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.
Claims 1–20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without a practical application or significantly more.
Regarding claims 1, 8 and 15, these claims recite the following limitations which are found to be abstract ideas not reciting a practical application or significantly more, with claim 1 being exemplary:
determining, by the information handling system, a risk factor for the patient based on the 2-D perfusion angiography scan data and the Wound Ischemia foot Infection (WIfI) score using a machine learning algorithm (abstract idea as a mental process as a human mind, for example, a medical doctor, is capable of determining risk factors based on specific diagnostic data presented to them, including 2-D perfusion angiography and a WIfI score).
This judicial exception is not integrated into a practical application for the following reasons. Claims 1, 8 and 15 all recite the additional elements of the steps of “receiving, by an information handling system, a Wound Ischemia foot Infection (WIfI) score for a patient; receiving, by the information handling system, 2-D perfusion angiography scan data for the patient,” which while not necessarily being abstract ideas, are insignificant extra solution activity since they are merely data gathering (see MPEP §2106.05(g)). Moreover, these elements amount to receiving and outputting data in a computer based system and are well understood, routine, conventional activity. See MPEP 2106.05(d), subsection II.
Claims 1, 8 and 15 further recite additional elements: “an information handling system” and “machine learning algorithm.” Further, claim 9 is directed towards a system comprising a memory, and a processor, and claim 15 is directed towards a non-transitory computer-readable media. While an information handling system, and machine learning algorithm from all the claims, non-transitory computer-readable media of claim 15, and the processor and memory of claim 8 are additional elements, they are not sufficient to recite a practical application of the abstract ideas recited in claims 1, 8 and 15 as they amount to mere generic computer elements and thus amount to no more than a recitation of the words "apply it" (or an equivalent) or are no more than mere instructions to implement an abstract idea or other exception on a computer. see MPEP §2106.05(f).
Further, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because when considered separately and in combination, the above recited additional elements from claims 1, 8 and 15 do not add significantly more (also known as an “inventive concept”) to the exception. Rather, the additional elements disclosed above perform well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d).
Therefore, independent claims 1, 8 and 15 are directed towards an abstract idea without a practical application or significantly more.
Regarding claims 2, 9 and 16, reciting “wherein the step of determining, by the information handling system, the risk factor for the patient is also based on the healthcare record,” this limitation is merely directed towards details of the data that is part of the abstract idea from the independent claims that these claims depend from, and thus are merely an extension of the abstract idea, without providing a practical application or significantly more.
Further these claims all recite the additional elements of the steps of “receiving, by the information handling system, a healthcare record for the patient,” which while not necessarily being abstract ideas, are insignificant extra solution activity since they are merely data gathering (see MPEP §2106.05(g)). Moreover, these elements amount to receiving data in a computer based system and are well understood, routine, conventional activity. See MPEP 2106.05(d), subsection II. Accordingly, claims 2, 9 and 16 also do not recite a practical application or significantly more, and are also subject matter ineligible as being directed towards an abstract idea.
Regarding claims 3, 5–6, 10, 12–13, 17 and 19, the limitations recited in these claims are merely directed towards details of the data that is part of the abstract idea from the independent claims that these claims depend from, and thus are merely an extension of the abstract idea, without providing a practical application or significantly more.
Regarding claims 4, 7, 11, 14, 18 and 20, the limitations recited in these claims are directed towards abstract ideas as a mental process as a human mind, such as a doctor, is capable of making determinations of a risk factor including determining “a rate to measure baseline” (claims 4, 11 and 18) or a risk of a major amputation (claims 7, 14 and 20), and therefore, these limitations are mere abstract ideas. These claims do not recite any additional elements beyond those recited in the independent claims, and thus, also do not recite a practical application or significantly more.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 8 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Schobel et al., US Patent Application Publication No. US 2021/0327540 A1 (herein “Schobel”) in view of Mills et al., “The Society for Vascular Surgery Lower Extremity Threatened Limb Classification System: Risk stratification based on Wound, Ischemia, and foot Infection (WIfI), Journal of Vascular Surgery, Volume 59, Issue 1, 2014, pages 220-234 (herein “Mills”), further in view of Braun et al., “Early quantitative evaluation of indocyanine green angiography in patients with critical limb ischemia,” J Vasc Surg 2013, volume 57, issue 5, May 2013, pages 1213-1218 (herein “Braun”).
Regarding claims 1, 8 and 15, with deficiencies of Schobel noted in square brackets [], and with substantial differences between the claims noted in curly brackets {}, and with claim 1 as exemplary, Schobel teaches {a method, - claim 1 / an information handling system, comprising: a memory; and a processor coupled to the memory, in which the processor is configured to perform steps – claim 8 / a computer-program product comprising: a non-transitory computer readable medium comprising instructions for causing an information handling system to perform steps – claim 15}comprising (Schobel Abstract, ¶¶ 148–149, 154–156, method and systems for predicting if a subject has an increased risk of having or developing one or more clinical outcomes, the disclosure being embodied as a system, method or computer program product embodied in a computer readable medium such as a RAM that is non-transitory, the system including a processor and memory for executing instructions):
receiving, by an information handling system, a [Wound Ischemia foot Infection (WIfI)] score for a patient (Schobel ¶¶ 9, 17, and 20, system for predicting a clinical outcome by receiving a value of at least one clinical parameter of a subject (patient), the clinical parameter being an injury severity score);
receiving, by the information handling system, [2-D perfusion] angiography scan data for the patient (Schobel ¶¶ 88–89, 93, data input to (thus received by) the machine learning engine, including diagnostic imaging data such as an angiography, used for a evaluating a patient along with the patient’s clinical parameters, and thus for “the patient”);
determining, by the information handling system, a risk factor for the patient based on the [2-D perfusion] angiography scan data and the [Wound Ischemia foot Infection (WIfI)] score using a machine learning algorithm (Schobel ¶¶107, 109, 117, fig. 1, prediction engine as the last processing step in the process of a machine learning engine, thus downstream of and thus based on the earlier steps receiving the score data and diagnostic imaging data, outputs predictions of one or more clinical outcomes, including risk for one or more clinical outcomes (risk factor)).
While Schobel teaches receiving an injury severity score, which is a generic score of which a Wound Ischemia foot Infection (WIfI) score is a species score, nonetheless, Schobel does not explicitly teach a Wound Ischemia foot Infection (WIfI) score.
Further, while Schobel teaches receiving diagnostic imaging data including angiography, Schobel does not explicitly teach 2-D perfusion angiography scan data.
Mills teaches a Wound Ischemia foot Infection (WIfI) score (Mills page 226, table II, teaching the elements involved in computing a Wound Ischemia foot Infection score, where the Abstract section discloses that the WIfI score is used to determine risk stratification (risk factor)).
Mills also refers to the Braun reference on page 225, in the Ischemia Grades section, disclosing that an ischemia parameter is used to determine risk for amputation, and that ischemia parameters can be obtained from “quantitative indocyanine green angiography,” with a citation number 70, to the Braun reference. Therefore, while Mills does teach that a “quantitative indocyanine green angiography” is used for determining risk factor, Mills does not explicitly teach that the “quantitative indocyanine green angiography” is a “2-D perfusion angiography.”
Braun teaches 2-D perfusion angiography (Braun page 1214, left column up to the METHODS section teaches that indocyanine green angiography is an image of regional perfusion, and thus is a 2-D perfusion type of angiography, where page 1213 teaches that the detected perfusion from the disclosed angiography is used to determine the risk factor of critical limb ischemia).
Therefore, in view of the teachings of Schobel and Mills together as a whole, it would have been obvious to a person having ordinary skill in the art (herein “PHOSITA”) before the effective filing date of the claimed invention to have modified the injury severity score of Schobel to be specifically a WIfI score as disclosed in Mills at least because doing so would permit more meaningful analysis of outcomes for various forms of therapy in the challenging group of patients having diabetes, where over the last 40 years, there has been a dramatic rise in the incidence of diabetes mellitus. See Mills Abstract.
Further, taking the teachings of Schobel and Braun together as a whole, it would have been obvious to a PHOSITA before the effective filing date of the claimed invention to have modified the angiography of Schobel to be specifically a 2-D perfusion angiography as disclosed in Braun at least because doing so would provide rapid and quantitative information about regional foot perfusion, and therefore, would lead to proper management of patients suffering from limb ischemia. See Braun Abstract and page 1213.
Regarding claims 2, 9 and 16, with claim 2 as exemplary, Schobel teaches further comprising: receiving, by the information handling system, a healthcare record for the patient (Schobel ¶¶ 88–89, 95 , fig. 1, data input into (received by) the machine learning system including administrative health data, including gender, age, date of injury, amount of blood products administered, length of hospital stay – all of which are types of healthcare records), wherein the step of determining, by the information handling system, the risk factor for the patient is also based on the healthcare record (Schobel ¶¶107, 109, 117, fig. 1, prediction engine as the last processing step in the process of a machine learning engine, thus downstream of and thus based on the earlier steps receiving the administrative health data, outputs predictions of one or more clinical outcomes, including risk for one or more clinical outcomes (risk factor)).
Regarding claims 3, 10 and 17, with claim 3 as exemplary, Schobel teaches wherein receiving, by the information handling system, the healthcare record for the patient comprises receiving at least one of clinical conditions or classifications of the patient (Schobel ¶¶ 88–89, 95 , fig. 1, data input into (received by) the machine learning system including administrative health data, including gender, age (classifications of the patient), and severity of traumatic brain injury (clinical condition)).
Regarding claims 4, 11 and 18, while Schobel teaches determining, by the information handling system, the risk factor (Schobel ¶¶107, 109, 117, fig. 1, prediction engine as the last processing step in the process of a machine learning engine, thus downstream of and thus based on the earlier steps receiving the score data and diagnostic imaging data, outputs predictions of one or more clinical outcomes, including risk for one or more clinical outcomes (risk factor)), Schobel does not teach, but Mills teaches comprises determining at least one of a peak intensity to wound, a rate to measure baseline, a plateau at peak intensity, or a speed dissipation of a signal (Mills page 227, table II.a. key summary point 1 teaching that table II is used for the initial baseline classification of patients with ischemic wounds within the spectrum of chronic lower limb ischemia, and where table II indicates rates such as heart rate and respiratory rate, thus are rates to measure baseline).
Therefore, in view of the teachings of Schobel and Mills together as a whole, it would have been obvious to a PHOSITA before the effective filing date of the claimed invention to have modified the determining a risk factor of Schobel to include determining a baseline rate for WiFI measure as disclosed in Mills at least because doing so would permit more meaningful analysis of outcomes for various forms of therapy in the challenging group of patients having diabetes, where over the last 40 years, there has been a dramatic rise in the incidence of diabetes mellitus. See Mills Abstract.
Regarding claims 7, 14 and 20, with claim 7 as exemplary, Schobel does not explicitly teach, but Mills teaches wherein determining, by the information handling system, the risk factor for the patient comprises determining a risk of least one of an onset of Critical Limb Threating Ischemia (CLTI), a major amputation, a wound healing, or a death (Mills Abstract and page 228 “Amputation Risk According to WIfI Category” section, risk stratification based on the disclosed Wound, Ischemia and foot Infection factors, for amputation risk (major amputation)).
Therefore, in view of the teachings of Schobel and Mills together as a whole, it would have been obvious to a PHOSITA before the effective filing date of the claimed invention to have modified the determining of risk of Schobel to include amputation risk as disclosed in Mills at least because doing so would permit more meaningful analysis of outcomes for various forms of therapy in the challenging group of patients having diabetes, where over the last 40 years, there has been a dramatic rise in the incidence of diabetes mellitus. See Mills Abstract.
Claims 5–6, 12–13, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Schobel in view of Mills in view of Braun, as set forth above regarding claims 1, 8 and 15, and further in view of Sonck et al., US Patent Application Publication No. US 2024/0130674 A1 (herein “Sonck”).
Regarding claims 5, 12 and 19, with claim 5 as exemplary, Schobel in view of Braun as set forth above in the independent claims teaches the claimed wherein the 2-D perfusion angiography scan data for the patient (as noted above, Braun page 1214, left column up to the METHODS section teaches that indocyanine green angiography is an image of regional perfusion, and thus is a 2-D perfusion type of angiography, where page 1213 teaches that the detected perfusion from the disclosed angiography is used to determine the risk factor of critical limb ischemia). Schobel as modified above does not, but Sonck teaches corresponds to the patient prior to a percutaneous coronary intervention (Sonck ¶98, fig. 2, FFR data on the left before a PCI (percutaneous coronary intervention), where the FFR data on the right is after PCI, where ¶73 teaches that FFR stands for fractional flow reserve, and where ¶ 80 teaches the FFR data is obtained from a quantitative coronary angiography).
Therefore, in view of the teachings of Schobel as modified by Mills and Braun, and Sonck together as a whole, it would have been obvious to a PHOSITA before the effective filing date of the claimed invention to have modified the angiography of Schobel to be before percutaneous coronary intervention (PCI) as disclosed in Sonck at least because doing so would provide an improved assessment of coronary artery disease and more accurately determine whether a patient be better suited for treatment under PCI and those that would be better suited for treatment under coronary artery bypass grafting, thus enhancing the ability to choose the more suitable treatment for a patient. See Sonck ¶7.
Regarding claims 6 and 13, with claim 6 as exemplary, Schobel in view of Braun as set forth above in the independent claims teaches the claimed wherein the 2-D perfusion angiography scan data for the patient (as noted above, Braun page 1214, left column up to the METHODS section teaches that indocyanine green angiography is an image of regional perfusion, and thus is a 2-D perfusion type of angiography, where page 1213 teaches that the detected perfusion from the disclosed angiography is used to determine the risk factor of critical limb ischemia). Schobel as modified above does not, but Sonck teaches corresponds to the patient after a percutaneous coronary intervention (Sonck ¶98, fig. 2, FFR data on the right is after PCI, where ¶73 teaches that FFR stands for fractional flow reserve, and where ¶ 80 teaches the FFR data is obtained from a quantitative coronary angiography).
Therefore, in view of the teachings of Schobel as modified by Mills and Braun, and Sonck together as a whole, it would have been obvious to a PHOSITA before the effective filing date of the claimed invention to have modified the angiography of Schobel to be after percutaneous coronary intervention (PCI) as disclosed in Sonck at least because doing so would provide an improved assessment of coronary artery disease and more accurately determine whether a patient be better suited for treatment under PCI and those that would be better suited for treatment under coronary artery bypass grafting, thus enhancing the ability to choose the more suitable treatment for a patient. See Sonck ¶7.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Lee et al., US Patent Application Publication No. US 2020/0093382 A1, directed towards revascularization assessment by analyzing sensor data.
Perkins et al., “Predicting the Outcome of Limb Revascularization in Patients With Lower-extremity Arterial Trauma,” Annals of Surgery, Volume 272, Number 4, October 2020, Wolters Kluwe Health, Inc., directed towards a prediction model for limb revascularization considering ischaemic damage and tissue perfusion.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHELLE M KOETH whose telephone number is (571)272-5908. The examiner can normally be reached Monday-Thursday, 09:00-17:00, Friday 09:00-13:00, EDT/EST.
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MICHELLE M. KOETH
Primary Examiner
Art Unit 2671
/MICHELLE M KOETH/Primary Examiner, Art Unit 2671