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 .
Response to Amendment
Claims 1-21 remain pending in the application in response to the applicant’s amendments to the rejections previously set forth in the Non-Final Office Action mailed 04/07/2026.
Response to Arguments
Applicant's arguments filed 07/07/22026 have been fully considered but they are not persuasive.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
For claim 1, the applicant argues “Considering this, Imhauser never identifies individual sets of contact points of those joint structures as claimed. Rather, any poses derived from the Imhauser model are thus based on ligament slack length and fiber location/density through the solution of equations of motion.” (see pg. 9, para. 1 of applicant’s remarks), and the examiner disagrees.
Imhauser is used to teach determining contact points based on geometry (Fig. 2; see para. 0094 "The knee joint model can further be constructed with a meniscus model 106 [articular contact geometry] and a coronary ligament having seven fibers [sets of contact points] constraining a medial menisci 106A of the meniscus and the tibial bone...").
For claim 1, the applicant argues “But nothing therein [Lang] ever describes applying a threshold to the determined joint poses, let alone ranking them based on the tissue information, as claimed.” (see pg. 9, para. 4), and the examiner disagrees.
Lang is used to teach applying a threshold and ranking determined joint poses based on tissue information (see para. 0568 "In various embodiments, the various levels of stress and/or strain in a muscle and/or muscle group modeled may indicate relevant information for the model, such as a value that exceeds a specified threshold [thresholding] and indicates the potential for injury and/or pain generation [ranking] in a given muscle based upon a certain implant design and/or procedure, which may be important information to a clinician seeking to avoid such an occurrence in a patient during and after surgical recovery.").
For claim 1, the applicant argues “Additionally, as the action acknowledges that Lang does not teach determining a movement capacity, it cannot possibly teach determining a motion signature based on the joint poses of the movement capacity.” (see pg. 9, para. 4), and the examiner disagrees.
Lang is used to teach determining movement capacity (see para. 0105 "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 [physically permissible joint poses]. The images and data collected from the patient can be banked or stored in a patient-specific database.").
For claim 4, the applicant argues “Nothing [in Imhauser] describes particularly identifying subchondral regions of the bones as part of that geometry.” (see pg. 10, para. 4), and the examiner disagrees.
Subchondral regions of bones are inherent and known in the art, so Imhauser inherently teaches subchondral regions of bones (see para. 0187 "Referring to FIG. 7, a 3D computational computer model of a knee joint 700 was constructed based on geometries of the bones [inherently includes subchondral regions] 702, 704, articular cartilage, menisci 706, and ligaments 708...").
For claim 6, the applicant argues “However, the alleged constraint is to the amount of bending of the knee (the flexion angle) rather than to how possible contact surfaces may relate to each other. Indeed, in some instances a 130 degree flexion may not be possible for a patient joint because of its geometry. In that case, the constraint of Imhauser and solution of equation of motions would fail to exclude that joint pose.” (see pg. 10, para. 5), and the examiner disagrees.
Imhauser teaches excluding determined combinations of contact points beyond a threshold (see para. 0148 "The computer model 700 was constructed to model passive knee flexion through a large functionally important range of motion i.e., from 0°to 130° flexion [joint poses of predetermined threshold], since this is a common peri- and intra-operative clinical examination." So modelling the knee out of the range of motion is inherently excluded).
For claim 7, the applicant argues “Additionally, regarding claim 7, the action alleges that the number of fibers in a ligament correspond to the claimed "sets of contact points." But there is no relation between these elements for several reasons. First, the number of fibers relates only to the ligament, not any other surface which it may contact, let alone the location or geometry of that contact. Second, even if those other surfaces are considered, the ligament may not be fully attached, or each fiber may be attached in several positions, such that one of ordinary skill would not consider a correspondence between the number of individual fibers and the contact points.” (see pg. 11, para. 2), and the examiner disagrees.
Imhauser teaches a set of contact points on a bone model (Fig. 2; see para. 0091 – “Additionally, each ligament model of the computer model is defined as a single or a set of fibers. In other words, the ligament model includes at least one fiber that connects two bodies, e.g., first and second bone models of a computer model of a joint.” So the fiber is connected to the bones).
For claims 8-10, the applicant argues “And merely noting that the model [in Lang] may be augmented with tissue information does not specify the particular type of information or how it is used (e.g., thresholding as in claim 9, or locations of local peaks in claim 10).” (see pg. 11, para. 3), and the examiner disagrees.
Lang teaches determining joint poses based on tissue quality (see para. 0567 "The kinematics of each joint and the force-generating parameters foreach muscle can be derived from any combinations of actual patient-specific data, experimental data, databases of relevant patients and/or mathematical approximations. The various models can estimate muscle-tendon lengths and movement arms for each of the muscles over a wide range of postures, movements and/or degrees of freedom. Given a modeled pattern of muscle activations, the hybrid kinematic model can estimate muscle forces, joint movements and surface/subsurface forces and stresses experienced by joint support structures and/or articulating surfaces (including implant component designs therefor).").
For claim 15, the applicant argues “That is, the claim particularly recites identifying centroids of a ligament insertion or identifying elevated tissue intensity regions. Such specific features cannot be found or inferred from the generic suggestion that a model be based on bone geometry.” (see pg. 11, para. 4), and the examiner disagrees
Imhauser teaches determining the geometry of a ligament, and determining a centroid as a geometry is inherent and known in the art, so Imhauser inherently teaches determining a centroid of a ligament (see para. 0187 "Referring to FIG. 7, a 3D computational computer model of a knee joint 700 was constructed based on geometries of the bones 702, 704, articular cartilage, menisci 706, and ligaments 708...").
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.
Claims 1-21 are rejected under35U.S.C. 103asbeingunpatentableover Lang (US 20160045317 A1, published February 18, 2016) in view of Imhauser et al. (US 20170162078 A1, published June 8, 2017), hereinafter referred to as Lang and Imhauser, respectively.
Regarding claim 1, and similarly for claims 20 and 21, Lang teaches a method (Fig. 1) comprising:
acquiring three-dimensional (3D) data of a joint of a subject (see para. 0029 "As illustrated in FIG. 1, a method of generating a model of a patient's joint or other biological feature can include one or more of the steps of obtaining image data of a patient's biological structure 910..."; see para. 0033 "Moreover, as shown in FIG. 2B, the segmented and selected data from multiple images can be combined to create a 3D representation of the biological structure.");
determining a tissue quality on articular contact geometry based on the 3D data (see para. 0187 "The finite element data can be augmented with patient specific data (e.g., data obtained from the patient's scan including also for example bone mineral density or structure [tissue quality and geometry]) or any of the parameters mentioned above and throughout the specification."); and
determining a motion signature of the joint based on the reconstructed articular contact geometry and the tissue quality by applying a predetermined threshold and ranking the joint poses of the movement capacity based on the determined tissue quality (see para. 0567 "The kinematics of each joint and the force-generating parameters foreach muscle can be derived from any combinations of actual patient-specific data, experimental data, databases of relevant patients and/or mathematical approximations. The various models can estimate muscle-tendon lengths and movement arms for each of the muscles over a wide range of postures, movements and/or degrees of freedom. Given a modeled pattern of muscle activations, the hybrid kinematic model can estimate muscle forces, joint movements and surface/subsurface forces and stresses experienced by joint support structures and/or articulating surfaces (including implant component designs therefor)."),
wherein the movement capacity is a subject-specific set of physically permissible joint poses based on the reconstructed articular geometry (see para. 0105 "In certain embodiments, all patients below a certain age, for example, all patients below40 years of age can be scanned to collect one or more images of the patient's joint [physically permissible joint poses]. The images and data collected from the patient can be banked or stored in a patient-specific database."), and
wherein the motion signature is a subject-specific set of joint poses that is a subset of the movement capacity and that corresponds to the subject's habitual movement and is ranked based on the determined tissue quality (see para. 0568 "In various embodiments, the various levels of stress and/or strain in a muscle and/or muscle group modeled may indicate relevant information for the model, such as a value that exceeds a specified threshold and indicates the potential for injury and/or pain generation in a given muscle based upon a certain implant design and/or procedure, which may be important information to a clinician seeking to avoid such an occurrence in a patient during and after surgical recovery.").
Lang teaches acquiring imaging data of a joint, including articular contact geometry (see para. 0054 "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."), but does not explicitly teach determining joint poses from the sets of contact points of joint structures from the reconstructed articular contact geometry.
Whereas, Imhauser, in an analogous field of endeavor, teaches reconstructing an articular contact geometry of the joint based on the 3D data (Fig. 2; see para. 0094 "The knee joint model [3D data] can further be constructed with a meniscus model 106 [articular contact geometry]...");
determining a movement capacity of the joint based on the reconstructed articular contact geometry by determining sets of contact points of joint structures from the reconstructed articular contact geometry (Fig. 2; see para. 0094 "The knee joint model can further be constructed with a meniscus model 106 [articular contact geometry] and a coronary ligament having seven fibers [sets of contact points] constraining a medial menisci 106A ofthe meniscus and the tibial bone..."),
determining joint poses from the sets of contact points (Fig. 2, viewing (determining) joint poses from knee ligament fibers (shown as lines connecting sets of contact points)), and
applying a predetermined threshold to the determined joint poses, and including only the joint poses which satisfy the predetermined threshold (see para. 0148 "The computer model 700 was constructed to model passive knee flexion through a large functionally important range of motion i.e., from 0° to 130° flexion [joint poses of predetermined threshold], since this is a common peri- and intra operative clinical examination.").
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified acquiring imaging data of a joint, including articular contact geometry, as disclosed in Lang, by also determining joint poses from the sets of contact points of joint structures from the reconstructed articular contact geometry, as disclosed in Imhauser. One of ordinary skill in the art would have been motivated to make this modification in order to make accurate predictions of instability, which is a common symptom of an ACL-deficient knee, as taught in Imhauser (see para. 0211).
Furthermore, regarding claim 2, Lang further teaches wherein the joint is a musculoskeletal joint (see para. 0064 "In certain embodiments, a computer program simulating biomotion of one or more joints, such as, for example, a knee joint, or a knee and ankle joint, or a hip, knee and/or ankle joint [musculoskeletal joints], can be utilized.").
Furthermore, regarding claim 3, Lang further teaches wherein the joint is an artificial joint (see para. 0093 - “If desired, an implant design [artificial joint] can alter the kinematics of the patient knee as desired, such as, for example, by altering a condyle location and/or surface to alter the implant motion and ultimately the kinematics of the patient's limb.").
Furthermore, regarding claim 4, Imhauser further teaches wherein reconstructing the articular contact geometry comprises: segmenting bones of the joint based on the 3D data; determining subchondral regions of bone surface geometry of the joint based on the segmented bones and the 3D data; and determining articular contact surfaces based on the subchondral regions (see para. 0187 "Referring to FIG. 7, a 3D computational computer model of a knee joint 700 was constructed based on geometries of the bones 702, 704, articular cartilage, menisci 706, and ligaments 708...").
Furthermore, regarding claim 5, Imhauser further teaches determining he movement capacity of the joint, wherein determining the movement capacity of the joint comprises determining combinations of contact points between opposing articular contact surfaces of the reconstructed articular contact geometry, wherein each determined combination of contact points corresponds to a pose and orientation of the joint (Fig. 2, viewing (determining) joint poses from ligament fibers (shown as lines connecting sets of contact points) between tibia and femur).
Furthermore, regarding claim 6, Imhauser further teaches wherein determining the movement capacity or the motion signature of the joint comprises excluding determined combinations of contact points in which opposing articular contact surfaces penetrate each other beyond a predetermined threshold (Fig. 2, knee ligament fibers shown as lines connecting sets of contact points; see para. 0148 "The computer model 700 was constructed to model passive knee flexion through a large functionally important range of motion i.e., from0°to 130° flexion [joint poses of predetermined threshold], since this is a common peri- and intra-operative clinical examination." So modelling the knee out of the range of motion is inherently excluded).
Furthermore, regarding claim 7, Imhauser further teaches wherein each of the opposing articular contact surfaces have corresponding contact points, and wherein alignment of the corresponding contact points to each other is constrained based on geometric relationships between contact points of opposing articular surfaces (Fig. 2; see para. 0094 "The knee joint model can further be constructed with a meniscus model 106 and a coronary ligament having seven fibers [sets of contact points] constraining a medial menisci 106A of the meniscus and the tibial bone...").
Furthermore, regarding claim 8, Lang further teaches wherein determining the motion signature comprises: mapping the determined tissue quality on the articular contact geometry (see para. 0032 "As shown, the distinctive transition in color intensity or grayscale 19000 at the surface of the structure can be used to identify pixels, voxels, corresponding data points, a continuous line, and/or surface data representing the surface or other feature of the biological structure."); and
estimating joint rotations and translations based on contact point sets of opposing articular contact surfaces (see para. 0193 "Joint motion that can be measured can include, but is not limited to: translation of one articular surface relative to the other; rotation of one articular surface relative to the other during: Flexion; Extension; Abduction; Adduction; Elevation; Internal rotation; External rotation; and other joint movements.").
Furthermore, regarding claim 9, Lang further teaches excluding estimated joint rotations and translations based on thresholds of the determined tissue quality mapped to the articular contact geometry at the contact points (see para. 0568 "In various embodiments, the various levels of stress and/or strain in a muscle and/or muscle group modeled may indicate relevant information for the model, such as a value that exceeds a specified threshold and indicates the potential for injury and/or pain generation in a given muscle based upon a certain implant design and/or procedure, which may be important information to a clinician seeking to avoid such an occurrence in a patient during and after surgical recovery.").
Furthermore, regarding claim 10, Lang further teaches wherein the joint rotations and translations are estimated based on locations of local peaks of the determined tissue quality mapped to the articular geometry as contact point candidates, and based on a cumulative tissue quality across contact points of each joint rotation and translation (see para. 0187 "The finite element data can be augmented with patient specific data (e.g., data obtained from the patient's scan including also for example bone mineral density or structure) or any of the parameters mentioned above and throughout the specification.").
Furthermore, regarding claim 11, Imhauser further teaches segmenting cartilage of the joint based on the 3D data; and generating surface geometries of cartilage based on the segmented cartilage, wherein reconstructing the articular contact geometry comprises generating articular surfaces based on articulating portions of cartilage determined from the segmented cartilage and generated surface geometries of the cartilage (see para. 0187 "Referring to FIG. 7, a 3D computational computer model of a knee joint 700 was constructed based on geometries of the bones 702, 704, articular cartilage, menisci 706, and ligaments 708...").
Furthermore, regarding claim 12, Imhauserfurther teaches wherein determining the movement capacity or motion signature comprises: estimating joint rotations and translations based on contact point sets of opposing articular contact surfaces; and excluding joint rotations and translations in which cartilage surfaces penetrate each other beyond a predetermined threshold (Fig. 2, knee ligament fibers shown as lines connecting sets of contact points; see para. 0148 "The computer model 700 was constructed to model passive knee flexion through a large functionally important range of motion i.e., from 0° to 130° flexion [joint poses of predetermined threshold], since this is a common peri- and intra operative clinical examination." So modelling the knee out of the range of motion is inherently excluded).
Furthermore, regarding claim 13, Imhauser further teaches wherein the joint is a knee and the method further comprises: segmenting menisci tissue of the knee based on the 3D data; and generating surface geometry of menisci based on the segmented menisci, wherein reconstructing the articular contact geometry comprises generating articular surfaces based on the segmented menisci and generated surface geometries of the menisci (see para. 0187 "Referring to FIG. 7, a 3D computational computer model of a knee joint 700 was constructed based on geometries of the bones 702, 704, articular cartilage, menisci 706, and ligaments 708...").
Furthermore, regarding claim 14, Imhauser further teaches wherein determining the movement capacity or the motion signature comprises: estimating joint rotations and translations based on contact point sets of opposing articular contact surfaces; and excluding joint rotations and translations in which opposing articular contact surfaces and menisci penetrate each other beyond a predetermined threshold (Fig. 2, knee ligament fibers shown as lines connecting sets of contact points; see para. 0148 "The computer model 700 was constructed to model passive knee flexion through a large functionally important range of motion i.e., from0°to 130° flexion [joint poses of predetermined threshold], since this is a common peri- and intra-operative clinical examination." So modelling the knee out of the range of motion is inherently excluded).
Furthermore, regarding claim 15, Imhauser further teaches wherein the method further comprises determining ligament insertions by: segmenting ligament insertion footprints on joint bones based on the 3D data; and identifying a centroid of ligament insertion based on the segmented ligament insertion footprints, or identifying elevated tissue intensity regions on the joint bones and estimating ligament insertion footprints based on the identified elevated tissue intensity regions (see para. 0187 "Referring to FIG. 7, a 3D computational computer model of a knee joint 700 was constructed based on geometries of the bones 702, 704, articular cartilage, menisci 706, and ligaments 708...").
Furthermore, regarding claim 16, Imhauserfurther teaches wherein determining the movement capacity or motion signature comprises: estimating joint rotations and translations based on contact point sets of opposing articular contact surfaces; determining a length of a ligament for the estimated joint rotations and translations based on the estimated ligament insertion footprints; determining a statistical distribution of the determined ligament lengths across a plurality of joint rotations and translations; and excluding joint rotations and translations in which ligament lengths exceed a predetermined threshold (see para. 0218 "In sum, the computational computer model 700 and method of constructing the computational computer model of a knee joint included identifying ligaments having a load at full extension, and identifying a ligament slack length of each ligament and incorporating said ligaments and slack lengths in a computational computer knee model. The computer model was capable of predicting knee kinematics and forces on a subject knee joint at low ligament loads and coupled anterior translation and internal rotation through a large range of passive flexion of the subject's knee joint.").
Furthermore, regarding claim 17, Lang further teaches wherein the 3D data of the joint is of an unloaded configuration of the joint (see para. 0122 "It may also be desirable to model various of the patient measurements (especially non-load-bearing measurements as described above) to simulate the targeted joint and surrounding anatomy virtually.").
Furthermore, regarding claim 18, Lang further teaches wherein the 3D data of the joint is of a loaded configuration of the joint (see para. 0121 "Such load-bearing measurements can include imaging of the patient standing, kneeling, walking and/or carrying loads of varying sizes and/or weights.").
Furthermore, regarding claim 19, Lang further teaches generating a report of the determined movement capacity and/or the determined motion signature; outputting the report (see para. 0082 "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."; see para. 0118 "The models (as well as the raw anatomical information) can be used to simulate biomotion of one or more joints and/or extremities, such as a knee joint, or a knee and ankle joint, or a hip, knee and/or ankle joint.”); and
diagnosing or treating a patient based on the determined movement capacity or the determined motion signature (see para. 0088 "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.").
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Saget et al. (US 20190122330 A1, published April 25, 2019) discloses receiving an at least one preoperative image of a subject; computing an image quality score using an Image Quality Scoring Module; accepting or rejecting the preoperative image based on quality score generated by a Pose Guide Module.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Nyrobi Celestine whose telephone number is 571-272-0129. The examiner can normally be reached on Monday - Thursday, 7:00AM - 5:00PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Pascal Bui-Pho can be reached on 571-272-2714. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/N.C./Examiner, Art Unit 3798
/PASCAL M BUI PHO/Supervisory Patent Examiner, Art Unit 3798
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