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
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. DE 10 2022 111 284.5, filed on 05/06/2022.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/30/2024 was filed in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference sign(s) mentioned in the description:
FIG. 2: Although the specification states “If, on the other hand, it is determined in condition B3 that at least one load limit has been exceeded, the method proceeds to step S5, in which a visual warning is output via the display device before the implant model 6’ is selected” [Page 13, Lines 19-21], this figure does not include the label “S5”. Rather, this figure includes two labels “S4”.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The disclosure is objected to because of the following informalities:
[Page 3, Lines 23-24]: As written it reads “In particular, the implant model is available as a three-dimensional CAD model, which is used to perform the numerical calculations with regard to mechanical loading”. However, this is the first indication of the term “CAD”, therefore, the term should be spelled out to provide clarity.
[Page 5, Lines 15-20]: As written it reads “According to a further embodiments, the method may further comprise the step of: reading in a patient anatomy by reading in three-dimensional images/picture data of the patient, in particular MRI images and/or CT images and/or X-ray images, to create a simulation model with a patient model and the implant model, and performing the step of calculating more accurately, in particular based on a three-dimensional portion of a skeletal model and/or a musculoskeletal model of the patient”. However, this is the first indication of the term “MRI” and “CT”, therefore, the terms should be spelled out to provide clarity.
[Page 5, Lines 26-28]: As written it reads “This process can preferably be simplified and improved by using an SSM (Statistical Shape Model), especially when using X-ray images”. However, to be grammatically correct “an” (i.e. underlined) above should be “a”.
[Page 12, Lines 15-16]: As written it reads “If the control unit 2 determines that the load limits for the simulated loads on the implant model 6’ are compiled with, it issues a visual confirmation via the OR monitor”. However, this is the first instance of the term “OR”, therefore, the term should be spelled out to provide clarity.
[Page 12, Lines 20-21]: As written it reads “However, if control unit 2 determines that the load limits have been exceeded, it controls the OP monitor in such a way that a visual warning is issued before the implant model is selected”. However, this is the first indication of the term “OP”, therefore, the term should be spelled out to provide clarity.
Appropriate correction is required.
Claim Objections
Claims 15 and 20 objected to because of the following informalities:
Regarding claim 15, as written it reads “wherein, in the step of calculating simulated dynamic loads, a standardized load test according to standard ISO 14879-1 or according to standard ISO 14243 is used as a basis and is simulated and calculated accordingly”. However, this is the first instance of the acronym ISO in the claims, therefore the term should be spelled out to provide clarity.
Regarding claim 20, as written it reads “further comprising the steps of: reading in a patient anatomy by reading in three-dimensional images of the patient of MRI images and/or CT images and/or X-ray images to create a simulation model with a patient model and the implant model”. However, this is the first instance of the terms MRI and CT in the claims, therefore the terms should be spelled out to provide clarity.
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f):
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f). The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f). The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: calculation unit in claim 13 and control unit in claim 31.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. That being said, the calculation unit is described in the specification when it states “The control unit 2 has a calculation unit as a sub-unit (not shown), which calculates simulated loads based on the read-in implant parameters using predefined forces and momenta on an at the implant model 6’ and performs numerical simulations with regard to mechanical loads. On the basis of the at least one read-in implant parameter, the control unit 2 (or the calculation unit) determined whether the load limits associated with the implant model 6’ are complied with for the numerically simulated loads” [Page 12, Lines 5-10]. Therefore, it appears that the calculation unit is a component of a processor which calculates simulated loads and performs numerical simulations. Thus, claim 13 and its corresponding dependent claims are not subject to further rejection under 35 U.S.C. 112 with respect to the calculation unit.
Furthermore, the control unit is also described on [Page 12, Lines 5-10] (see above). Therefore, it appears that the control unit is a processor which calculates simulated loads and performs numerical simulations. Thus claim 31 and its corresponding dependent claims are not subject to further rejection under 35 U.S.C. 112 with respect to the control unit.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f).
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 13-14, and 16-32 is/are rejected under 35 U.S.C. 102(a)(1) and 35 U.S.C. 102(a)(2) as being anticipated by Lang et al. US 2016/0045317 A1 “Lang”.
Regarding claims 13 and 31, Lang teaches “A computer-implemented implant assistance method for a simulation and selection of at least one implant for optimized insertion or joint replacement in a surgical intervention in a patient, the computer-implemented implant assistance method comprising the steps of:” (Claim 13) (“This application relates to improved methods of modeling, designing and selecting patient-adapted (e.g., patient-specific and/or patient-engineered) implant designs, including the use of novel kinematic modeling systems and techniques in the design, manufacture, testing and surgical planning for joint replacement procedures” [0002]; “Various embodiments described herein include the use of automated and/or semi-automated computing systems to obtain, quantify, classify and/or model patient anatomical image data for use in selecting and/or designing surgical tools, implants and/or surgical procedures to repair and/or replace portions of a patient's anatomy. The models created can include actual and/or approximate models of the patient's existing anatomy as well as models of optimal, desired, undesired and/or unacceptable anatomy derived using, at least in part, the patient's existing anatomical data. The derived models can be created using a wide variety of tools, techniques and/or data sources” [0024]; “It may also be desirable to model various patient measurements (including non-load-bearing measurements as described above) to simulate the targeted joint and surrounding anatomy virtually. Such simulations can include virtually modeling the alignment and load bearing condition of the joint and surrounding anatomical structures for the patient standing and/or moving (i.e., walking, running, jumping, squatting, kneeling, walking up and down stairs or inclines/declines, picking up objects, etc.)” [0058]; “Once one or more desired models has been created using the various techniques described above, the models (optionally with information from other data sources) can be utilized to select and/or design appropriate implant components and/or surgical tools, as well as to plan the surgical procedure” [0082].
In this case, since the application relates to methods of modeling, designing and selecting a patient-adapted (i.e. patient specific) implant designs, the embodiments are automated and/or semi-automated to model patient anatomical image data for use in selecting and/or designing implants, and the model can use various patient measurements to simulate the target joint (i.e. modeling alignment and load bearing), Lang discloses a computer-implemented implant assistance method for a simulation and selection of at least one implant for optimized insertion or joint replacement in a surgical intervention in a patient.);
“An implant assistance system for a simulation and selection of at least one implant for optimized insertion or joint replacement in a surgical intervention in a patient, the implant assistance system comprising:” (Claim 31) (“Patient-adapted articular repair systems, including implants, instruments, and surgical plans, and methods of making and using such systems, are disclosed herein” [Abstract]; “In order to control the fit or match of the articular repair system with the surrounding or adjacent cartilage, cortical bone, trabecular bone, subchondral bone, cut bone and/or menisci and other tissues preoperatively, a software program can be used that projects the articular repair system over the anatomic position where it will be implanted. Suitable software is commercially available and/or can be readily modified or designed by a skilled programmer. In some embodiments, an articular surface repair system can be projected over the implantation site prior to, during or after planning or simulating the surgery virtually using one or more 3-D images” [0085]. Therefore, Lang discloses an implant assistance system for a simulation and selection of at least one implant for optimized insertion or joint replacement (see [0058]) in a surgical intervention in a patient.);
“A. a display device for outputting a visual content; and B. a control unit configured for:” (Claim 31) (“In certain embodiments, the computer software program can have a user interface that includes, for example, one or more of the components including a 3D render canvas, a data path selector, an ID listbox, a report views selection, a scan selection, a generate report button, a generate views button, an image display, and an image slice slider” [0088]. In this case, since the computer software program has a user interface which includes an image display among other functions, the implant assistance system comprises A. a display device for outputting a visual content (i.e. image display); and B. a control unit configured for performing specific steps (i.e. computer software program).);
“reading in of at least one implant parameter of an implant model, wherein the at least one implant parameter comprises an implant type” (Claim 13); “i. reading in at least one implant parameter of an implant model wherein the at least one implant parameter comprises an implant type” (Claim 31) (“In a similar manner, pre-existing implant designs and/or implant components can be selected from, catalogued in, and/or stored in a library. The library can include a virtual library of implants, or components, or component features that can be combined and/or altered to create a final implant. The library can include a catalogue of physical implant components. In certain embodiments, physical implant components can be identified and selected using the library. The library can include previously-generated implant components having one or more patient-adapted features, and/or components with standard or blank features that can be altered to be patient-adapted. Accordingly, implants and/or implant features can be selected from the library” [0106]. In order to select a pre-existing implant design or previously-generated implant components from the library, the control unit (i.e. processor) had to have performed the step of reading in of at least one implant parameter of an implant model, wherein the at least one implant parameter comprises an implant type.);
“calculating simulated dynamic loads by a calculation unit and based on the at least one implant parameter by predefined forces and momenta on and at the implant model of a load situation of a dynamic activity” (Claim 13); “ii. calculating simulated dynamic loads based on the at least one implant parameter by predefined forces and momenta on and at the implant model of a load situation of a dynamic activity” (Claim 31) (See [0058] above, and “In various embodiments, it is important to ensure that optimization, correction and/or modifications of the joint, implant, tools and/or procedure in one given manner do not adversely and/or unacceptably affect the implant components or joint in some other manner. In various embodiments, this cross-checking or cross-referencing of proposed individual modifications to the joint, implant, tools and/or surgical procedure can be accomplished using software and automated and/or semi-automated systems” [0100]; “For example, an implant component may be selected and/or adapted in shape so that it stays clear of (i.e., avoids incidental and/or long-term contact with) important ligament structures (either or both during the surgical insertion procedure as well as after implantation)” [0101]; “Testing can be accomplished by, for example, superimposing the implant image over the image for the patient's joint. In a similar manner, load-bearing measurements and/or virtual simulations thereof may be utilized to optimize or otherwise alter a derived implant design. For example, where a proposed implant for a knee implant has been designed, it may then be virtually inserted into a biomechanical model or otherwise analyzed relative to the load-bearing conditions (or virtually modeled simulations thereof) it may encounter after implantation” [0102]; “Such load-bearing/modeling analysis may also be used to further optimize or otherwise modify the implant design, such as where the implant analysis indicates that the current design is “over-engineered” in some manner than required to accommodate the patient's biomechanical needs” [0103].
Therefore, since cross-checking or cross-referencing of proposed individual modifications to an implant is performed and testing is accomplished by performing load-bearing measurements and/or virtual simulations thereof in order optimize a derived implant design, the control unit (i.e. processor) performs the step of calculating simulated dynamic loads by a calculation unit and based on the at least one implant parameter by predefined forces and momenta on and at the implant model of a load situation of a dynamic activity.);
“determining, by the calculation unit and based on the at least one implant parameter, whether load limits of the implant model are complied with for the simulated dynamic loads” (Claim 13); “iii. determining, based on the at least one implant parameter, whether load limits of the implant model are complied with in the simulated dynamic loads” (Claim 31) (“For example, where a proposed implant for a knee implant has been designed, it may then be virtually inserted into a biomechanical model or otherwise analyzed relative to the load-bearing conditions (or virtually modeled simulations thereof) it may encounter after implantation. These conditions may indicate that one or more features of the implant are undesirable for varying reasons (i.e., the implant design creates unwanted anatomical impingement points, the implant design causes the joint to function in an undesirable fashion, the joint design somehow interferes with surrounding anatomy, the joint design creates a cosmetically-undesirable feature on the repaired limb or skin covering thereof, FEA or other loading analysis of the joint design indicates areas of high material failure risk, FEA or other loading analysis of the joint design indicates areas of high design failure risk, FEA or other loading analysis of the joint design indicates areas of high failure risk of the supporting or surrounding anatomical structures, etc.)” [0102]; “If desired, the modeling software may conduct FEA or other load analysis on the tibial tray (incorporating various patient-specific information, including patient weight and intended activity levels, among other factors) and determine if specific areas of the intended implant design at are an undesirable risk of failure or fatigue. Such areas can be reinforced, thickened or otherwise redesigned (if desired) to accommodate and/or alleviate such risks (desirably before actual manufacture of the implant)” [0104]. Therefore, since the proposed implant design is virtually inserted into a biomechanical model to test load-bearing conditions and indicate one or more features or areas of the implant that are undesirable and/or present an undesirable risk of failure or fatigue, the control unit (i.e. processor) performs the step of determining, by the calculation unit and based on the at least one implant parameter, whether load limits of the implant model are complied with for the simulated dynamic loads (i.e. if an undesirable feature/specific area presents undesirable risk of failure, then the loam limits of the implant are not complied with).).; and
“outputting, by a display device, of a visual confirmation of a selection of the implant model when the load limits are complied with or outputting a visual warning before the selection of the implant model when the load limits are exceeded” (Claim 13); “iv. outputting, by the display device: a visual confirmation of a selection of the implant model when the load limits are complied with, or a visual warning before the selection of the implant model when the load limits are exceeded” (Claim 31) (“In various embodiments, the computer can model the existing patient anatomy for various uses, including (1) to create patient-specific imaging data and/or models thereof, (2) to identify deficiencies in the existing anatomy, (3) to determine if replication of the existing patient anatomy would create a desired or acceptable outcome for the joint repair/replacement procedure, (4) to derive, identify and/or plan modifications or alterations to the existing anatomy to create one or more desired anatomical features for the patient's anatomy, (5) to design joint repair/replacement implant components, surgical tools and surgical procedures for treating the relevant patient anatomy, and/or (6) to plan surgical repair and replacement procedures for display to and/or further use by surgeons and/or patients” [0118]; “At any point in the design and/or selection procedure, including any point before or after initial design and/or selection of implant components, tools and/or surgical procedure planning has been completed, biomotion models for a particular patient can be supplemented with patient-specific finite element modeling, kinematic modeling and/or other biomechanical models known in the art. Anticipated motion and/or resultant forces in the knee joint can be calculated for each component or combination of components for each specific patient. The implant and/or surgical procedure can be engineered to the patient's load and force demands. […] Such considerations may require and/or recommend changes to the initially designed and/or selected implant components, tools and/or surgical procedure steps” [0124]; “Once one or more reference points, measurements, structures, surfaces, models, or combinations thereof have been determined, selected, varied, deformed, altered or derived, the resulting models and/or features can be used to select and/or design one or more implant components having an ideal or optimized feature or shape, e.g., corresponding to the measured, deformed, altered and/or corrected joint feature(s) or shape(s). For example, one application of this embodiment could create an ideal or optimized implant shape that reflects the shape of the patient's joint before he or she developed arthritis” [0126].
Therefore, since the computer can model the existing patient anatomy to design joint repair/replacement implant components and plan surgical repair and replacement procedures for display to and/or further use by surgeons and/or patients and biomechanical models can be used to assess patient specific implant components and recommend changes to initially designed and/or selected implant components (i.e. the recommended changes representing a visual warning), the computing unit (i.e. processor) performs the step of outputting, by a display device, of a visual confirmation of a selection of the implant model when the load limits are complied with (i.e. optimized implant, see [0126]) or outputting a visual warning (i.e. recommend changes, see [0124]) before the selection of the implant model when the load limits are exceeded.).
Regarding claim 14, Lang discloses all features of the claimed invention as discussed with respect to claim 13 above, and Lang further teaches “wherein the step of calculating simulated dynamic loads of a load situation of a dynamic activity that is reproducing a load situation scaled to 100 kg on the implant model, which is obtained from measurement data of an instrumented knee prosthesis” (“A patient-specific biomotion model can be derived that includes combinations of parameters listed above. The biomotion model can simulate various activities of daily life including normal gait, stair climbing, descending stairs, running, kneeling, squatting, sitting and any other physical activity. The biomotion model can start out with standardized activities, typically derived from reference databases. These reference databases can be, for example, generated using biomotion measurements using force plates and motion trackers using radiofrequency or optical markers and video equipment” [0120]; “The biomotion model can then be individualized with use of patient-specific information including at least one of, but not limited to the patient's age, gender, weight, height, body mass index, and race, the desired limb alignment or deformity correction, and the patient's imaging data, for example, a series of two-dimensional images or a three-dimensional representation of the joint for which surgery is contemplated” [0123]; “A wide variety of possible adjustments for implant components are contemplated in the various embodiments discussed herein, including: adjustment of implant flexion (or extension) relative to one or more anatomic or biomechanical axes (e.g. femoral component flexion in a knee prosthesis)” [0190].
Therefore, since the patient-specific biomotion model simulates various activities of daily life, such as normal gait (i.e. walking), running, et cetera, and the biomotion model is individualized with the use of patient-specific information such as weight and this model is used to design/adjust implant components (see [0190]), the method involves the step of calculating simulated dynamic loads of a load situation of a dynamic activity that is reproducing a load situation scaled to 100 kg (i.e. representative of patient’s weight) on the implant model, which is obtained from measurement data of an instrumented knee prosthesis (i.e. from reference database for example.).
Regarding claim 16, Lang discloses all features of the claimed invention as discussed with respect to claim 13 above, and Lang further teaches “wherein the at least one implant parameter comprises an implant size and/or an implant dimension of the implant model” (“In various embodiments, reference points can be used to create a model of the patient's relevant biological feature(s) and/or one or more patient-adapted surgical steps, tools, and implant components. For example the reference points can be used to design a patient-adapted implant component having at least one patient-specific or patient-engineered feature, such as a surface, dimension, or other feature” [0050]. Therefore, since reference point can be used design a patient-adapted implant component having at least one patient-specific or patient-engineered feature, such as a dimension, the at least one implant parameter comprises an implant size and/or an implant dimension of the implant model.).
Regarding claim 17, Lang discloses all features of the claimed invention as discussed with respect to claim 16 above, and Lang further teaches “wherein the at least one implant parameter further comprises a position and orientation of the implant model” (“The modeling of a patient's anatomy, and the surgical repair and/or replacement of a patient's anatomical features, provides the surgeon and implant manufacturers with an opportunity to modify, correct and/or otherwise optimize/enhance at least a portion of the patient's anatomy. Many of the embodiments described herein relate to improvements, alterations, optimizations and/or modifications to the patient's biological features and/or to articular repair systems (including implant components, tools/jigs and/or surgical procedures), with an ultimate objective being the modification of and/or improvement to joint and/or extremity alignment and/or kinematics. Various embodiments include implant components that incorporate various patient-engineered features optimized from patient-specific data. […] Additional embodiments can include inserts, spacers or other components to modify and/or enhance the positioning, orientation and/or performance of the implant, as well as the performance, kinematics and/or alignment of the joint and/or extremity” [0112]; “In various embodiments, an implant component position and/or orientation could be adjusted in a hybrid kinematic model to achieve desired post-implantation joint kinematics or biomotion patterns or performance. […] The adjustment or optimization of the implant position and orientation and any related surgical interventions could also be performed automatically or semi-automatically, e.g. with optional manual user interaction or input” [0145].
Therefore, since implant components can be optimized from patient-specific data by utilizing inserts, spacers or other components to enhance the positioning, orientation and/or performance of the implant (see [0112]) and the implant component position and/or orientation may be adjusted to achieve desired post-implantation joint kinematics, biomotion patterns or performance (see [0145]), the at least one implant parameter further comprises a position and orientation of the implant model.).
Regarding claim 18, Lang discloses all features of the claimed invention as discussed with respect to claim 17 above, and Lang further teaches “wherein the at least one implant parameter further comprises a weight restriction of the implant model” (See [0104] as discussed in claim 13 above, and “Optionally, other data including anthropometric data may be added for each patient. These data can include but are not limited to the patient's age, gender, weight, height, size, body mass index, and race. Desired limb alignment and/or deformity correction can be added into the model” [0065]; “The biomotion model can then be individualized with use of patient-specific information including at least one of, but not limited to, the patient's age, gender, weight, height, body mass index, and race, the desired limb alignment or deformity correction, and the patient's imaging data, for example, a series of two-dimensional images or a three-dimensional representation of the joint for which surgery is contemplated” [0067]; “If desired, the modeling software may conduct FEA or other load analysis on the tibial tray (incorporating various patient-specific information, including patient weight and intended activity levels, among other factors) and determine if specific areas of the intended implant design at are an undesirable risk of failure or fatigue. Such areas can be reinforced, thickened or otherwise redesigned (if desired) to accommodate and/or alleviate such risks (desirably before actual manufacture of the implant)” [0104]; “The implant and/or surgical procedure can be engineered to the patient's load and force demands. For instance, in one embodiment a patient weighing 125 lbs. may not need a tibial plateau as thick as a patient weighing 280 lbs. Similarly, the polyethylene can be adjusted in shape, thickness and material properties for each patient. For example, a 3 mm polyethylene insert can be used in a light lite patient with low force, and a heavier or more active patient may need an 8 mm polymer insert or similar device. Such considerations may require and/or recommend changes to the initially designed and/or selected implant components, tools and/or surgical procedure steps” [0124]. Therefore, since the implant can be engineered to the patient’s load and force demand (i.e. with patient-specific information including weight), such that it is different for a patient weighing 125 lbs. vs. 280 lbs., the at least one implant parameter further comprises a weight restriction of the implant model.).
Regarding claim 19, Lang discloses all features of the claimed invention as discussed with respect to claim 13 above, and Lang further teaches “wherein the step of calculating simulated dynamic loads includes a weight of the patient and/or a muscular parameter of the patient as patient parameters and scales the simulated dynamic loads with the weight to provide a patient-specific calculation and selection” (See [0103] and [0104] as discussed in claim 13 above. Therefore, since the modeling software may conduct FEA or other load analysis (i.e. load-bearing/modeling analysis, see [0103]) by incorporating various patient-specific information, including patient weight, to determine specific areas of the intended implant design that are at an undesirable risk of failure or fatigue and such areas can be reinforced, thickened and/or redesigned to alleviate such risks (see [0104]), method involves the step of calculating simulated dynamic loads includes a weight of the patient and/or a muscular parameter of the patient as patient parameters and scales the simulated dynamic loads with the weight to provide a patient-specific calculation and selection.).
Regarding claim 20, Lang discloses all features of the claimed invention as discussed with respect to claim 13 above, and Lang further teaches “further comprising the steps of: reading in a patient anatomy by reading in three-dimensional images of the patient of MRI images and/or CT images and/or X-ray images to create a simulation model with a patient model and the implant model” (“In certain embodiments, imaging data collected from the patient, for example, imaging data from one or more of x-ray imaging, digital tomosynthesis, cone beam CT, non-spiral or spiral CT, non-isotropic or isotropic MRI, SPECT, PET, ultrasound, laser imaging, and/or photo-acoustic imaging, is used to qualitatively and/or quantitatively measure one or more of a patient's biological features, one or more of normal cartilage, diseased cartilage, a cartilage defect, an area of denuded cartilage, subchondral bone, cortical bone, endosteal bone, bone marrow, a ligament, a ligament attachment or origin, menisci, labrum, a joint capsule, articular structures, and/or voids or spaces between or within any of these structures” [0054]; “In order to control the fit or match of the articular repair system with the surrounding or adjacent cartilage, cortical bone, trabecular bone, subchondral bone, cut bone and/or menisci and other tissues preoperatively, a software program can be used that projects the articular repair system over the anatomic position where it will be implanted. […] In some embodiments, an articular surface repair system can be projected over the implantation site prior to, during or after planning or simulating the surgery virtually using one or more 3-D images. The cartilage, cortical bone, trabecular bone, subchondral bone, cut bone, menisci, and/or other anatomic structures are extracted from a 3-D electronic image such as an MRI or a CT using manual, semi-automated and/or automated segmentation techniques” [0085]. In this case, in order for the software program to project the articular repair system (i.e. model) over the anatomic position using one or more 3D images (i.e. MRI or CT), the method must further comprise the step of: reading in a patient anatomy by reading in three-dimensional images of the patient of MRI images and/or CT images and/or X-ray images to create a simulation model with a patient model and the implant model.) and
“performing the step of calculating simulated dynamic loads more accurately, based on a three-dimensional portion of a skeletal model and/or a musculoskeletal model of the patient” (See [0085] above and [0104] as discussed in claim 13 above. Since the software program projects the articular repair system (i.e. implant model) over the anatomic position (i.e. patient model) and bone and other anatomic structures are extracted form 3D images (i.e. such as an MRI or CT image) and FEA or other load analysis (i.e. load-bearing/modeling analysis) is performed to incorporate various patient-specific information, such as patient weight, to determine if specific areas of the intended implant are at an undesirable risk of failure or fatigue (see [0104]), the method further comprises performing the step of calculating simulated dynamic loads more accurately, based on a three-dimensional portion of a skeletal model and/or a musculoskeletal model of the patient.).
Regarding claim 21, Lang discloses all features of the claimed invention as discussed with respect to claim 13 above, and Lang further teaches “further comprising the step of outputting the visual warning when the load limits are exceeded: outputting, based on a stored implant-data set, an implant model with a modified implant size and/or implant orientation that complies with the load limits” (See [0104] and [0124] as discussed in claim 13, [0050] as discussed in claim 16 above, [0145] as discussed in claim 17 above, and “In such a case, the implant design may be further modified and/or redesigned to more accurately accommodate the patient's needs, which may have an unintended (but potentially highly-desirable) consequence of reducing implant size or thickness, reducing the required amount of bony support material removal, increasing or altering the number and/or type of potential implant component materials (due to altered requirements for material strength and/or flexibility), increasing estimate life of the implant, reducing wear and/or otherwise altering one or more of the various design “constraints” or limitations currently accommodated by the present design features of the implant and/or surgical procedure” [0103]; “Prior virtual removal/filling of such structures can facilitate and improve the design, planning and placement of tibial components, and prevent anatomic distortion from significantly affecting the final design and placement of the tibial components. For example, once one or more tibial cut planes has been virtually removed, the size, shape and rotation angle of a tibial implant component can be more accurately determined from the virtual surface, as compared to determining the size, shape and/or tibial rotation angle of an implant from the natural tibial anatomy prior to such cuts” [0133]; “Many simulations and optimizations can be performed in order to achieve postoperative kinematics that closely resemble the preoperative kinematics or in the case of severe arthritis that resemble the kinematics of the patient in the pre-arthritic state. These simulations or optimizations can include:” [0195] “Selection of an implant size” [0196]; “Selection of implant shape(s), e.g. on a femur or a tibia or a tibial insert shape (including, for example, sagittal curvature, coronal curvature of femoral component(s), tibial component, insert height etc.)” [0197]; “Selection of an implant position” [0198]; “Selection of an implant orientation” [0199].
Therefore, since the implant design may be further modified and/or redesigned to more accurately accommodate the patient’s needs (see [0103]), for example, by changing the size, shape and rotation angle of a tibial implant component (see [0133]) and this modification can be accomplished through simulations and optimizations including selecting an implant size, position and orientation (see [0195-0199], the method further comprises the step of outputting the visual warning (i.e. recommendations, see [0124]) when the load limits are exceeded (i.e. resulting in undesirable risk of failure or fatigue): outputting, based on a stored implant-data set (see Software and Data Libraries, specifically [0105]), an implant model with a modified implant size and/or implant orientation that complies with the load limits (i.e. does not present undesirable risk of failure or fatigue, see [0104]).).
Regarding claim 22, Lang discloses all features of the claimed invention as discussed with respect to claim 13 above, and Lang further teaches “further comprising the steps of: detecting, before an incision, kinematics of a joint of the patient by a navigation system or a tracking system via detectable markers attached to the joint or via inertial measuring units attached to the joint; determining a kinematic phenotype based on the kinematics of the joint of the patient; and outputting a suggestion of implant type and/or implant alignment based on the kinematic phenotype” (See [0124] and [0126] as discussed in claim 13 above, and “Various additional information can be incorporated into the model(s), including patient-specific kinematic data, such as obtained in a gait lab. If desired, patient-specific navigation data, for example generated using a surgical navigation system, image guided or non-image guided can be fed into the computer program. This kinematic or navigation data can, for example, be generated by applying optical or RF markers to the limb and by registering the markers and then measuring limb movements, for example, flexion, extension, abduction, adduction, rotation, and other limb movements” [0119]; “In addition to (or in place of) the above-mentioned measurements, it may be desirable to obtain measurements of the targeted joint (as well as surrounding anatomical areas and or other joints of the patient's anatomy) in a load-bearing or otherwise “real-world” condition. Such measurements can potentially yield extremely useful data on the alignment and/or movement of the joint and surrounding structures (as well as the loading conditions of the various joint components)” [0121]; “Such simulations can include virtually modeling the alignment and load bearing condition of the joint and surrounding anatomical structures for the patient standing and/or moving (i.e., walking, running, jumping, squatting, kneeling, walking up and down stairs or inclines/declines, picking up objects, etc.). Such simulations can be used to obtain valuable anatomical, biomechanical and kinematic data including the loaded condition of various joint components, component positions, component movement, joint and/or surrounding tissue anatomical or biomechanical constraints or limitations, as well as estimated mechanical axes in one or more directions (i.e., coronal, sagittal or combinations thereof). This information could then be utilized (alone or in combination with other data described herein) to design various features of a joint resurfacing/replacement implant” [0122]; “The resultant biomotion data can be used to further optimize the implant and/or procedure design with the objective to establish normal or near normal kinematics” [0070].
Therefore, since patient-specific kinematic and navigation data can be obtained using a surgical navigation system which generates said data by applying optical or RF markers to the limb, and the kinematic and navigation data can be utilized to obtain valuable anatomical, biomechanical and kinematic for use in designing various features of a joint resurfacing/replacement implant, the method further comprises the steps of: detecting, before an incision, kinematics of a joint of the patient by a navigation system or a tracking system via detectable markers (i.e. optical or RF markers) attached to the joint or via inertial measuring units attached to the joint; determining a kinematic phenotype (i.e. anatomical data about the movement of a joint, corresponding to flexion, extension, abduction, adduction, rotation, and other limb movements, see [0119]) based on the kinematics of the joint of the patient; and outputting a suggestion (i.e. recommend, see [0124] or resultant biomotion data, see [0070]) of implant type and/or implant alignment based on the kinematic phenotype (i.e. anatomical data about the movement of a joint).).
Regarding claim 23, Lang discloses all features of the claimed invention as discussed with respect to claim 13 above, and Lang further teaches “wherein, in addition to the at least one implant parameter, a further parameter for ground reaction forces and/or electromyography data and/or moving images are read in in order to simulate a course of patient kinematics and to determine, by inverse kinematics, a time course of the predefined forces and momenta on and at the implant model, which are used as a basis for simulated dynamic loads in the step of calculating simulated dynamic loads” (“It may also be desirable to model various patient measurements (including non-load-bearing measurements as described above) to simulate the targeted joint and surrounding anatomy virtually. Such simulations can include virtually modeling the alignment and load bearing condition of the joint and surrounding anatomical structures for the patient standing and/or moving (i.e., walking, running, jumping, squatting, kneeling, walking up and down stairs or inclines/declines, picking up objects, etc.). Such simulations can be used to obtain valuable anatomical, biomechanical and kinematic data including the loaded conditions of various joint components, component positions, component movement, joint and/or surrounding tissue anatomical or biomechanical constraints or limitations, as well as estimated mechanical axes in one or more directions (i.e., coronal, sagittal or combinations thereof)” [0058], “In various embodiments, a hybrid kinematic model could include data obtained by moving a joint through a range of motion, which can include pre-operative imaging of the joint as well as intraoperative imaging of the joint with a trial or actual implant or implant component in place, but not permanently affixed yet to the joint” [0159].
Therefore, since a hybrid kinematic model can include data obtained by moving a joint through a range of motion, which can include pre-operative imaging and intraoperative imaging of the joint, in addition to the at least one implant parameter, a further parameter for ground reaction forces and/or electromyography data and/or moving images, (i.e. specifically moving images) are read in in order to simulate a course of patient kinematics (i.e. walking, running, jumping, squatting, kneeling, walking up and down stairs or inclines/declines, picking up objects, etc., see [0058]) and to determine, by inverse kinematics, a time course of the predefined forces and momenta on and at the implant model (i.e. corresponding to the hybrid kinematic model), which are used as a basis for simulated dynamic loads in the step of calculating simulated dynamic loads (see virtual modeling in [0058]).).
Regarding claim 24, Lang discloses all features of the claimed invention as discussed with respect to claim 13 above, and Lang further teaches “further comprising the steps of: creating a multidimensional matrix based on a variance of input parameters; and determining limits/boundary parameters that are to be complied with in a combination of input parameters so that the load limits are complied with” (“In various alternative embodiments, one or more databases may be created that include anatomical information of multiple individuals, with preplanned surgical steps/tools and/or pre-designed implant components associated with relevant anatomical information. The associated information may be compiled from records of previous surgeries and/or may be created by designers and/or physicians using patient anatomical information from specific patients and/or from general population groups and/or averages. If desired, an automated and/or semi-automated system may search these one or more databases using various data from a prospective patient (utilizing one or more of any data sources described herein, including actual anatomical data, variations, reference points and features and/or models) and identify one or more matches (or other relationships, such as similarities of various relevant component features of individual anatomy) to one or more individuals. The preplanned surgical steps/tools and/or pre-designed implant components associated with such anatomy may then be assessed, evaluated, rated and/or combined (if desired), and the resulting information may be utilized to design and/or select an appropriate implant and surgical plan/tools for the prospective patient” [0097]; “Data and models can be collected in one or more libraries for subsequent use for the same patient or for a different patient (e.g., a different patient with similar data). In certain embodiments, a library can be generated to include images from a particular patient at one or more ages prior to the time that the patient needs a joint implant. For example, a method can include identifying patients eliciting one or more risk factors for a joint problem, such as low bone mineral density score, and collecting one or more images of the patient's joints into a library. In certain embodiments, all patients below a certain age, for example, all patients below 40 years of age can be scanned to collect one or more images of the patient's joint. The images and data collected from the patient can be banked or stored in a patient-specific database. For example, the articular shape of the patient's joint or joints can be stored in an electronic database until the time when the patient needs an implant. Then, the images and data in the patient-specific database can be accessed and a patient-specific and/or patient-engineered partial or total joint replacement implant using the patient's original anatomy, not affected by arthritic deformity yet, can be generated. This process results in a more functional and more anatomic implant” [0105].
Therefore, since one or more databases may be created that include anatomical information along with pre-designed implant components (i.e. organized as a multidimensional matrix, for example), such that an automated or semi-automated system can search the database using various data from a prospective patient (i.e. anatomical data, variations, reference points, features and/or models) to identify matches and use those matches to design and/or select an appropriate implant and a patient-specific database can be generated (see [0105]), the method involves creating a multidimensional matrix (i.e. within a database) based on a variance of input parameters (i.e. various data from a prospective patient including anatomical data, variations, reference points, features and/or models) and determining limits/boundary parameters (i.e. identifying risk factors for a joint problem, see [0105]) that are to be complied with in a combination of input parameters so that the load limits are complied with.).
Regarding claim 25, Lang discloses all features of the claimed invention as discussed with respect to claim 24 above, and Lang further teaches “further comprising the step of outputting, as a function of a patient's weight and an implant size, of an output parameter varus/valgus angle at which the implant model is insertable without exceeding the load limits” (See [0133] as discussed in claim 21 above, and “The position of the knee relative to said mechanical axis can be a reflection of the degree of varus or valgus deformity” [0063]; “In certain embodiments, the degree of deformity correction that is necessary to establish a desired limb alignment can be calculated based on information from the alignment of a virtual model of a patient's limb. The virtual model can be generated from patient-specific data, such 2D and/or 3D imaging data of the patient's limb. The deformity correction can correct varus or valgus alignment or antecurvatum or recurvatum alignment. In a preferred embodiment, the desired deformity correction returns the leg to normal alignment, for example, a zero degree biomechanical axis in the coronal plane and absence of genu antecurvatum and recurvatum in the sagittal plane, or various other user-defined alignment(s) can be designated and obtained” [0091]; “In particular, the patient's lower limb may be misaligned in the coronal plane, for example, a valgus or varus deformity. The deformity correction can be achieved by designing and/or selecting one or more of a resection dimension, an implant component thickness, and an implant component surface curvature that adjusts the mechanical axis or axes into alignment in one or more planes” [0129].
Therefore, since the degree of deformity correction (i.e. varus or valgus deformity) is calculated based on information from the alignment of a virtual model of a patient’s limb (see [0091]) and deformity correction (i.e. to correct a valgus or varus deformity) can be achieved by designing an implant component thickness and an implant component surface curvature that adjusts the mechanical axis or axes into alignment (see [0129]), so as to achieve normal alignment (see [0091]), the method further comprises the step of outputting, as a function of a patient's weight and an implant size, of an output parameter varus/valgus angle (i.e. corresponding to the implant component surface curvature, see [0129]) at which the implant model is insertable without exceeding the load limits (i.e. without undesirable risk of failure or fatigue, see [0104].).
Regarding claim 26, Lang discloses all features of the claimed invention as discussed with respect to claim 24 above, and Lang further teaches “further comprising the step of outputting a confirmation when a combination of the input parameters is within the limits/boundary parameters” (See [0126] as discussed in claim 13 above. Therefore, since one or more reference points, measurements, structures, surfaces, models or combinations thereof can be used to determine/select resulting models and/or features that are used to design one or more implant components having an ideal or optimized shape (i.e. specific to a patient), the method further comprises the step of outputting a confirmation when a combination of the input parameters is within the limits/boundary parameters (i.e. represents an optimal implant).).
Regarding claim 27, Lang discloses all features of the claimed invention as discussed with respect to claim 24 above, and Lang further teaches “further comprising the step of outputting a warning when a combination of the input parameters is outside the limits/boundary parameters” (See [0104] and [0124] as discussed in claim 13 above. In this case, since the modeling software may conduct FEA or other load analysis (i.e. incorporating various patient-specific information including patient weight) and determine if specific areas of the intended implant design are at an undesirable risk of failure or fatigue (see [0104]) and recommended changes to the initially designed and/or selected implant component are provided (see [0124]), the method further comprises the step of outputting a warning (i.e. recommendation, see [0124]) when a combination of the input parameters (i.e. corresponding to a patient) is outside the limits/boundary parameters (i.e. presents undesirable risk of failure or fatigue, see [0104]).).
Regarding claims 28 and 32, Lang discloses all features of the claimed invention as discussed with respect to claims 13 and 31 above, and Lang further teaches “wherein the at least one implant parameter is at least one implant dimension and/or a weight restriction of a selected implant model” (Claim 28); “wherein the at least one implant parameter is at least one implant dimension and/or a weight restriction of the implant model” (Claim 32) (See [0050] as discussed in claim 16; and [0065], [0067] and [0104] as discussed in claim 18 above.
Therefore, since reference points can be used to design a patient-adapted implant component having at least one patient-specific or patient engineered feature, such as a surface, dimension or other feature (see [0050]) and a biomotion model can be individualized with the use of patient specific information including weight (see [0067]) to determine is specific areas of the intended implant design are an undesirable risk of failure or fatigue (see [0104]), the at least one implant parameter is at least one implant dimension (see [0050]) and/or a weight restriction (i.e. patient weight) of a selected implant model/the implant model.).
Regarding claim 29, Lang discloses all features of the claimed invention as discussed with respect to claim 13 above, and Lang further teaches “wherein the dynamic activity is walking or running” (See [0058] as discussed with respect to claim 13 above. Therefore, since the model can be used to simulate the targeted joint and surrounding anatomy virtually and such simulations can include virtually modeling the alignment and load bearing condition of the joint and surrounding structures for the patient standing and/or moving (i.e. walking, running, jumping, squatting, kneeling, walking up and down stairs or inclines/declines, picking up objects, etc.), see [0058]), the dynamic activity is walking or running.).
Regarding claim 30, Lang teaches “A computer-readable storage medium comprising instructions which, when executed by a computer, cause the computer to perform the computer-implemented implant assistance method according to claim 13” (“The resulting model image can be rendered on a virtual rendering canvas (e.g., using Matlab GETFRAME function) and saved onto a computer-readable medium” [0090]. In order to carry out the processes described in claim 13 (see citations above), the computer had to have accessed instructions stored on the computer-readable medium. Therefore, Lang discloses a computer-readable storage medium comprising instructions which, when executed by a computer, cause the computer to perform the computer-implemented implant assistance method according to claim 13.).
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 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.
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lang et al. US 2016/0045317 A1 “Lang” as applied to claim 13 above, and further in view of Rashidi et al. US 2016/0235550 A1 “Rashidi”.
Regarding claim 15, Lang discloses all features of the claimed invention as discussed with respect to claim 13 above. Although Lang discloses “The biomotion model can start out with standardized activities, typically derived from reference databases” [0120], Lang does not teach “wherein, in the step of calculating simulated dynamic loads, a standardized load test according to standard ISO 14879-1 or according to standard ISO 14243 is used as a basis and is simulated and calculated accordingly”.
Rashidi is within a related field of endeavor as the claimed invention because it involves a testing apparatus for orthopedic specimens in an effort to evaluate the suitability of a particular design for use such as a prothesis, for example a knee implant (See [0003]).
Rashidi teaches “wherein, in the step of calculating simulated dynamic loads, a standardized load test according to standard ISO 14879-1 or according to standard ISO 14243 is used as a basis and is simulated and calculated accordingly” (“Various suppliers design and manufacture orthopaedic specimens in an effort to evaluate the suitability of a particular design for use such as a prosthesis, for example, a knee implant. Before these new designs are available for use, specimens must undergo rigorous testing under prescribed conditions. For example, ISO 14243 is a standard that sets forth criteria for evaluating the design and materials of knee implants, and particularly aids in evaluating the wear of test specimens. Imposed forces result in defined, discrete motions and the motions are coordinated with one another in a preselected environment (e.g., a force(s) applied in a particular pattern, for a desired time, at a desired velocity, and in a particular environment). The test is typically conducted for millions of cycles, for example, 5,000,000 to 10,000,000 cycles at 1 Hz. The test is extensive, carefully controlled, and test conditions are closely monitored, and preferably the testing apparatus can simultaneously test multiple, individual specimens under similar conditions” [0003].
Therefore, the ISO 14243 standard is used to evaluate the design and materials of knee implants, particularly in evaluating the wear of test specimens. Thus, in the step of calculating simulated dynamic loads, a standardized load test according to standard ISO14243 is used as a basis and is simulated and calculated accordingly.).
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 method of Lang such that it utilizes standard ISO 14243 as disclosed in Rashidi in order to effectively evaluate the design and materials of knee implants, particularly the wear of test specimens, as forces and discrete motions are imposed on the knee implant. The standard ISO 14243 is one of a finite number of reference characteristics that can be used to evaluate an orthopaedic prosthesis, such as a knee implant, with a reasonable expectation of success. Thus, modifying the method of Lang such that the step of calculating simulated dynamic loads, a standardized load test according to standard ISO 14879-1 or according to standard ISO 14243 is used as a basis and is simulated and calculated accordingly as disclosed in Rashidi would yield the predictable result of effectively assessing the design and materials of the implant model.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Neetz US 2016/0371838 A1 “Neetz” is pertinent to the applicant’s disclosure because it discloses “A method is disclosed for creating a production model for a patient-specific medical object” [Abstract].
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