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 .
Response to Amendment
This action is in response to the remarks filed on 5/15/2026.
The amendments filed on 5/15/2026 have been entered. Accordingly claims 1-13 remain pending.
The objections to the claims have been withdrawn in light of the amendments and the applicant’s remarks.
Claim Interpretation
Claims 2 and 6 recite the newly amended limitation of “if the VFR is (a) below 0.83” which in an interpretation it may be construed as a conditional limitation where the limitations followed by the conditional limitations may not be given a full weight in light of the below decisions as for considering the other case scenario of “if the VFR is” not being “below 0.83”.
In the recent Ex parte Gopalan decision, the PTAB addressed a claim where all of the features were recited in a conditional manner. A first step of “identifying … an outlier” was performed if “traffic is outside of a prediction interval.” A second step of “identifying” was performed “only when a count of outliers … is greater than or equal to two, and exceeds an anomaly threshold.” These were the only two elements of the independent claim. Thus, if the traffic is never outside Gopalan’s prediction interval, then the steps of the method are never performed.
However, the PTAB distinguished Schulhauser and noted that this construction “would render the entire claim meaningless.” Gopalan at p. 5. The Board went on to state, “Although each of these steps is conditional, they are integrated into one method or path and do not cause the claim to diverge into two methods or paths, as in Schulhauser. Thus, we conclude that the broadest reasonable interpretation of claim 1 requires the performance of both steps…” Id. at p. 6.”
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim 1 and 7 recite “calculating… a virtual flow reserve” and “determining a clinical outcome”.
The limitation of “calculating”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “by a [presumed] processor,” (presumption is due to the storing in an electronic memory device) nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “by a processor” language, “calculating” in the context of this claim encompasses the user manually calculating the amount manually or with a simple pen and paper. Similarly, the limitation of “determining”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example, but for the “by a processor” language, “determining” in the context of this claim encompasses the user thinking of an outcome for a cutoff value. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites one additional element – using a processor to perform the limitation of “calculating… virtual flow reserve” and “determining a clinical outcome”. The processor in both steps is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of “” such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform “” steps amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
The depending claims also recite similar abstract ideas (e.g., determined, etc.) without additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application.
Therefore, the claims are not patent eligible.
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-13 are rejected under 35 U.S.C. 103 as being unpatentable over Sauer (US 20160022371) in view of Rai et al (The Value of Pre- and Post-Stenting Fractional Flow Reserve for Predicting Mid-Term Stent Restenosis Following Percutaneous Coronary Intervention (PCI), Glob J Health Sci. 2015 Dec 16;8(7):240–244) and Schmitt et al (US 20170245824 A1).
Regarding claim 1, Sauer teaches a method of predicting a clinical outcome of one or more treated blood vessels in a patient (“predicted hemodynamic metrics for the set of stenotic lesions resulting from the stenting configuration” abst), the method comprising the steps of:
receiving, by one or more processors, blood vessel image data collected from the treated blood vessel in a patient (“invention may be performed within a computer system using data stored within the computer system” [0013]);
calculating , by the one or more processors, a virtual flow reserve (VFR) of the treated blood vessel based on the blood vessel image data (“anatomical modeling tasks can be performed automatically … the anatomical models to analyze the effects of such changes on the subsequent computation of FFR [hence Virtual FFR]” [0020]; “automatically detected in the medical image data or in the patient-specific anatomical model of the coronary arteries and then a hemodynamic metric, such as FFR, can be computed for each of the detected lesions” [0021]; “the predicted FFR values for each treatment option can be computed by adjusting patient-specific measurements (e.g., radius measurements) for the stented lesion(s) to reflect full or partial opening due to the virtual stenting and then computed FFR values based on the adjusted patient-specific measurements using a machine learning based technique” [0034]);
determining, by the one or more processors, a clinical outcome of the treated blood vessel in the patient using a cutoff for VFR, wherein the cutoff for altering the clinical outcome is equal to 0.83 (“With two lesions “in series” upstream/downstream of each other, the stenting options are (1) stent lesion #1, (2) stent lesion #2, (3) stent both lesions #1 and #2, and (4) don't stent any lesion. Stenting all lesions (option 3) will restore maximal blood flow. Apart from very pathologic cases, this option can be considered to be curative and, in a possible implementation, does not require extra confirmation by simulation. The evaluation of the stenting options to predict FFR values is performed to determine whether stenting only a subset of the serial lesions is sufficient to restore blood flow such that the predicted FFR values are above the threshold. For the case of two lesions, the evaluation in step 110 can automatically determine whether it is sufficient to stent only lesion #1 or only lesion #2, and if stenting sufficient restores the blood flow, whether lesion #1 or lesion #2 is the preferred lesion to stent. In a possible implementation, we have three stenting options (1)-(3), two of which need to be evaluated. Option (4) can be evaluated by assessing the FFR value after the most distal lesion (in this case downstream of lesion #2) without any stenting. If the FFR value is greater than the threshold (e.g., >0.8), then stenting is not needed for either of the lesions.” [0029]); and
providing for display, by the one or more processors, an indicator of the clinical outcome, wherein the indicator is text, a number, a symbol, a color, a picture, or any combination thereof (“FIGS. 4-10 illustrate predicted FFR values for a set of serial stenotic lesions (stenosis 1, stenosis 2, and stenosis 3) in the left anterior descending (LAD) artery for different stenting configurations. FIG. 4 illustrates predicted FFR values resulting from a stenting configuration in which only stenosis 1 is stented. FIG. 5 illustrates predicted FFR values resulting a stenting configuration in which only stenosis 2 is stented. FIG. 6 illustrates predicted FFR values resulting from a stenting configuration in which only stenosis 3 is stented. FIG. 7 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1 and stenosis 2 are stented. FIG. 8 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1 and stenosis 3 are stented. FIG. 9 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 2 and stenosis 3 are stented. FIG. 10 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1, stenosis 2, and stenosis 3 are all stented. [0038]”).
As factually seen above, Sauer teaches all the claimed limitations including setting a cutoff VFR as 0.83 as within the realm of skilled artisan under broadest reasonable interpretation; yet, if one argues in a narrower interpretation that Sauer does not teach (which the office does not concede) virtual flow reserve and the cutoff is equal to 0.83, the below references are brought in to provide compact prosecution to show the narrow interpretation.
However, in the same field of endeavor, Rai also teaches FFR cut-off values. Measuring fractional flow reserve (FFR) in percutaneous coronary intervention (PCI) has predictive value for PCI outcome. We decided to examine the utility of pre- and post-stenting FFR as a predictor of 6-month stent restenosis as well as MACE (major adverse cardiac events). Pre- and post-stenting FFR values were measured for 60 PCI patients. Within 6 months after stenting, all patients were followed for assessment of cardiac MACE including myocardial infarction, unstable angina, or positive exercise test. Stent restenosis was also assessed. Cut-off values for pre- and post-stenting FFR measurements were considered respectively as 0.65 and 0.92. Stent restenosis was detected in 4 patients (6.6%). All 4 patients (100%) with restenosis had pre-stenting FFR of < 0.65, while only 26 of 56 patients without restenosis (46.4%) had pre-stenting FFR value of < 0.65 (P = 0.039). Mean pre-stenting FFR in patients with restenosis was significantly lower than in those without restenosis (0.25 ± 0.01 vs. 0.53 ± 0.03, P = 0.022). Although stent restenosis was higher in patients with post-stenting FFR of < 0.92 (2 cases, 9.5%) than in those with FFR value of ≥ 0.92 (2 cases, 5.1%), the difference was not statistically (P = 0.510) (Abst).
It would have been obvious to an ordinary skilled in the art before the invention was made to modify the method and/or device of the modified combination of reference(s) as outlined above with setting the FFR cutoff value to equal to 0.83 as taught by Rai because it leads to the high diagnostic accuracy of FFR in clinical setting (Intro of Rai).
Further, also in the same field of endeavor, Schmitt teaches cardiac data is processed by a processing unit comprising a first fractional flow reserve (FFR) providing unit (11) for providing first FFR values being indicative of the FFR of different arteries of the living being, wherein said virtual FFR values were calculated from non-invasive imaging data of arteries of the living being; a second FFR providing unit (12) for providing FFR values measured in the arteries of the living being; a correction unit (13) configured to correct the first FFR values based on the second FFR values; and a display unit (14) configured to display at least one first FFR value and a second FFR value for a corresponding position in the coronary arteries. The first and second FFR values are displayed to a cardiologist, who can base his course of action on the simulated and corrected values (abst). Simulation methods for the FFR value is calculated on the basis of non-invasive medical imaging (such as computed tomography, NMR, PET and the like) to determine a degree of stenosis by performing FFR calculations based on reconstructed arterial information. This ‘virtual FFR value’ used as input for a cardiologist to determine a further course of action [0003]. In FIG. 3a a 3D model of an arterial tree segment is shown with first (simulated) FFR values for 5 positions in the arterial tree (indicated by the acronym SIM and the FFR value). When an FFR value is higher than a critical value (in this case FFR>0.8) it is indicated by the word ‘OK’. In case an FFR value is critical (in this case FFR<=0.8) a warning sign is shown. Alternatively this could be indicated differently, e.g. by flashing the critical values or by color coding in two or more colors, such as red for critical FFR, green for non-critical FFR and optionally orange for borderline cases (e.g. 0.8<FFR 0.85). In FIG. 3a the simulated FFR values show that there is one critical FFR value at the fourth position from the top [0033].
It would have been obvious to an ordinary skilled in the art before the invention was made to modify the method and/or device of the modified combination of reference(s) as outlined above with setting a cutoff value for virtual FFR which is a design choice for a practitioner to set a cautionary measure to determine when an action should be taken as taught by Schmitt because it would therefore be desirable to reduce the time needed for diagnosis or treatment ([0004] of Schmitt).
Regarding claim 2, Sauer teaches wherein if the VFR is (a) below 0.83, it is determined that the treated blood vessel more likely than not to experience a poor clinical outcome; or (b) equal to or above 0.83, it is determined that the treated blood vessel is more likely than not, not to experience a poor clinical outcome (“computational approaches such as machine-learning based approaches, and these values can be used to compute hemodynamic quantities, such as fractional flow reserve (FFR), that support an initial clinical decision regarding whether or not therapy in the form of stenting one or more of the lesions is needed” [0014]; “FIGS. 4-10 illustrate predicted FFR values for a set of serial stenotic lesions (stenosis 1, stenosis 2, and stenosis 3) in the left anterior descending (LAD) artery for different stenting configurations. FIG. 4 illustrates predicted FFR values resulting from a stenting configuration in which only stenosis 1 is stented. FIG. 5 illustrates predicted FFR values resulting a stenting configuration in which only stenosis 2 is stented. FIG. 6 illustrates predicted FFR values resulting from a stenting configuration in which only stenosis 3 is stented. FIG. 7 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1 and stenosis 2 are stented. FIG. 8 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1 and stenosis 3 are stented. FIG. 9 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 2 and stenosis 3 are stented. FIG. 10 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1, stenosis 2, and stenosis 3 are all stented.” [0038]).
Regarding claims 3 and 10, Sauer teaches wherein the treated blood vessel is a blood vessel that has previously undergone one or more of angioplasty, stenting, atherectomy, or any combinations thereof (”the plurality of treatment options corresponds to a stenting configuration in which one or more of the stenotic lesions are stented” [0006]).
Regarding claims 4 and 11, Sauer teaches wherein the treated blood vessel has previous received one or more intravascular stents (”the plurality of treatment options corresponds to a stenting configuration in which one or more of the stenotic lesions are stented” [0006]).
Regarding claim 5, Sauer teaches wherein the poor clinical outcome is target vessel failure, target lesion failure, or a combination thereof (“set of stent combinations can include options corresponding stenting each individual lesion and options corresponding to stenting each possible combination of multiple target stenosis regions, up to an option corresponding to stenting all of the target stenosis regions. In a possible embodiment, multiple treatment options corresponding to different stent characteristics (e.g., implant sizes and/or implant typed, etc.) can be generated for each possible stent combination.” [0027]).
Regarding claim 6, Sauer teaches wherein if the VFR is below 0.83, it is determined that treated blood vessel is more likely than not to experience a poor clinical outcome (“computational approaches such as machine-learning based approaches, and these values can be used to compute hemodynamic quantities, such as fractional flow reserve (FFR), that support an initial clinical decision regarding whether or not therapy in the form of stenting one or more of the lesions is needed” [0014]; “FIGS. 4-10 illustrate predicted FFR values for a set of serial stenotic lesions (stenosis 1, stenosis 2, and stenosis 3) in the left anterior descending (LAD) artery for different stenting configurations. FIG. 4 illustrates predicted FFR values resulting from a stenting configuration in which only stenosis 1 is stented. FIG. 5 illustrates predicted FFR values resulting a stenting configuration in which only stenosis 2 is stented. FIG. 6 illustrates predicted FFR values resulting from a stenting configuration in which only stenosis 3 is stented. FIG. 7 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1 and stenosis 2 are stented. FIG. 8 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1 and stenosis 3 are stented. FIG. 9 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 2 and stenosis 3 are stented. FIG. 10 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1, stenosis 2, and stenosis 3 are all stented.” [0038]).
Regarding claim 7, Sauer teaches a system for use in predicting a clinical outcome of one or more treated blood vessels in a patient (“system for automated decision support for treatment planning of arterial stenoses is disclosed” abst; “predicted hemodynamic metrics for the set of stenotic lesions resulting from the stenting configuration” abst), the system comprising:
a diagnostic system to obtain blood vessel image data from a treated blood vessel of interest in a patient (“set of stenotic lesions is identified in a patient's coronary arteries from medical image data of the patient. A plurality of treatment options are generated for the set of stenotic lesions, wherein each of the plurality of treatment options corresponds to a stenting configuration in which one or more of the stenotic lesions are stented” abst), the diagnostic system comprising:
an electronic memory device (“invention may be performed within a computer system using data stored within the computer system” [0013]);
a processor in communication with the electronic memory device (Fig. 11), wherein the memory device comprises instructions executable by the processor to cause the processor to (“FIG. 1 may be defined by the computer program instructions stored in the memory 1110 and/or storage 1112 and controlled by the processor 1104 executing the computer program instructions” [0039]):
compute, using the processor, a virtual flow reserve (VFR) of the treated blood vessel, wherein the VFR is generated using blood vessel data collected from a treated blood vessel (“anatomical modeling tasks can be performed automatically … the anatomical models to analyze the effects of such changes on the subsequent computation of FFR [hence Virtual FFR]” [0020]; “automatically detected in the medical image data or in the patient-specific anatomical model of the coronary arteries and then a hemodynamic metric, such as FFR, can be computed for each of the detected lesions” [0021]; “the predicted FFR values for each treatment option can be computed by adjusting patient-specific measurements (e.g., radius measurements) for the stented lesion(s) to reflect full or partial opening due to the virtual stenting and then computed FFR values based on the adjusted patient-specific measurements using a machine learning based technique” [0034]); and
determine a clinical outcome of the patient using a cutoff for VFR, wherein the cutoff for the clinical outcome is equal to 0.83 (“With two lesions “in series” upstream/downstream of each other, the stenting options are (1) stent lesion #1, (2) stent lesion #2, (3) stent both lesions #1 and #2, and (4) don't stent any lesion. Stenting all lesions (option 3) will restore maximal blood flow. Apart from very pathologic cases, this option can be considered to be curative and, in a possible implementation, does not require extra confirmation by simulation. The evaluation of the stenting options to predict FFR values is performed to determine whether stenting only a subset of the serial lesions is sufficient to restore blood flow such that the predicted FFR values are above the threshold. For the case of two lesions, the evaluation in step 110 can automatically determine whether it is sufficient to stent only lesion #1 or only lesion #2, and if stenting sufficient restores the blood flow, whether lesion #1 or lesion #2 is the preferred lesion to stent. In a possible implementation, we have three stenting options (1)-(3), two of which need to be evaluated. Option (4) can be evaluated by assessing the FFR value after the most distal lesion (in this case downstream of lesion #2) without any stenting. If the FFR value is greater than the threshold (e.g., >0.8), then stenting is not needed for either of the lesions.” [0029]); and
providing for display an indicator of the clinical outcome (“FIGS. 4-10 illustrate predicted FFR values for a set of serial stenotic lesions (stenosis 1, stenosis 2, and stenosis 3) in the left anterior descending (LAD) artery for different stenting configurations. FIG. 4 illustrates predicted FFR values resulting from a stenting configuration in which only stenosis 1 is stented. FIG. 5 illustrates predicted FFR values resulting a stenting configuration in which only stenosis 2 is stented. FIG. 6 illustrates predicted FFR values resulting from a stenting configuration in which only stenosis 3 is stented. FIG. 7 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1 and stenosis 2 are stented. FIG. 8 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1 and stenosis 3 are stented. FIG. 9 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 2 and stenosis 3 are stented. FIG. 10 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1, stenosis 2, and stenosis 3 are all stented. [0038]”).
As factually can be seen above, Sauer teaches all the claimed limitations including setting a cutoff VFR as 0.83 as within the realm of skilled artisan under broadest reasonable interpretation; yet, if one argues in a narrower interpretation that Sauer does not teach (which the office does not concede) virtual flow reserve and the cutoff is equal to 0.83, the below reference are brought in to provide compact prosecution to show the narrow interpretation.
However, in the same field of endeavor, Rai also teaches FFR cut-off values. Measuring fractional flow reserve (FFR) in percutaneous coronary intervention (PCI) has predictive value for PCI outcome. We decided to examine the utility of pre- and post-stenting FFR as a predictor of 6-month stent restenosis as well as MACE (major adverse cardiac events). Pre- and post-stenting FFR values were measured for 60 PCI patients. Within 6 months after stenting, all patients were followed for assessment of cardiac MACE including myocardial infarction, unstable angina, or positive exercise test. Stent restenosis was also assessed. Cut-off values for pre- and post-stenting FFR measurements were considered respectively as 0.65 and 0.92. Stent restenosis was detected in 4 patients (6.6%). All 4 patients (100%) with restenosis had pre-stenting FFR of < 0.65, while only 26 of 56 patients without restenosis (46.4%) had pre-stenting FFR value of < 0.65 (P = 0.039). Mean pre-stenting FFR in patients with restenosis was significantly lower than in those without restenosis (0.25 ± 0.01 vs. 0.53 ± 0.03, P = 0.022). Although stent restenosis was higher in patients with post-stenting FFR of < 0.92 (2 cases, 9.5%) than in those with FFR value of ≥ 0.92 (2 cases, 5.1%), the difference was not statistically (P = 0.510) (Abst).
It would have been obvious to an ordinary skilled in the art before the invention was made to modify the method and/or device of the modified combination of reference(s) as outlined above with setting the FFR cutoff value to equal to 0.83 as taught by Rai because it leads to the high diagnostic accuracy of FFR in clinical setting (Intro of Rai).
Further, also in the same field of endeavor, Schmitt teaches cardiac data is processed by a processing unit comprising a first fractional flow reserve (FFR) providing unit (11) for providing first FFR values being indicative of the FFR of different arteries of the living being, wherein said virtual FFR values were calculated from non-invasive imaging data of arteries of the living being; a second FFR providing unit (12) for providing FFR values measured in the arteries of the living being; a correction unit (13) configured to correct the first FFR values based on the second FFR values; and a display unit (14) configured to display at least one first FFR value and a second FFR value for a corresponding position in the coronary arteries. The first and second FFR values are displayed to a cardiologist, who can base his course of action on the simulated and corrected values (abst). Simulation methods for the FFR value is calculated on the basis of non-invasive medical imaging (such as computed tomography, NMR, PET and the like) to determine a degree of stenosis by performing FFR calculations based on reconstructed arterial information. This ‘virtual FFR value’ used as input for a cardiologist to determine a further course of action [0003]. In FIG. 3a a 3D model of an arterial tree segment is shown with first (simulated) FFR values for 5 positions in the arterial tree (indicated by the acronym SIM and the FFR value). When an FFR value is higher than a critical value (in this case FFR>0.8) it is indicated by the word ‘OK’. In case an FFR value is critical (in this case FFR<=0.8) a warning sign is shown. Alternatively this could be indicated differently, e.g. by flashing the critical values or by color coding in two or more colors, such as red for critical FFR, green for non-critical FFR and optionally orange for borderline cases (e.g. 0.8<FFR 0.85). In FIG. 3a the simulated FFR values show that there is one critical FFR value at the fourth position from the top [0033].
It would have been obvious to an ordinary skilled in the art before the invention was made to modify the method and/or device of the modified combination of reference(s) as outlined above with setting a cutoff value for virtual FFR which is a design choice for a practitioner to set a cautionary measure to determine when an action should be taken as taught by Schmitt because it would therefore be desirable to reduce the time needed for diagnosis or treatment ([0004] of Schmitt).
Regarding claim 8, Sauer teaches wherein the means for displaying the indicator of the clinical outcome is a monitor, a tablet, a mobile phone, an e-mail, an electronic document, a printed document, or any combination thereof (“output and displayed, for example on a display screen of the computer system” [0019]).
Regarding claim 9, Sauer teaches wherein the indicator is text, a number, a symbol, a color, a picture, or any combination thereof (“FIGS. 4-10 illustrate predicted FFR values for a set of serial stenotic lesions (stenosis 1, stenosis 2, and stenosis 3) in the left anterior descending (LAD) artery for different stenting configurations. FIG. 4 illustrates predicted FFR values resulting from a stenting configuration in which only stenosis 1 is stented. FIG. 5 illustrates predicted FFR values resulting a stenting configuration in which only stenosis 2 is stented. FIG. 6 illustrates predicted FFR values resulting from a stenting configuration in which only stenosis 3 is stented. FIG. 7 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1 and stenosis 2 are stented. FIG. 8 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1 and stenosis 3 are stented. FIG. 9 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 2 and stenosis 3 are stented. FIG. 10 illustrates predicted FFR values resulting from a stenting configuration in which stenosis 1, stenosis 2, and stenosis 3 are all stented. [0038]”).
Regarding claims 12 and 13, Sauer teaches wherein the treated blood is a vessel coronary artery, a carotid artery, a femoral artery, an iliac artery, a renal artery, an abdominal aortic artery, a vein, or any combinations thereof (“treatment planning of arterial stenoses is disclosed. A set of stenotic lesions is identified in a patient's coronary arteries from medical image data of the patient” abst).
Response to Arguments
Applicant's arguments have been fully considered but they are not persuasive at least for the following reasons;
Regarding the rejection of claims under 35 USC 101, the applicant argues the following;
With regard to claim 1, it recites "receiving, by one or more processors, blood vessel image data collected from the treated blood vessel in a patient" and based on this image data, a determination of VFR values and clinical determinations using the VFR values can be performed. Applicant submits that it is not practically feasible for an individual to determine the recited VFR values based on image data. In particular, claim 1 recites a determination of clinical outcome that is based on a cutoff VFR value of 0.83. As disclosed in paragraphs [0154]-[0161] of the specification for the current application, a treated vessel may continue to be at risk for a poor clinical outcome, whereby additional treatments may be needed. The current disclosure provides for a system in which specific VFR values can be determined using image data, and a clinical outcome determination can be provided to the physician based on the specific VFR values.
Applicant submits that it is not practical for a physician to view image data and to be able to determine, using the image data, that a cutoff VFR value of 0.83 has been established within a patient. Accordingly, the recited features of claim 1 go beyond a mere abstract idea, as claim 1 instead constitutes a technical and practical improvement of patient imaging analysis that cannot be realized merely by performing a mental process. For at least these reasons, Applicant submits that claim 1 recites more than merely an abstract idea, and constitutes patentable subject matter.
Similar arguments can also be made for claim 7. Accordingly, Applicant submits that each of the pending claims recite patentable subject matter.
Contrary to the applicant’s assertion, claims still recite abstract idea as "calculating... a virtual flow reserve" and "determining a clinical outcome" which is still a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. Other than the recitation of generic computer components (“processors”) nothing in the claim element precludes the step from practically being performed in the mind.
Further, the applicant also argues that “using the image data, that a cutoff VFR value of 0.83 has been established within a patient. Accordingly, the recited features of claim 1 go beyond a mere abstract idea, as claim 1 instead constitutes a technical and practical improvement of patient imaging analysis that cannot be realized merely by performing a mental process.” However, which are all generic component that is used for mere data gathering and merely making a decision based on the data and merely setting a value to it which are examples of activities that courts have found to be insignificant extra-solution activity. These components are widely practiced and commonly known with no specificity which courts have found to be insignificant extra-solution activity.
Therefore, under its broadest reasonable interpretation, claims cover performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Judicial exception is not integrated into a practical application since the claim only recites additional element generic computer components (“processors”).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Therefore, the claims are not patent eligible.
Applicant’s arguments regarding the prior art rejections have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SERKAN AKAR whose telephone number is (571)270-5338. The examiner can normally be reached 9am-5pm M-F.
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/SERKAN AKAR/ Primary Examiner, Art Unit 3797
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