiac cycle data; transforming an amplitude axis of the transformed reference fluid velocity curve to provide an amplitude-transformed reference fluid velocity curve such that an average velocity of the amplitude-transformed reference fluid velocity curve computed over a time interval between the proximal time and the distal time, corresponds to the average transit velocity; and providing a corrected transit time by multiplying the transit time by a ratio of the average transit velocity to the average velocity of the amplitude-transformed reference fluid velocity curve over a full cardiac cycle.
Liu discloses receiving measured cardiac cycle data for a heart fluidically coupled to the vessel, the measured cardiac cycle data comprising a measured cardiac period, and a time of a signature of each of one or more cardiac states within the cardiac cycle ([0026]: “N represents the number of frames in the local region image divided into the heartbeat cycle region, and fps represents the time interval between switching between two adjacent frames.”); mapping the time of the one or more signatures, and the proximal time, and the distal time, to corresponding times within the measured cardiac period ([0024]: “within the cardiac cycle region employs a contrast agent transport time algorithm, including: dividing the cardiac cycle region into N local region images;”); receiving reference fluid velocity data comprising a time-dependent reference fluid velocity curve representing a fluid velocity in the vessel over a reference cardiac cycle having a reference cardiac period ([0027]: “the method for measuring the blood flow velocity, include: contrast agent traversal distance algorithm, Stewart-Hamilton algorithm, First-pass distribution analysis method, optical flow method, or fluid continuity method”); Identifying in the reference fluid velocity curve, a time of a reference signature corresponding to each of the one or more cardiac states in the measured cardiac cycle data ([0023]: “represent the measurement of the average blood flow velocity within the cardiac cycle region, a represents a constant ranging from 1 to 3, and b represents a constant ranging from 50 to 300.”); transforming a time axis of the reference fluid velocity curve such that the reference cardiac period matches the measured cardiac period, and such that the time of the reference signature of each of the one or more cardiac states identified in the reference fluid velocity curve corresponds to the time of the signature of each of the one or more corresponding cardiac states in the measured cardiac cycle data ([0023], wherein the cycle corresponds to the state); transforming an amplitude axis of the transformed reference fluid velocity curve to provide an amplitude-transformed reference fluid velocity curve such that an average velocity of the amplitude-transformed reference fluid velocity curve computed over a time interval between the proximal time and the distal time, corresponds to the average transit velocity ([0023-0024]); and providing a corrected transit time by multiplying the transit time by a ratio of the average transit velocity to the average velocity of the amplitude-transformed reference fluid velocity curve over a full cardiac cycle ([0114-0117]: “employs a contrast agent transport time algorithm, including: dividing the heartbeat cycle region into N local region images… : contrast agent traversal distance algorithm, Stewart-Hamilton algorithm, First-pass distribution analysis method, optical flow method, or fluid continuity method.”).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the system disclosed by De Maria with the system disclosed by Liu in order to improve the accuracy of the determined parameters.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over De Maria in view of Kassab (US 20110178417 A1).
Regarding claim 6, De Maria discloses the system according to claim 5, but fails to disclose wherein: the intraluminal sensor data is provided by an intraluminal device comprising a proximal temperature sensor and a distal temperature sensor, and the one or more processors are further configured to determine the transit time based on the time taken for a temperature transition induced by the injected bolus to travel between the proximal temperature sensor in the vessel and the distal temperature sensor in the vessel; and wherein the transit length corresponds to a length of the intraluminal device between the proximal temperature sensor and the distal temperature sensor.
Kassab discloses wherein an intraluminal sensor data is provided by an intraluminal device comprising a proximal temperature sensor and a distal temperature sensor ([0040]: “sensors 102 are separated by a distance L as shown therein. As discussed in greater detail herein, an exemplary method for determining FFR is based upon the principle that two or more sensors 102 spaced at a predetermined distance apart can “time” the injection of a bolus injection as the plug flow moves past the sensors 102 sequentially (e.g., sensor 102 “1” first, and then sensor 102 “2” as shown in FIG. 1)… thermocouples”), and the one or more processors are further configured to determine the transit time based on the time taken for a temperature transition induced by the injected bolus to travel between the proximal temperature sensor in the vessel and the distal temperature sensor in the vessel ([0040]: “and the time difference between the detection of the bolus by sensors 102.”); and wherein the transit length corresponds to a length of the intraluminal device between the proximal temperature sensor and the distal temperature sensor ([0040]: “sensors 102 are separated by a distance L”).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to substitute the known method of detecting a transit time disclosed by De Maria to the method of detecting a transit time via temperature sensor as disclosed by Kassab for the predictable result of determining the amount of time it takes a bolus to traverse a distance.
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over De Maria in view of Strobel (US 20090016587 A1).
Regarding claim 11, De Maria discloses the system of claim 10 but fails to disclose wherein the vessel forms part of a vessel tree, and wherein the temporal sequence of images represents the vessel tree, and further represents a flow of the injected contrast agent bolus through the vessel tree; and wherein the one or more processors are further configured to: generate a time-intensity curve for the vessel tree from the temporal sequence of images; and calculate the transit time from the time-intensity curve, the transit time being defined by a difference between a first point in time at which the bolus enters a portion of the vessel tree, and a second point in time at which the bolus saturates the vessel tree, in the corresponding images in the temporal sequence.
Strobel discloses wherein a vessel forms part of a vessel tree, and wherein the temporal sequence of images represents the vessel tree ([0005]: “such as a vessel tree”), and further represents a flow of the injected contrast agent bolus through the vessel tree ([0010]: “the time series of digital images of blood flow comprises a digital subtraction angiography sequence of a contrast agent bolus propagating through said patient's bloodstream”); and wherein the one or more processors are further configured to: generate a time-intensity curve for the vessel tree from the temporal sequence of images ([0012]: “calculating one or more time-density curves from said second time series of digital images, each curve indicative of how the intensity at corresponding points in successive images changes over time”); and calculate the transit time from the time-intensity curve ([0034]: “bolus arrival time can be computed from a time-density curve”), the transit time being defined by a difference between a first point in time at which the bolus enters a portion of the vessel tree, and a second point in time at which the bolus saturates the vessel tree, in the corresponding images in the temporal sequence ([0012]: “each curve indicative of how the intensity at corresponding points in successive images changes over time, selecting a first projection point in a first image in one time series, applying spatial and temporal constraints to locate a corresponding second projection point in a temporally corresponding second image in the other time series, and calculating a 3D coordinate from the 2D coordinates of the first and second projection points.”).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the system disclosed by De Maria to include the vessel tree disclosed by Stobel in order to obtain a more robust data set of additional vessel branches.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over De Maria in view of Carroll (US 6501848 B1).
Regarding claim 12, De Maria further discloses the images comprise projection images generated by an X-ray imaging system. However, De Maria fails to disclose the one or more processors are further configured to: receive X-ray imaging system geometric data representing an orientation of the X-ray imaging system respective the vessel; and determine the estimate of the transit length by: determining a length scale factor for positions along a length of the vessel in one or more of the X-ray projection images, based on a matching between the vessel in the one or more of the X- ray projection images, and a reference vessel in a reference projection image generated by projecting a 3D model of a reference vessel representing the vessel using the X-ray imaging system geometric data; and computing the length of the vessel between the proximal position and the distal position (Posd) by scaling the vessel represented in the one or more X-ray projection images, with the length scale factor determined at the corresponding positions along the length of the vessel, to provide the estimate of the transit length.
Carroll discloses the one or more processors are further configured to: receive X-ray imaging system geometric data representing an orientation of the X-ray imaging system respective the vessel (col 3 lines 58-61 “and the 3-D coronary arterial trees were reconstructed, including both left and right coronary artery systems. Various two-dimensional (2-D) projection images of the reconstructed 3-D coronary arterial tree were generated and compared to other viewing angles obtained in the actual patient study.”); and determine the estimate of the transit length by: determining a length scale factor for positions along a length of the vessel in one or more of the X-ray projection images, based on a matching between the vessel in the one or more of the X- ray projection images, and a reference vessel in a reference projection image generated by projecting a 3D model of a reference vessel representing the vessel using the X-ray imaging system geometric data (col 4 lines 26-31:“determining a transformation in the form of a rotation matrix and a translation vector utilizing the bifurcation points corresponding to each of the projections images, the rotation matrix, and the translation vector representing imaging parameters corresponding to the relative orientations of the imaging portions of the imaging system”); and computing the length of the vessel between the proximal position and the distal position (Posd) by scaling the vessel represented in the one or more X-ray projection images, with the length scale factor determined at the corresponding positions along the length of the vessel (col4 lines 31-41: “utilizing the data points and the transformation to establish a correspondence between the two-dimensional vessel centerlines corresponding to each of the projection images such that each data point corresponding to one projection image is linked to a data point corresponding to the other projection images, the linked data points representing an identical location in the vessel of the target object after the projections; h) calculating three-dimensional vessel centerlines utilizing the two-dimensional vessel centerlines and the correspondence between the data points of the two-dimensional vessel centerlines;”), to provide the estimate of the transit length (col 9 lines 10-12: “Element 3708 is operable to evaluate the length of a selected arterial segment from the arterial tree image presently under study”).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the system disclosed by De Maria with the length scale factor disclosed by Carroll in order to account for foreshortening in exclusively 2D models and improve the accuracy of the calculated length (Carroll col 2 lines 65-68).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Xie et al. (CN113693579A) – discloses a method of normalizing a microcirculatory resistance index
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/KAVYA SHOBANA BALAJI/Examiner, Art Unit 3791
/DEVIN B HENSON/Primary Examiner, Art Unit 3791
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