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 .
DETAILED ACTION
In the Amendment dated 19 December 2024, the following occurred:
Claims 4, 8, 14, 20, 24, and 25 were amended.
Claims 5, 6, 9, 15, 17, 19, 21, 26-30, 32, and 33 were cancelled.
Claims 1-4, 7, 8, 10-14, 16, 18, 20, 22-25, and 31 are pending.
Priority
This application claims priority to Patent Application No. PCT/US2023/026661 dated 30 June 2022.
Information Disclosure Statement
The Information Disclosure Statement (IDS) submitted on 19 December 2024 is in compliance with the provisions of 37 CFR 1.97 and has been fully considered by the Examiner.
Specification
The title of the invention contains a typo. A fixed title is required.
The following title is suggested: Automated Arthroplasty Planning with Machine Learning.
Claim Objections
Claims 12 and 16 are objected to because of the following informalities:
In claim 1, line 9, “the patient,” should read, “a patient.”
In claim 12, line 1, “the automated planning software,” should read, “the planning software.”
In claim 16, line 1-2, “wherein GUI further comprising at least one of additional window of view options window,” should read, “wherein the GUI further comprises at least one additional window such as a view options window.”
Appropriate corrections are required.
Subject Matter Free of Art
Claims 1-4, 7, 8, 10-14, 16, 18, 20, 22-25, and 31 include subject matter that is free of prior art. The cited prior art of record fails to expressly teach or suggest, either alone or in combination, the features found within independent claims 1, 23, and 31. In particular, the cited prior art fails to expressly teach or suggest the combination of:
Claims 1 and 23:
receive a bone image and display the bone image on the GUI;
receive, via the GUI, a selection of a planning model corresponding to experience of a first historical user, the planning model based on recognized patterns in a collection of planned cases of the first historical user;
analyze the bone image of the patient to determine a set of characteristics of the bone image;
compare the set of characteristics of the bone image to bone characteristics of the collection of planned cases; and
generate a surgical plan comprising implant positioning data defined with respect to the bone image based on the set of characteristics of the bone image and the recognized patterns of the planning model corresponding to experience of the first historical user.
The closest prior art is:
Metcalfe et al. (U.S. 2023/0080515) teaches receiving a bone image and displaying the bone image on a GUI, analyzing the bone image to determine a set of characteristics, comparing the set of characteristics to bone characteristics of historical cases, and generating a surgical plan comprising implant positioning data. However, Metcalfe fails to teach receiving a selection of a planning model through a GUI.
Avisar et al. (U.S. 2021/0401501) teaches an artificial intelligence surgical planning system configured to receive as input historical surgical procedure data relating to a plurality of surgical procedures previously performed for a plurality of patients. However, the model of Avisar is not based on recognized patterns in a collection of planned cases of a historical user.
Claim 31:
The prior art of record fails to teach that two separate planning models are generated by the same machine learning model using historical planning data from two different historical users of the planning system and the user selects from the two models, which is then executed using a bone image as input.
The closest prior art is:
McGuan et al. (U.S. 2022/0125515) teaches creating a model from historical user data of the user or another user. However, McGuan fails to teach that two separate planning models are generated by the same machine learning model using historical planning data from two different historical users of the planning system and a user selects from the two models, which is then executed using a bone image as input.
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 31 is 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 31 does not include a computer in the body of the claim, and thus it is unclear whether a computer is performing all of the recited steps. For examination purposes, it is interpreted that a computer performs the steps.
Claim 31 recites a “computerized method” without any recitation in the body of each of the claims describing which step is implemented by a computer or how the computer may be involved. Each of the limitations purely pertain to data manipulation without describing whether a computer may be involved in any particular step or how it may be involved. See, e.g., Ex Parte Langemyr, Appeal No. 2008-1495 at Pg. 20, 2008 Pat App. LEXIS 13 (B.P.A.I. May 28, 2008) (finding that nominal recitation of computer-implementation in the preamble is insufficient to tie the particular steps of the method to the computer). Accordingly, it is unclear where and to what extent the computer-implementation described in the preamble may take place within the body of the claim. The Examiner suggests reciting “wherein each of the following steps are performed by the computer” or similar language and interest the claim such that all the sets are performed by a computer.
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 1-4, 7, 8, 10-14, 16, 18, 20, 22-25, and 31 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1, 23, and 31 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
The claims recite systems and a method for determining personalized risk assessments for positioning an implant image relative to a bone image, and therefore meet step 1.
Step 2A1
The limitations of (Claim 1) receiv[ing] a bone image and display[ing] the bone image…; receiv[ing]… a selection of a planning model corresponding to experience of a first historical user, the planning model based on recognized patterns in a collection of planned cases of the first historical user; analyz[ing] the bone image of the patient to determine a set of characteristics of the bone image; compar[ing] the set of characteristics of the bone image to bone characteristics of the collection of planned cases; and generat[ing] a surgical plan comprising implant positioning data defined with respect to the bone image based on the set of characteristics of the bone image and the recognized patterns of the planning model corresponding to experience of the first historical user, as drafted, is a process that, under the broadest reasonable interpretation, falls in the grouping of certain methods of organizing human activity (i.e., managing personal behavior including following rules or instructions).
The limitations of (Claim 23) receiv[ing] a bone image; receiv[ing] a selection of a planning model corresponding to experience of a first historical user, the planning model based on recognized patterns in a collection of planned cases of the first historical user; analyz[ing] the bone image to determine a set of characteristics of the bone image; compar[ing] the set of characteristics of the bone image to bone characteristics of the collection of planned cases; and generat[ing] a surgical plan comprising position and orientation (POSE) data for a planned POSE of an implant with respect to a bone based on the set of characteristics of the bone image and the recognized patterns in the planning model, as drafted, is a process that, under the broadest reasonable interpretation, falls in the grouping of certain methods of organizing human activity (i.e., managing personal behavior including following rules or instructions).
The limitations of (Claim 31) providing a first planning model and a second planning model, wherein the first planning model is generated… using first historical planning data from a first historical user and the second planning model is generated… using second historical planning data from a second historical user; receiving a selection of the first planning model or the second planning model; and executing the selected first planning model or second planning model with an input comprising a bone image to automatically define implant positioning data with respect to the bone image, as drafted, is a process that, under the broadest reasonable interpretation, falls in the grouping of certain methods of organizing human activity (i.e., managing personal behavior including following rules or instructions).
That is, other than reciting systems and a method implemented by a computer, the claimed invention amounts to managing personal behavior or interaction between people. The Examiner notes that certain “method[s] of organizing human activity” includes a person’s interaction with a computer (see MPEP 2106.04(a)(2)(II)). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or interactions between people (i.e., rules or instructions for a person or persons to follow) but for the recitation of generic computer components, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Step 2A2
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional element of a computer comprising a processor potentially having a graphical user interface (claims 1, 23, and 31) that implements the identified abstract idea. The computing elements are not exclusively described by the applicant and are recited at a high-level of generality (see, e.g., Para. 0056) such that they amount to no more than mere instructions to apply the exception using generic computer components. See MPEP 2106.05(f). Accordingly, 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.
Claim 31 and dependent Claim 8 (which depends from Claim 1) further recite the additional element of a machine learning model that is utilized to generate models or recognize patterns in the planned cases. These represent mere instructions to implement the abstract idea on a generic computer. Implementing an abstract idea using a generic computer or components thereof does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. See, e.g., Recentive Analytics, Inc. v. Fox Corp., No. 2023-2437 at 10 (Fed. Cir. April 18, 2025) (finding that claims that do no more than apply established methods of machine learning to a new data environment are ineligible). Alternatively, or in addition, the implementation of machine learning to the data merely confines the use of the abstract idea (i.e., the trained models) to a particular technological environment or field of use (the noted types of ML) and thus fails to add an inventive concept to the claims. Accordingly, 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.
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 integration of the abstract idea into a practical application, the additional element of using a computer to perform the noted steps amounts 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 (“significantly more”).
As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using the trained machine learning model to generate models or recognize patterns in the planned cases was found to represent mere instructions to implement the abstract idea on a generic computer and/or confine the use of the abstract idea (i.e., the trained model) to a particular technological environment or field of use (the noted types of ML). This has been re-evaluated under the “significantly more” analysis and determined to be insufficient to provide significantly more. MPEP 2106.05(I) indicates that mere instructions to implement the abstract idea on a generic computer and/or confining the use of the abstract idea to a particular technological environment or field of use cannot provide significantly more. See also Recentive Analytics, Inc. v. Fox Corp., No. 2023-2437 at 17 (Fed. Cir. April 18, 2025) (finding that applying machine learning to an abstract idea does not transform a claim into something significantly more). Accordingly, even in combination, these additional elements do not provide significantly more. As such, these claims are not patent eligible.
Claims 2-4, 7, 8, 10-14, 16, 18, 20, 22, 24, and 25 are similarly rejected because they either further define/narrow the abstract idea and/or do not further limit the claim to a practical application or provide an inventive concept such that the claims are subject matter eligible even when considered individually or as an ordered combination.
Claim 2 merely describes the implant positioning data and the planning software, which further defines the abstract idea.
Claims 3, 4, and 25 merely describe the planning software, which further defines the abstract idea.
Claim 25 further recites the additional element of a plurality of planning models, which is analyzed in the same manner as the first and second planning models in Step 2B.
Claims 7 and 8 merely describe generating the planning model, which further defines the abstract idea.
Claims 7 and 8 further recite the additional element of a training computer, which is analyzed in the same manner as the computer in Step 2B.
Claim 10 merely describes receiving a selection, comparing the set of characteristics, and generating a second surgical plan, which further defines the abstract idea.
Claim 11 merely describes the second implant positioning data and the planning software, which further defines the abstract idea.
Claim 12 merely describes displaying the surgical plans, which further defines the abstract idea.
Claims 13, 16, and 18 merely describe the GUI, which further defines the abstract idea.
Claim 14 merely describes the 3-D view window, which further defines the abstract idea.
Claims 20 and 22 merely describe the implant library window, which further defines the abstract idea.
Claim 24 merely describes the implant positioning data, which further defines the abstract idea.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Metcalfe et al. (U.S. 2024/0058067) discloses bone estimation techniques for surgical planning.
Gaborit et al. (U.S. 2023/0027978) discloses machine-learned models in support of surgical procedures.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CAMRYN B LEWIS whose telephone number is (703)756-1807. The examiner can normally be reached Monday - Friday, 11:00 am - 8:00 pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert W Morgan can be reached on 571-272-6773. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CAMRYN B LEWIS/
Examiner, Art Unit 3683
/JASON S TIEDEMAN/Primary Examiner, Art Unit 3683
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