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 .
Election/Restrictions
The Applicant’s election without traverse of Group I, directed to Claims 1-6, in the response filed on 08 June 2026 is acknowledged.
Claims 7-20, directed to the inventions of Group II and III, have been cancelled in the response.
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 1-6 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Claims 1-6 recite a computer system (machine) which is within the four statutory categories. Claims 1-6 are directed to an abstract idea as described below.
Step 2A, Prong One:
Claim 1 recites in part:
A computer system, comprising:
….[a] processor to perform a method of determining a condition of a tissue of a patient, the method comprising:
determining, using a first trained statistical classifier, a first value indicative of a risk of injury of the tissue from a first magnetic resonance image depicting a tissue;
determining, using a second trained statistical classifier, a second value indicative of a risk of injury of the tissue from a second magnetic resonance image depicting the tissue and surrounding anatomy; and
determining a risk of injury score for the patient using the first value and the second value.
The limitations of “determining, using a first trained statistical classifier, a first value”, “determining, using a second trained statistical classifier, a second value” and “determining a risk of injury score for the patient”, as drafted, under their broadest reasonable interpretation, are merely a mental process than can be performed mentally by a person by viewing images data, because these are steps are akin to having a doctor or other human actor performing a medical diagnosis of a patient and mathematically evaluating sensed data. Therefore, these steps may be performed mentally by a human actor to calculate values for a diagnosis. If claim limitations, under their broadest reasonable interpretation covers the performance of the limitations within the human mind or by a human using a pen and paper, then it falls within “mental processes” grouping of abstract ideas. See MPEP 2106.04(a)(2)(III).
Furthermore, these limitations, under their broadest reasonable interpretations, recite performing mathematical calculations (processing and mathematically analyzing the image data) and forming mathematical relationships (a relationship/correlation for prediction determining values and predicting injury score), and as such, the claims recite limitations which may also fall within the 'mathematical concepts' grouping of abstract ideas. See MPEP 2106.4(a)(2). ‘‘[A] scientific truth, or the mathematical expression of it, is not patentable invention[.]’’ See, e.g., Benson, 409 U.S. at 65, 175 USPQ2d at 674; Flook, 437 U.S. at 589, 198 USPQ2d at 197; Mackay Radio & Telegraph Co. v. Radio Corp. of Am., 306 U.S. 86, 94, 40 USPQ 199, 202 (1939).
Claims 2-6 depend from Claim 1, and merely recite additional processing and analyzing steps relating to the image data, and therefore are also considered to cover concepts that are performing mathematical calculations and forming mathematical relationships, and may be considered mental processes as defined in MPEP 2106.04(a) and MPEP 2106.04(b).
Step 2A, Prong Two:
The judicial exception is not integrated into a practical application.
These elements merely use generic computer components to evaluate sensed image data and perform calculations based on the data. It is noted that no direct therapy or treatment initiation is explicitly claimed.
Recording magnetic resonance data/images sensed from a mammal is a well-known and conventional technique that uses some type of known generic imaging device to record data from a mammal. This analysis includes merely acquiring MRI image data from a patient using a MRI component and is considered an insignificant pre-solution activity of gathering data for use in a claimed process (see MPEP 2106.05(g)). This pre-solution activity of data gathering and then performing calculations/analyses is well-known and typical in the field of medical sensing and computing technology.
Additionally, processing with a machine learning model is considered as a well-known technique in the field, with statistical classifiers/neural networks being trained to process information and identify/classify certain traits being a concept used to process received data and other physiological signals. Further, Claim 1 comprises steps of processing the data to estimate a health index (“injury score”). This limitation amount to mere instructions to apply an exception (MPEP 2106.05(f)), wherein the exception is a natural phenomena where a correlation between data analysis diagnosis exists and a neural network/machine modeling is simply added as a computer function/trained set of instructions to “apply”/find the exception. As found in MPEP 2106.05(f), “the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words “apply it”.”
Claims 2-6 depend from Claim 1, and merely recite additional processing and analyzing steps/details, and therefore are also considered to not be integrated into a practical application for the same reasons as Claim 1. Therefore, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
By the above reasoning, none of the above amount to integrating the mathematical concepts or mental processes into practical application.
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As discussed above with respect to the integration of the judicial exception into a practical application (Step 2A - Prong Two), the additional elements in the claim amount to no more than insignificant extra solution activity and mere instructions to apply the exception using generic computer/processing components and sensors. The same analysis applies here in 2B and does not provide an inventive concept. The data gathering of Claim 1 amounts to no more than mere pre-solution activity of data processing, and this pre-solution activity of processing data using known sensors is well-understood, routine, and conventional in the field of computing and medical technology.
Furthermore, the only structural elements provided in the claims relate to computer modeling/analyzing. In Claim 1, the only structural elements include, “a computer system, comprising: a computer processor; and a non-transitory computer-readable storage medium storing processor-executable instruction that, when executed by the processor, cause the processor to perform a method”. These are well-understood, routine, and conventional systems in the field of computing and medical technology. For example, see Dam et al. (US Publication No. 2013/0204115), Imhauser et al. (US Publication No. 2017/0162978), and Theodore et al. (US Publication No. 2018/0214180) described in detail below.
These additional elements are recited at a high-level of generality (i.e. most generic computer and medical systems would be known to have these components for general computation, sensing/imaging, processing, and output of sensed data), and only provide conventional, well-known sensing and computing functions that do not add meaningful limits to practicing the abstract idea.
Dependent Claims 2-6 fail to recite additional significant structure. These dependent claims do not add significantly more to the judicial exceptions and merely recite additional analysis/mathematical steps.
Therefore, the claims are not patent eligible.
Therefore, Claims 1-6 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 102
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 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 2, and 5 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Dam et al. (US Publication No. 2013/0204115).
Regarding Claim 1, Dam et al. discloses a computer system, comprising:
a computer processor (computer systems executing stored algorithms, Paragraph 0005, 0019, 0034, 0061; Claim 1); and a non-transitory computer-readable storage medium storing processor-executable instruction that, when executed by the processor, cause the processor to perform a method of determining a condition of a tissue of a patient (determination of level of or risk of disease/injury to knee joint, Paragraph 0005, 0019, 0034, 0061; Claim 1), the method comprising:
determining, using a first trained statistical classifier (multiple classifiers, Paragraph 0056, 0076, 0080), a first value indicative of a risk of injury of the tissue from a first magnetic resonance image depicting a tissue (extracting multiple image biomarkers from MRI image; Paragraph 0018-0019, 0034, 0049-0054, 0087; determining level of or risk of disease/injury to knee joint Paragraph 0021-0026, 0032-0034, 0056, 0100; Claims 1-3, 11);
determining, using a second trained statistical classifier (multiple classifiers, Paragraph 0056, 0076, 0080), a second value indicative of a risk of injury of the tissue from a second magnetic resonance image depicting the tissue and surrounding anatomy (MRI images of knee joint and surrounding tissue/bone, see Figs. 1A-1C depicting connective tissue of knee joint; Paragraph 0014-0015, 0017-0018, 0033; determining level of or risk of disease/injury to knee joint, Paragraph 0021-0026, 0032-0034, 0056, 0100; Claims 1-3, 11); and
determining a risk of injury score for the patient using the first value and the second value (comparison of first and second images, Claim 13, Paragraph 0021, 0022, 0025, 0019; overall determining level of or risk of disease/injury to knee joint by calculation of multiple ‘score’/indices based on images, Paragraph 0021-0026, 0032-0034, 0056, 0100; Claims 1-3, 11; see Table 1).
Regarding Claim 2, Dam et al. discloses a system further wherein the first magnetic resonance image depicting the tissue comprises a magnetic resonance image (Paragraph 0011, 0019) depicting a connective tissue of a knee of the patient (see Figs. 1A-1C depicting connective tissue of knee joint; Paragraph 0014-0015, 0017-0018, 0033).
Regarding Claim 5, Dam et al. discloses a system further wherein the second trained statistical classifier uses patterns (patterns determined by classifiers, Paragraph 0019, 0034, 0052, 0054, 0087, 0106) indicative of a risk for injury to determine the second value (determining level of or risk of disease/injury to knee joint, Paragraph 0021-0026, 0032-0034, 0056, 0100; Claims 1-3, 11).
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.
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 3 and 4 are rejected under 35 U.S.C. 103 as being unpatentable over Dam et al. (US Publication No. 2013/0204115) in view of Imhauser et al. (US Publication No. 2017/0162978).
Regarding Claims 3 and 4, Dam et al. discloses a system further wherein the first magnetic resonance image depicts connective tissue of a knee joint (see Figs. 1A-1C depicting connective tissue of knee joint, e.g. “ROI” – region of interest; Paragraph 0014-0015, 0017-0018, 0033), and wherein the second magnetic resonance image depicting the tissue and the surrounding anatomy comprises a magnetic resonance image depicting the knee of the patient (see Figs. 1A-1C depicting connective tissue of knee joint; Paragraph 0014-0015, 0017-0018, 0033), further wherein the first magnetic resonance image is generated from the second magnetic resonance image (extracting multiple image biomarkers from MRI image; Paragraph 0018-0019, 0034, 0049-0054, 0087). However, Dam et al. does not explicitly disclose wherein the first image comprises a magnetic resonance image depicting an Anterior Cruciate Ligament (ACL).
Imhauser et al. teaches a computer system configured to perform a method of determining a condition of a tissue of a patient (Abstract) including analyzing magnetic resonance images (MRIs; Paragraph 0068, 0083, 0086, 0222, 0261) depicting an Anterior Cruciate Ligament (ACL) and surrounding knee joint tissue (Paragraph 0012, 0068, 0222, 0225, 0228, 0263; Claim 12) determining a risk of injury score for the patient by analyzing the images (Abstract; Paragraph 0056-0059, 0105-0108).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include images depicting an Anterior Cruciate Ligament (ACL), as taught by Imhauser et al., in the system disclosed by Dam et al., in order to “to develop an injury prevention plan or protocol” (Imhauser et al., Paragraph 0108) and “to develop a treatment plan for physical therapy of the joint” (Imhauser et al., Paragraph 0107) and specifically for the ACL and other connective tissues of the knee joint (see Imhauser et al., Paragraph 0104).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Dam et al. (US Publication No. 2013/0204115) in view of Theodore et al. (US Publication No. 2018/0214180).
Regarding Claim 6, Dam et al. discloses a system further comprising determining a risk of injury score for the patient using the first value and the second value (comparison of first and second images, Claim 13, Paragraph 0021, 0022, 0025, 0019; overall determining level of or risk of disease/injury to knee joint by calculation of multiple ‘score’/indices, Paragraph 0021-0026, 0032-0034, 0056, 0100; Claims 1-3, 11; see Table 1), including risk of developing injury/disease in the future (risk of developing injury/disease, Paragraph 0022, 0025).
However, Dam et al. does not explicitly disclose wherein the risk of injury is a risk of reinjury at a time after a ligament reconstruction surgery. Theodore et al. discloses teaches a computer system configured to perform a method of determining a condition of a tissue of a patient (Abstract; Paragraph 0057) including analyzing magnetic resonance images (MRIs; Paragraph 0024, 0059, 0067) depicting knee joint tissue (Paragraph 0030, 0084, 0068, 0105; Claims 1, 19) determining a risk of injury score for the patient by analyzing the images, wherein the risk of injury is a risk of reinjury at a time after a ligament reconstruction surgery (post-operative characteristic, Paragraph 0034, 0057, 0084, 0088, 0098, 0104)
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include a risk of reinjury at a time after a ligament reconstruction surgery, as taught by Theodore et al., in the system disclosed by Dam et al., since “determining a predicted characteristic of the joint after
the surgery based on a spatial parameter of the surgery and based on the mechanical property of the one or more ligaments; and generating an output signal indicative of the predicted characteristic to assist the surgery” (Theodore et al., Paragraph 0009) will lead to advantages “because the surgeon can plan the surgery more accurately, which also means the patient outcome will be improved. As a result, treated patients have increased quality of life as they are able to perform more activities due to the improved surgery outcome.” (Theodore et al., Paragraph 0010)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PAMELA M BAYS whose telephone number is (571)270-7852. The examiner can normally be reached 10:00am - 6:00pm EST.
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/PAMELA M. BAYS/Primary Examiner, Art Unit 3796
