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 .
Priority
This application’s status as a continuation of 17/061,221 (now US 12023102 B1) and corresponding claim of priority to provisional patent application 62/909,423 is acknowledged.
Status of the Claims
The status of the claims as of the preliminary amendment filed 11/21/2024 is as follows: Claims 1-20 are cancelled. Claims 21-34 are newly pending and have been considered below.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 11/21/2024 and 6/12/2025 are in accordance with the provisions of 37 CFR 1.97 and are considered by the Examiner.
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.
Claims 28-29 and 31 are 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 28 recites the limitation "the trained machine learning algorithm" in lines 2-3. It is unclear if this is intended to be the same machine learning algorithm introduced in parent claim 21, or if it is intended to be a separate trained machine learning algorithm. For purposes of examination, Examiner will interpret this algorithm as a trained machine learning algorithm newly introduced by the claim. Claim 29 is also rejected on this basis because it inherits the indefinite limitation due to its dependence on claim 28.
Claim 29 recites the limitation “the type and quality of bone present in the joint of the patient” in line 3. There is insufficient antecedent basis for this limitation in the claim because there is no previous introduction of a type or quality of bone present in the joint of the patient. For purposes of examination, Examiner will interpret this limitation as “a type and quality of bone present in the joint of the patient” newly introduced by the claim.
The limitation “patient data formatted in a digital imaging and communication in medicine (DICOM) format or a comparable format” in claim 31 includes a relative term which renders the claim indefinite. The term “comparable” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. For purposes of examination, Examiner will interpret “patient data formatted in a digital imaging and communication in medicine (DICOM) format or a comparable format” to include any format of patient data.
Claim Eligibility - 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 21-34 are patent eligible. When considered as a whole using the 2-step framework outlined by the 2019 PEG and MPEP 2106, each of the claims satisfy Step 1 because they are directed to a method (i.e. a process). When examining these claims under Step 2A – Prong 1, independent claim 21 is found to recite an abstract idea in the form of a mental process, e.g. steps for selecting one of the plurality of bone defect models that illustrates a state of bone defect that most closely corresponds to the joint of the patient, selecting an implant system from a plurality of available implant systems, and determining apposition for implanting the selected implant system in the patient, which are clinical judgements or determinations that a surgeon or other clinician would be capable of performing mentally or with aid of pen and paper. However, under Step 2A – Prong 2, the additional elements of receiving a three-dimensional joint model of at least a portion of the joint of the patient; receiving a plurality of collective three-dimensional joint models, each of the collective three-dimensional joint models being of at least a portion of a joint that corresponds to the joint of the patient; and applying progression parameters to each of the plurality of collective three-dimensional joint models, thereby generating, for each of the plurality of collective three-dimensional joint models, a respective plurality of bone defect models, each of the respective plurality of bone defect models illustrating a different state of bone defect; provide a practical application of the invention. These steps, when considered in the context of the claim as a whole, do not amount to mere instructions to “apply” the exception, are not merely insignificant extra-solution activity, do not merely generally link the judicial exception to a particular technological environment or field of use; rather, they describe specific methods of generating a library of computerized models of different bone defects of anatomical joints for selection and use during a surgical planning operation that provides meaningful limits on the judicial exception such that the claim as a whole is more than a mere drafting effort to monopolize the judicial exception of selecting a model from a library and selecting an implant system and position of the implant system for a patient based on the selected model. Thus, independent claim 21 is patent eligible, as are claims 22-34 depending therefrom.
Claim Rejections - 35 USC § 103
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.
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 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 21-27 and 30-34 are rejected under 35 U.S.C. 103 as being unpatentable over Schoenefeld et al. (US 20110092804 A1) in view of Anderson et al. (US 20110112808 A1) and Janna et al. (US 20220202497 A1).
Claim 21
Schoenefeld teaches a method of planning a surgical procedure to be performed on a joint of a patient (Schoenefeld abstract), the method comprising:
receiving a three-dimensional joint model of at least a portion of the joint of the patient (Schoenefeld Fig. 1, [0045], noting creation of a three-dimensional model of a patient’s bone or joint);
receiving a plurality of collective (Schoenefeld Fig. 21, [0100], noting a database of diseased/deformed bone models may be created from in-house patient data or other publicly available data (i.e. a plurality of collective joint models corresponding to a joint of the patient));
selecting one of the plurality of bone defect models that illustrates a state of bone defect that most closely corresponds to the joint of the patient, the selected one of the plurality of bone defect models corresponding to a first one of the plurality of collective three-dimensional joint models (Schoenefeld Fig. 21, [0100], noting a best-fit diseased/deformed model is selected from the database for a given patient’s data);
based at least in part on the first one of the plurality of collective three-dimensional joint models, selecting an implant system from a plurality of available implant systems (Schoenefeld Fig. 21, [0100], noting the selected best-fit bone model may be used to generate a pre-operative plan, which per [0047] can include selecting sizes and types of implants, e.g. from a plurality of off-the-shelf or semi-custom implant options as in [0055] & [0058]-[0059]); and
determining a position for implanting the selected implant system in the patient (Schoenefeld [0047], [0067]-[0072], noting the surgical plan can include orientation of various features and modifiable implant parameters like distances/lengths and angles of the implant, which are considered equivalent to a position for the implant within the patient because the size, dimensions, angles, etc. of the implant impact where the implant is physically positioned within the patient’s joint).
In summary, Schoenefeld teaches a pre-operative surgical planning method that generates a database of diseased/deformed bone models using known data and selects a best fit model to select appropriate implant features for the patient. However, this reference fails to explicitly disclose that the diseased/deformed bone models are generated by receiving a plurality of collective three-dimensional joint models and applying progression parameters to each of the plurality of collective three-dimensional joint models, and makes no mention of the selecting, selecting, and determining steps being performed using a machine learning algorithm.
However, Anderson teaches the generation of diseased/degraded joint models by applying disease progression parameters to three-dimensional models of the joint (Anderson [0001]-[0003], [0005]-[0006], [0015], [0028]-[0030], [0046]-[0047], [0052], [0061], [0098], [0120]-[0125], noting generic structural joint models from a database are customized to model the temporal influences of various factors (e.g. disease/pathology progression/wear as in [0029] & [0120]-[0125]) over time for a patient). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the unspecified diseased bone model generation method from available data of Schoenefeld to include application of progression parameters to three dimensional models as in Anderson in order to utilize a specific method of creating realistic models of physical progressions of disease, aging, physical wear, etc. in the joint for use in clinical assessment treatment option planning (as suggested by Anderson [0002] & [0046]-[0047]). The result of such a combination would include the generation of a database of diseased/deformed bone models from publicly available data as in Schoenefeld via the specific process of applying progression parameters to available 3D models as in Anderson.
Further, Janna teaches use of machine learning algorithms to perform various steps of a surgical planning operation such as identifying relevant similar patient information in a historical database and selecting an implant system and its position (Janna [0181], [0185], [0189]-[0191]). It would have been obvious to one of ordinary skill in the art, to modify the computerized surgical planning functions of selecting a matching bone model, selecting, an implant system, and determining an implant system position as in the combination to specifically be performed using a machine learning algorithm as in Janna in order to automate aspects of the surgical planning method such that a surgeon only needs to be minimally involved, thereby improving efficiency of the planning while still permitting the surgeon to have final confirmation of the surgical plan (as suggested by Janna [0191]).
Claim 22
Schoenefeld in view of Anderson and Janna teaches the method of claim 21, and the combination further teaches wherein the joint of the patient comprises at least a portion of a first bone, at least a portion of a second bone, and an interface between the at least a portion of the first bone and the at least a portion of the second bone (Schoenefeld Figs. 17 & 22A-B, showing an exemplary knee joint which consists of at least two bones interfacing at the knee joint).
Claim 23
Schoenefeld in view of Anderson and Janna teaches the method of claim 22, and the combination further teaches wherein each of the plurality of collective three- dimensional joint models comprises the at least a portion of the first bone being in one of a plurality of positions relative to the at least a portion of the second bone (Schoenefeld Figs. 22A, showing a selected best-fit bone model with a femur bone in a position relative to a tibia bone, which is one of a plurality of positions possible via known anatomical range of motion of the knee joint).
Claim 24
Schoenefeld in view of Anderson and Janna teaches the method of claim 22, and the combination further teaches wherein the joint of the patient has a bone defect (Schoenefeld [0047], noting the method is utilized for pre-surgical planning to restore a joint to a pre-injury or mechanically correct anatomy, indicating that the surgery is being undertaken on a joint of the patient with some kind of injury or defect; see also [0050], noting various bone bumps, protrusions, growths, and osteophytes (i.e. bone defects) may be removed from the joint model for planning purposes, indicating that the method may be performed for patients whose joints have one of these bone defects).
Claim 25
Schoenefeld in view of Anderson and Janna teaches the method of claim 24, and the combination further teaches wherein each of the plurality of collective three- dimensional joint models does not have a bone defect (Schoenefeld [0100], noting the diseased models are generated from in-patient or publicly available data; see also Anderson [0044], [0052], noting the models can start with generic models of typical patients, considered to include models without bone defects).
Claim 26
Note: this claim amounts to an intended use/result of the method because it does not include any positively recited claim limitations for actually performing the surgical implant procedure to place the bones of the joint in a selected position, instead merely describing the desired results permitted by using the selected implant in a “wherein” clause. Accordingly, this limitation is not patentably limiting, and will be considered to be met by the prior art teaching selection of a surgical implant for a joint because the intended purpose of any selected surgical implant for a joint is to correct the anatomy or structure of the patient’s defective joint.
Schoenefeld in view of Anderson and Janna teaches the method of claim 25, and the combination further teaches wherein when implanted in the patient, the selected implant system places the bones of the joint of the patient in a position that best matches the position of the bones of the joint of the patient prior to having the bone defect (Schoenefeld [0047], noting the surgical plan (including a selected implant) is used to obtain a healthy or as close to healthy anatomical orientation as possible after the surgical procedure).
Claim 27
Schoenefeld in view of Anderson and Janna teaches the method of claim 26, and the combination further teaches that the method can be “used for any orthopedic implant,” with a knee implant used as an exemplary embodiment (Schoenefeld [0039]). Though one of ordinary skill in the art would understand that “any orthopedic implant” would cover an implant for any musculoskeletal joint, the present combination fails to explicitly disclose wherein the selected implant system is an anatomical shoulder implant system. However, Anderson further teaches that a method of modeling musculoskeletal joints for assessing joint implants may be applied to an exemplary knee joint as well as be “applicable to other limbs and joints such as the shoulder” (Anderson [0053]). It therefore would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the selected implant system of the combination to specifically be an anatomical shoulder implant system in order to apply the orthopedic implant planning method to the shoulder joint so that shoulder implant systems may be selected and optimized for a patient (as suggested by Schoenefeld [0039] & Anderson [0053]).
Claim 30
Schoenefeld in view of Anderson and Janna teaches the method of claim 21, and the combination further teaches wherein the plurality of collective three-dimensional joint models is generated from an available collection of images and corresponding patient data (Schoenefeld [0100], noting in-house patient data and publicly available data as a basis for generating the diseased bone model database; see also Anderson [0044], [0052], [0060], noting the models can start with generic models of typical patients constructed from images and other patient data).
Claim 31
Schoenefeld in view of Anderson and Janna teaches the method of claim 21, and the combination further teaches wherein the plurality of collective three-dimensional joint models is generated from patient data formatted in a digital imaging and communications in medicine (DICOM) format or a comparable format (Schoenefeld [0100], noting in-house patient data and publicly available data as a basis for generating the diseased bone model database, such that the in-house patient data and publicly available data are considered equivalent to patient data in any format representing the plurality of collective joint models; see also Anderson [0044], [0052], [0060], noting the models can start with generic models of typical patients constructed from images and other patient data, considered equivalent to patient data in any format representing the plurality of collective three dimensional joint models).
Claim 32
Schoenefeld in view of Anderson and Janna teaches the method of claim 22, and the combination further teaches wherein the progression parameters comprise points of contact between the at least a portion of the first bone and the at least a portion of the second bone (Anderson [0014], [0120]-[0123], noting modeling of points of contact between two bones in a joint to simulate the progression of wear or other pathologies over time).
Claim 33
The method of claim 32, and the combination further teaches wherein the progression parameters further comprise an angle of the first bone relative to the second bone and a depth of penetration of one of the first bone or the second bone into the other of the first bone or the second bone (Anderson [0048], [0120]-[0122], [0151], noting modeling of joint angles or range of motion as well as relative position / spacing (i.e. depth of penetration) of two elements of a joint to simulate the progression of wear or other pathologies over time).
Claim 34
Schoenefeld in view of Anderson and Janna teaches the method of claim 24, but the present combination fails to explicitly disclose wherein the bone defect comprises at least some bone loss. However, Anderson further teaches that a method of pre-operative implant planning for correcting joint issues may be performed for patients with bone defects such as bone loss (Anderson [0098], noting use of the system for assessing wear or deterioration for patients with osteoporosis which results in loss of bone mass). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to utilize the joint-based pre-operative planning method of the combination to specifically correct a bone defect indicating bone loss as in Anderson in order to assist with treatment planning for this known type of bone defect (as suggested by Anderson [0098] & [0115]).
Claims 28-29 are rejected under 35 U.S.C. 103 as being unpatentable over Schoenefeld, Anderson, and Janna as applied to claims 21-26 above, and further in view of Mafhouz (US 20150328004 A1).
Claim 28
Schoenefeld in view of Anderson and Janna teaches the method of claim 26, but the present combination fails to explicitly disclose based at least in part on the first one of the plurality of collective three-dimensional joint models, identifying, via the trained machine learning algorithm, a type and severity of the bone defect of the joint of the patient. However, Mafhouz teaches using bone models to identify a type and severity of a bone defect of a patient via a trained machine learning algorithm (Mafhouz [0163]-[0166], noting the patient’s defective anatomy type and severity is classified by a classification module trained via a database of abnormalities, i.e. based at least in part on the transformed generic 3D models when considered in the context of the combination). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the pre-operative surgical planning method of the combination to include automatically identifying a type and severity of a bone defect of a patient’s joint as in Mafhouz because this type of information can affect the choice of treatment for a particular patient (as suggested by Mafhouz [0173]), so it would be important to identify such information in an efficient and objective manner in order to consider it when selecting a treatment.
Claim 29
Schoenefeld in view of Anderson, Janna, and Mafhouz teaches the method of claim 28, and the combination further teaches based at least in part on the first one of the plurality of collective three-dimensional joint models, the type and severity of the bone defect of the joint of the patient, and the type and (Schoenefeld [0100], noting the surgical procedure is pre-operatively planned based on the selected best fit model representing a specific type of disease/deformity of a given type of joint such as the knee (i.e. based at least in part on the type of bone defect, the type of bone present in the joint, and the first one of the plurality of collective three-dimensional joint models that has been transformed into a selected diseased/deformed model as in the combination); see also Mafhouz [0163]-[0166] & [0173], noting identified type and severity of a defect affects treatment options for a patient, indicating it is considered to pre-operatively plan the surgical procedure as in the combination above).
Though the present combination contemplates pre-operative surgical planning for a patient’s joint based on various factors of the joint, it fails to explicitly disclose considering quality of bone present as one of the factors. However, Anderson further teaches modeling bone density (i.e. quality as defined in para. [0058] of Applicant’s specification) for use in guiding surgical planning decisions for a joint (Anderson [0001]-[0002], [0008], [0029], [0048], [0145]-[0147]). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the pre-operative surgical planning considerations of the combination to also include the quality/density of bone as in Anderson in order to incorporate another important physical factor of joint health, thereby improving the surgical planning output (as suggested by Anderson [0145]-[0147]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KAREN A HRANEK whose telephone number is (571)272-1679. The examiner can normally be reached M-F 8:00-4:00 ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shahid Merchant can be reached at 571-270-1360. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KAREN A HRANEK/ Primary Examiner, Art Unit 3684
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