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
Applicant’s claim for the benefit of prior-filed application 63/725156 filed 11/26/2024, application 63/709057 filed 10/18/2024, application 63/624932 filed 01/25/2024, and application 63/623553 filed 01/22/2024, under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 09/23/2025 is being considered by the examiner.
Specification
The disclosure is objected to because of the following informalities:
Figures 40A, 40B, and 41-44 are not included in the “Brief Description of the Drawings” in paragraphs [006]-[0046]. Although the drawings are described in paragraphs [0218]-[0301], applicant is advised to include the drawings in the Brief Description for completeness and clarity.
Paragraph [0078] recites “processing circuit 50”; the processing circuit is described as element 40 in previous paragraphs. Applicant is advised to amend the line to “processing circuit 40”
Paragraph [0173] recites “as ae mean of”; Applicant is advised to amend the line to “as the mean of”
Appropriate correction is required.
Claim Interpretation
The claims are interpreted consistent with SuperGuide Corp. v. DirecTV Enters., Inc., 358 F.3d 870, 69 U.S.P.Q.2d 1865 (Fed. Cir. 2004). SuperGuide recites “The phrase ‘at least one of’ precedes a series of categories of criteria, and the patentee used the term "and" to separate the categories of criteria, which connotes a conjunctive list. Thus, “at least one of x, y, and z” is “at least one of x, and at least one of, and at least one of z.”
Thus, Claims 1, 2, 4, 5, 6, and 9 are interpreted consistently with SuperGuide. Claims 1, 2, 4, 5, and 6 recite “at least one of the air and the fat.” Claim 9 recites “at least one of a B-score and a C-score”
Claim Objections
Claims 1, 13, 16, and 19 are objected to because of the following informalities:
Claim 1 recites “, and least one of the air and the fat”; Applicant is advised to amend the limitation to “, and at least one of the air and the fat”
Claim 13 contains two sentences. The claim must be in one sentence form only. Applicant is advised to cancel and redraft or otherwise amend the claim to place the claims in proper form.
Claim 16 depends upon itself. Applicant is advised to cancel and redraft or otherwise amend the claim to place the claims in proper form.
Claim 19 depends upon itself. Applicant is advised to cancel and redraft or otherwise amend the claim to place the claims in proper form.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 10-13 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 10 recites the limitation "the at least one parameter" in line 2. There is insufficient antecedent basis for this limitation in the claim. Claim 9 recites “at least one parameter,” but Claim 10 does not depend from Claim 9.
Claim 11 recites the limitation “the at least one parameter” in line 1. There is insufficient antecedent basis for this limitation in the claim. Claim 9 recites “at least one parameter,” but Claim 11 does not depend from Claim 9.
Claim 12 recites the limitation “the at least one parameter” in line 1. There is insufficient antecedent basis for this limitation in the claim. Claim 9 recites “at least one parameter,” but Claim 12 does not depend from Claim 9.
Claim 13 recites the limitation “the plurality of C-scores” in line 1. There is insufficient antecedent basis for this limitation in the claim. Claim 9 recites “a C-score” and Claim 12 recites “a plurality of C-scores,” but Claim 13 does not depend from Claim 9 or Claim 12.
Claim 13 is rejected as failing to define the invention in the manner required by 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
The claim(s) are narrative in form and replete with indefinite language. The structure which goes to make up the device must be clearly and positively specified. The structure must be organized and correlated in such a manner as to present a complete operative device. The claim(s) must be in one sentence form only. Note the format of the claims in the patent(s) cited.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 3 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 3 fails to further limit the subject matter of Claim 2. Because Claim 2 is interpreted under the Superguide Decision, Claim 2 requires “determining a BMD calibration factor based on… BMD equivalents of the motion rod and the at least one of the air” and “the at least one of the fat.” Thus, the recitation in Claim 3 of “determining the BMD calibration factor based on…the BMD equivalents of the motion rod, the air and/or the fat” broadens the limitation such that Claim 3 which depends from Claim 2 recites a broader scope than Claim 2. Claim 3 includes a case where the BMD calibration factor is based on the air or the fat, and Claim 2 requires the BMD calibration factor based on the air and the fat.
Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Yildirim et al. (US 2017/0189119 A1), in view of Lang et al. (US 2007/0047794 A1), further in view of Siewerdsen et al. (US 2015/0173703 A1).
Regarding Claim 1, Yildirim teaches “A method for predicting a type of surgery for a patient, the method comprising:
receiving imaging data including at least one image acquired of a patient's anatomy” (Yildirim, [0030] discloses “In a first step 400, one or more pre-operative images of the patient's knee are generated”; where patient’s knee is patient’s anatomy),
determining, (Yildirim, [0030] discloses “A processor 514 in computer system 510 may be operatively connected to memory 512 to analyze the bone density profile of the knee images stored in memory 512 in step 410. The bone density analysis may be performed according to known methods, for example by converting Hounsfield Units of a CT image to bone mineral density values”);
“receiving patient data regarding the patient” (Yildirim, [0031] discloses “The patient's bone density profile previously uploaded to computer system 520 may be compared to information in the bone density profile database 524 in order to diagnose the patient's ACL deficiency.” Yildirim, [0034] also discloses “The medical image or images created when the patient is presumed to have a healthy ACL may be used to track bone density profiles of the specific patient over time. In other words, the earlier images provide bone density profile information to be used as a baseline”; where previously uploaded patient bone density profile, and earlier images are patient data regarding the patient);
“generating, based at least in part on the BMD of the bone and the patient data, a predicted procedure for the patient” (Yildirim, [0032] discloses “Based on the diagnosis of the patient's ACL integrity from step 420, the surgeon may then create a surgical plan based, at least in part, on the diagnosis in step 430. This step may be performed completely manually or partially or completely autonomously”; where a surgical plan is a predicted procedure); “and
outputting the predicted procedure for display within a graphical user interface (GUI)” (Yildirim, [0032] discloses “The robotic surgical system 530 may suggest a particular procedure to the surgeon, for example via a connected display device, based on the patient's ACL diagnosis.”)
PNG
media_image1.png
554
414
media_image1.png
Greyscale
Fig. 6 of Yildirim
Yildirim does not explicitly teach “receiving imaging data including at least one image acquired of a patient's anatomy, the at least one image exhibiting (i) at least one of air and/or fat, (ii) bone, and (iii) a motion rod;identifying, using the imaging data, intensities of the bone, the motion rod, and least one of the air and the fat;based on the intensities of the bone, the motion rod, and the at least one of the air and the fat, a bone mineral density (BMD) of the bone.”
However, in an analogous field of endeavor, Lang teaches “receiving imaging data including at least one image acquired of a patient's anatomy, the at least one image exhibiting (i) at least one of air and/or fat, (ii) bone, and (Lang, [0100] discloses “For example, since the x-ray density of muscle, fat, water (e.g., soft tissue), metal (e.g., dental fillings) and air are typically known, the density of air surrounding an anatomic structure or non-living object, the density of subcutaneous fat, and the density of muscle tissue can be used to estimate the density of a selected region of bone, for example within the distal radius”);
“identifying, using the imaging data, intensities of the bone, (Lang, [0016] discloses “analyzing the image obtained in step (a) using one or more indices selected from the group consisting of Hough transform, skeleton operator, morphological operators, mean pixel intensity, variance of pixel intensity, fourier spectral analysis, fractal dimension, morphological parameters and combinations thereof, thereby deriving quantitative information on bone structure”; where mean and variance pixel intensities are intensities of the bone, air, and fat);
“determining, based on the intensities of the bone, (Lang, [0033] discloses “In another aspect, the invention includes a method of determining bone mineral density from an x-ray image, the method comprising the steps of (a) determining density of one or more internal standards in said image; (b) creating a weighted mean between the values obtained in step (a); (c) utilizing said weighted mean to determine bone mineral density of bone in said image. The internal reference can be, for example, selected from the group consisting of air, fat, water, metal and combinations thereof”).
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to have modified Yildirim to incorporate the teachings of Lang by determining bone mineral density using references of air, fat, water, and metal. One of ordinary skill in the art would be motivated to combine the Yildirim and Lang references in order to improve accuracy of a calibration phantom: Lang, [0101] discloses “The information inherent in said anatomic structure can also be combined with information provided by the calibration phantom and the combination can result in an improved accuracy of the calibration phantom.” That is, it would be obvious to one of ordinary skill in the art that the method of determining BMD recited by Lang may be applied to the method of Yildirim, because Yildirim, [0030] explicitly recites “The bone density analysis may be performed according to known methods,” and Lang recites a known method of bone density analysis.
Although Lang discloses an internal reference may include “air, fat, water, metal and combinations thereof,” Lang does not explicitly teach “the at least one image exhibiting (i) at least one of air and/or fat, (ii) bone, and (iii) a motion rod” and “determining, based on the intensities of the bone, the motion rod, and the at least one of the air and the fat, a bone mineral density (BMD) of the bone.”
However, in an analogous field of endeavor, Siewerdsen discloses “the at least one image exhibiting (i) at least one of air and/or fat, (ii) bone, and (iii) a motion rod” and “determining, based on the intensities of the bone, the motion rod, and the at least one of the air and the fat, a bone mineral density (BMD) of the bone” (Siewerdsen, [0035] discloses “ FIG. 6 illustrates an additional configuration of the proposed system further including an immobilization device 30 positioned adjacent to the patient anatomy 20” and “In the example illustrated in FIG. 6, the immobilization device 30 takes the form of an air bag, configured to immobilize a patient's knee. As illustrated in FIG. 6, the calibration phantoms 24 are integrated within the immobilization device 30”; where immobilization device is a motion rod; under the broadest reasonable interpretation, an immobilization device integrated with calibration phantoms, which Siewerdsen, [0043] describes as “The calibration phantom included six rods oriented longitudinally in a ring about the inner bore of the scanner,” is a motion rod. Siewerdsen, [0032] also discloses “The cross-sections of the phantoms 24 can be used as reference to measure/extrapolate BMD of desired structures”).
PNG
media_image2.png
578
810
media_image2.png
Greyscale
Fig. 6 of Siewerdsen
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to have modified the combination of Yildirim and Lang to incorporate the teachings of Siewerdsen by using an immobilization device with calibration rods integrated therein to determine BMD. The prior art of Yildirim and Lang contained a ‘base’ method upon which the claimed invention can be seen as an ‘improvement’; Yildirim and Lang teach a method of determining BMD using calibration phantoms and then creating a surgical plan. The claimed invention also recites determining intensity of a motion rod to determine BMD. The prior art Siewerdsen contained a ‘comparable’ method that has been improved in the same way as the claimed invention; Siewerdsen teaches a method of determining BMD including calibration phantoms and an immobilization device. One of ordinary skill in the art could have applied the known ‘improvement’ technique in the same way to the ‘base’ method and the results would have been predictable to one of ordinary skill in the art. That is, Lang teaches an internal reference including air to determine BMD, and Siewerdsen teaches an air bag immobilization device; thus, it would be obvious to one of ordinary skill in the art that the air bag of Siewerdsen may be used to determine BMD by the methods of Yildirim and Lang. Finally, one of ordinary skill in the art would be motivated to combine the Yildirim, Lang, and Siewerdsen references in order to eliminate the need to reposition phantoms: Siewerdsen, [0037] discloses “The reference phantoms may be integrated at a predefined/fixed location, whether that is within or attached to the structure of the CT scanner or whether that is within or within an object not permanently coupled to the CT scanner, such as an immobilization device, as described with respect to FIG. 6. This eliminates the need to re-position the phantoms during each scan. This is beneficial from a workflow and time management perspective. The concept also eliminates the need to place the reference phantoms in close proximity to patients. This is an improved solution in comparison to previous methods, where the phantoms are placed underneath or over the patient or surrounding an extremity of the patient, which might cause discomfort.” Accordingly, the combination of Yildirim, Lang, and Siewerdsen discloses the invention of Claim 1.
Regarding Claim 2, the combination of Yildirim, Lang, and Siewerdsen teaches “The method of claim 1, wherein determining the BMD of the bone comprises:
determining BMD equivalents of the motion rod and the at least one of the air and the fat” (Yildirim, [0030] discloses “The bone density analysis may be performed according to known methods, for example by converting Hounsfield Units of a CT image to bone mineral density values”);
determining a BMD calibration factor based on (a) the intensities of the bone, the motion rode, and the at least one of the air and the fat, and (b) BMD equivalents of the motion rod and the at least one of the air and the fat” (Lang, [0100] discloses “For instance, a weighted mean can be determined between one or more of the internal standards (e.g., air, water, metal, and/or fat) and used as internal standards to determine bone density in the same x-ray image”; where a weighted mean is a BMD calibration factor); “and
determining the BMD of the bone based on the BMD calibration factor and the intensity of the bone” (Lang, [0033] discloses “In another aspect, the invention includes a method of determining bone mineral density from an x-ray image, the method comprising the steps of (a) determining density of one or more internal standards in said image; (b) creating a weighted mean between the values obtained in step (a); (c) utilizing said weighted mean to determine bone mineral density of bone in said image.”) The proposed combination as well as the motivation for combining the Yildirim, Lang, and Siewerdsen references presented in the rejection of Claim 1, apply to Claim 2 and are incorporated herein by reference. Thus, the apparatus recited in Claim 2 is met by Yildirim, Lang, and Siewerdsen.
Regarding Claim 3, the combination of Yildirim, Lang, and Siewerdsen discloses “The method of claim 2, further comprising:
identifying, using the imaging data, intensities of the bone, the motion rod, and the air and/or the fat” (Lang, [0016] discloses “analyzing the image obtained in step (a) using one or more indices selected from the group consisting of Hough transform, skeleton operator, morphological operators, mean pixel intensity, variance of pixel intensity, fourier spectral analysis, fractal dimension, morphological parameters and combinations thereof, thereby deriving quantitative information on bone structure”; where mean and variance pixel intensities are intensities of the bone, air, and fat);
“determining BMD equivalents of the motion rod and the air and/or the fat” (Yildirim, [0030] discloses “The bone density analysis may be performed according to known methods, for example by converting Hounsfield Units of a CT image to bone mineral density values”); “and
determining the BMD calibration factor based on the intensities and the BMD equivalents of the motion rod, and the air and/or the fat” (Lang, [0100] discloses “For instance, a weighted mean can be determined between one or more of the internal standards (e.g., air, water, metal, and/or fat) and used as internal standards to determine bone density in the same x-ray image”; where a weighted mean is a BMD calibration factor). The proposed combination as well as the motivation for combining the Yildirim, Lang, and Siewerdsen references presented in the rejection of Claim 1, apply to Claim 3 and are incorporated herein by reference. Thus, the apparatus recited in Claim 3 is met by Yildirim, Lang, and Siewerdsen.
Regarding Claim 4, Yildirim, Lang, and Siewerdsen teaches “The method of claim 2, wherein the BMD equivalents of the motion rod and the at least one of the air and the fat are predetermined” (Yildirim, [0030] discloses “The bone density analysis may be performed according to known methods, for example by converting Hounsfield Units of a CT image to bone mineral density values.” Siewerdsen, [0043] also discloses “The known HU values and calcium content of the phantoms allow automatic HU calibration and BMD measurement with each scan in a manner that accounts for variations arising from the size of the subject as well as spatial variation along the axial direction”; where known HU values of phantoms are predetermined BMD equivalents). The proposed combination as well as the motivation for combining the Yildirim, Lang, and Siewerdsen references presented in the rejection of Claim 1, apply to Claim 4 and are incorporated herein by reference. Thus, the apparatus recited in Claim 4 is met by Yildirim, Lang, and Siewerdsen.
Regarding Claim 5, the combination of Yildirim, Lang, and Siewerdsen teaches “The method of claim 1, further comprising automatically identifying the motion rod, the bone, and the at least one of the air and the fat from within the at least one image” (Lang, [0157] discloses “In one embodiment, identification of anatomic landmarks of the structure to be analyzed or identification of anatomical landmarks adjacent to the structure to be analyzed with subsequent positioning and computer analysis of the x-ray image relative to these anatomic landmarks or with subsequent positioning and computer analysis of anatomical region of interest (ROI) relative to these anatomic landmarks”; where identification of anatomical landmarks is identifying motion rod, bone, air, and fat). Lang, [0157] discloses “analyzing the resulting images using landmarks based on either 1) textural information, 2.) structural information, 3.) density information (e.g. density), or 4) 2 or 3 dimensional contour information 5) a combinations thereof of the tissue or structure to be measured and of tissues or structures adjacent to the measurement site”; Lang recites analyzing landmarks based on density, and Lang also teaches known densities of internal references including air, fat, water, and metal; thus Lang teaches automatically identifying the motion rod, bone, air, and fat from within the image). The proposed combination as well as the motivation for combining the Yildirim, Lang, and Siewerdsen references presented in the rejection of Claim 1, apply to Claim 5 and are incorporated herein by reference. Thus, the apparatus recited in Claim 5 is met by Yildirim, Lang, and Siewerdsen.
Regarding Claim 6, Yildirim, Lang, and Siewerdsen teaches “The method of claim 5, wherein the motion rod, the bone, and the at least one of the air and the fat are automatically identified from within the at least one image using a shape model” (Lang, [0157] discloses “analyzing the resulting images using landmarks based on either 1) textural information, 2.) structural information, 3.) density information (e.g. density), or 4) 2 or 3 dimensional contour information 5) a combinations thereof of the tissue or structure to be measured and of tissues or structures adjacent to the measurement site”; where analyzing landmarks based on structural information and contour information is identifying motion rod, bone, air, and fat using a shape model). The proposed combination as well as the motivation for combining the Yildirim, Lang, and Siewerdsen references presented in the rejection of Claim 1, apply to Claim 6 and are incorporated herein by reference. Thus, the apparatus recited in Claim 6 is met by Yildirim, Lang, and Siewerdsen.
Regarding Claim 7, the combination of Yildirim, Lang, and Siewerdsen teaches “The method of claim 1, further comprising generating a three-dimensional model of the bone and outputting the three-dimensional model of the bone for display with the predicted procedure” (Yildirim, [0032] discloses “Images and/or 3D models of the patient's knee may be displayed by the robotic surgical system 530, along with models of one or more potential implants, allowing the surgeon to manipulate the models of the implants with respect to the model of the patient's bone to confirm the surgical plan or to otherwise create an alternative surgical plan if the suggested plan is unsatisfactory.”)
Regarding Claim 14, the combination of Yildirim, Lang, and Siewerdsen teaches “The method of claim 1, wherein the at least one image is taken from a computed tomography (CT) scan or a magnetic resonance imaging (MRI) scan” (Yildirim, [0030] discloses “The imaging may be carried out using any suitable imaging modality, including CT scanning, x-ray imaging, and others.”)
Claims 8 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Yildirim et al. (US 2017/0189119 A1), in view of Lang et al. (US 2007/0047794 A1), further in view of Siewerdsen et al. (US 2015/0173703 A1), further in view of Souza et al. (US 2015/0348259 A1).
Regarding Claim 8, the combination of Yildirim, Lang, and Siewerdsen does not explicitly teach the method of Claim 8.
However, in an analogous field of endeavor, Souza teaches “The method of claim 7, wherein the three-dimensional model of the bone exhibits the determined BMD of the bone” (Souza, [0064] discloses “In FIGS. 5A and 5B, a display 70 shows the volume image of a 3-D trabecular bone surface model 72 with a color coding that indicates computed BMD values that have been assigned to image voxels.”)
PNG
media_image3.png
480
559
media_image3.png
Greyscale
Fig. 5B of Souza
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to have modified the combination of Yildirim, Lang, and Siewerdsen to incorporate the teachings of Souza by displaying a 3D model in addition to BMD values assigned to image voxels. One of ordinary skill in the art would be motivated to combine the Yildirim, Lang, Siewerdsen, and Souza references in order to improve visualization of BMD results: Souza, [0014] discloses “An object of the present disclosure is to address the need for improved tools for assessment, monitoring and 3-D visualization of BMD results from volume imaging data.” Accordingly, the combination of Yildirim, Lang, Siewerdsen, and Souza discloses the invention of Claim 8.
Regarding Claim 10, as best understood in light of the rejection under 35 U.S.C. 112(b), above, the combination of Yildirim, Lang, Siewerdsen, and Souza teaches “The method of claim 8, further comprising outputting the determined BMD of the bone and the at least one parameter for display with the predicted procedure” (Souza, [0064] discloses “In FIGS. 5A and 5B, a display 70 shows the volume image of a 3-D trabecular bone surface model 72 with a color coding that indicates computed BMD values that have been assigned to image voxels.” Yildirim, [0032] discloses “Images and/or 3D models of the patient's knee may be displayed by the robotic surgical system 530, along with models of one or more potential implants, allowing the surgeon to manipulate the models of the implants with respect to the model of the patient's bone to confirm the surgical plan or to otherwise create an alternative surgical plan if the suggested plan is unsatisfactory.”) The proposed combination as well as the motivation for combining the Yildirim, Lang, Siewerdsen, and Souza references presented in the rejection of Claim 1, apply to Claim 10 and are incorporated herein by reference. Thus, the apparatus recited in Claim 10 is met by Yildirim, Lang, Siewerdsen, and Souza.
Claims 15 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Yildirim et al. (US 2017/0189119 A1), in view of Lang et al. (US 2007/0047794 A1), further in view of Siewerdsen et al. (US 2015/0173703 A1), further in view of Couture et al. (US 2014/0364807 A1).
Regarding Claim 15, the combination of Yildirim, Lang, and Siewerdsen does not explicitly teach the method of Claim 15.
However, in an analogous field of endeavor, Couture teaches “The method of claim 1, wherein the motion rod is a bar coupled to the patient's anatomy” (Couture, [0042] discloses “While the abutment pads 42 may be patient-specific, it is also considered to have generic abutment pads, with a telescopic relation between the bar 50 and the bar interface 36, simply to provide leveraging support for the knee jig portion 30, which knee jig portion 30 is the component of the PSI jig 20 that must be positioned with highest precision”; see Fig. 2; where bar 50 is a bar coupled to the patient’s anatomy).
PNG
media_image4.png
471
474
media_image4.png
Greyscale
Fig. 2 of Couture
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to have modified the combination of Yildirim, Lang, and Siewerdsen to incorporate the teachings of Couture by stabilizing anatomy with a bar. One of ordinary skill in the art would be motivated to combine the Yildirim, Lang, Siewerdsen, and Couture references in order to stabilize the leg for further surgical procedures: Couture, [0043] discloses “The PSI jig 20 is given as an exemplary embodiment of a jig that may be used to help in performing the subchondral injection surgery according to planning.” Accordingly, the combination of Yildirim, Lang, Siewerdsen, and Couture discloses the invention of Claim 15.
Regarding Claim 19, the combination of Yildirim, Lang, Siewerdsen, and Couture discloses “The method of claim 19, further comprising receiving a confirmed procedure for the patient and using the predicted procedure and the confirmed procedure to further train the machine learning model” (Couture, [0093] discloses “The models 610 may then be retrained using data or examples collected during use in patients. A trained model 610 is deployed for each tool type, and these models 610 can be further refined over time as more data is made available. Similarly, the model 610 may have been trained for one type of instrument 220. Data collected from testing and/or use in a patient for a different type of instrument 220 (e.g., original is a clamp and other type is a scalpel) is then used to retrain the model 610 for use with this other type of instrument 220”; where training using data collected during use is using the predicted and confirmed procedure (predicted operation and actual operation in Couture) to train the machine learning model). The proposed combination as well as the motivation for combining the Yildirim, Lang, Siewerdsen, and Couture references presented in the rejection of Claim 1, apply to Claim 19 and are incorporated herein by reference. Thus, the apparatus recited in Claim 19 is met by Yildirim, Lang, Siewerdsen, and Couture.
Claims 16 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Yildirim et al. (US 2017/0189119 A1), in view of Lang et al. (US 2007/0047794 A1), further in view of Siewerdsen et al. (US 2015/0173703 A1), further in view of Herzberg (US 5782785 A).
Regarding Claim 16, the combination of Yildirim, Lang, and Siewerdsen does not explicitly teach the method of Claim 16.
However, in an analogous field of endeavor, Herzberg teaches “The method of claim 16, wherein the motion rod is comprised of aluminum” (Herzberg, column 6, lines 21-27 discloses “The fixation rods on the frame portions 11,111 are of tubular construction and, by way of example, are comprised of aluminum or some other suitable material which, apart from a high degree of inherent rigidity, possesses a certain flexibility so as to be able to adapt to the fixation rods to the leg contours.” Herzberg, column 4, lines 46-48 discloses “The knee brace offers a high degree of therapeutic safety. The knee is immobilizable and can be stabilized in a defined manner”; where aluminum fixation rods are a motion rod comprised of aluminum.
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to have modified the combination of Yildirim, Lang, and Siewerdsen to incorporate the teachings of Herzberg by providing fixation rods comprised of aluminum. One of ordinary skill in the art would be motivated to combine the Yildirim, Lang, Siewerdsen, and Herzberg references in order to immobilize the leg while allowing flexibility for the contours of the leg: Herzberg, column 6, lines 23-26 discloses “apart from a high degree of inherent rigidity, possesses a certain flexibility so as to be able to adapt to the fixation rods to the leg contours.” Accordingly, the combination of Yildirim, Lang, Siewerdsen, and Herzberg discloses the invention of Claim 16.
Regarding Claim 17, the combination of Yildirim, Lang, Siewerdsen, and Herzberg discloses “The method of claim 16, further comprising automatically identifying the motion rod from within the at least one image using a shape model” Lang, [0157] discloses “analyzing the resulting images using landmarks based on either 1) textural information, 2.) structural information, 3.) density information (e.g. density), or 4) 2 or 3 dimensional contour information 5) a combinations thereof of the tissue or structure to be measured and of tissues or structures adjacent to the measurement site”; where analyzing landmarks based on structural information and contour information is identifying motion rod, bone, air, and fat using a shape model). The proposed combination as well as the motivation for combining the Yildirim, Lang, Siewerdsen, and Herzberg references presented in the rejection of Claim 16, apply to Claim 17 and are incorporated herein by reference. Thus, the apparatus recited in Claim 17 is met by Yildirim, Lang, Siewerdsen, and Herzberg.
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Yildirim et al. (US 2017/0189119 A1), in view of Lang et al. (US 2007/0047794 A1), further in view of Siewerdsen et al. (US 2015/0173703 A1), further in view of Babu et al. (US 2024/0081938 A1).
Regarding Claim 18, , the combination of Yildirim, Lang, and Siewerdsen does not explicitly teach the method of Claim 15.
However, in an analogous field of endeavor, Babu teaches “The method of claim 1, wherein the predicted procedure is generated at least in part using a machine learning model trained with a plurality of predicted procedures generated for prior patients and a respective plurality of confirmed procedures received for the prior patients” (Babu, [0090] discloses “In act 910, the processor 540 predicts operation of the drive chain 500 during teleoperation. The prediction is performed, at least in part, by a machine-learned model 610. The machine-learned model 610 rapidly (i.e., with less processing than an algorithm) predicts operation in response to input of the measurements. The machine-learned model 610 was previously trained on the same type of surgical instrument 220, so the measurements from operation of a given surgical instrument 220 may be used to accurately predict operation of that instrument 220.”)
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to have modified the combination of Yildirim, Lang, and Siewerdsen to incorporate the teachings of Babu by using a machine learning model to predict operation of a surgical element (drive chain) during surgery. One of ordinary skill in the art would be motivated to combine the Yildirim, Lang, Siewerdsen, and Babu references in order to detect and respond to an anomaly during surgery: Babu, [0004] discloses “Anomalies may occur, such as due to wear of the surgical instrument or drive train or due to interference. Unexpected forces can arise due to factors such as presence of debris, increase in friction due to cable fraying, unexpected external side loads, etc. Such events can lead to instrument cables snapping or impede tool tip motion and adversely affect the surgeon's capability to perform procedures. Earlier reaction or replacement to avoid problems when using with a patient is desired.” Accordingly, the combination of Yildirim, Lang, Siewerdsen, and Babu discloses the invention of Claim 18.
Allowable Subject Matter
Claim 9 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claims 11-13 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding Claim 9, determining a B-score from image data is known in the art, as cited in the Specification paragraph [0081] of the instant application (Machine- learning, MRI bone shape and important clinical outcomes in osteoarthritis: data from the Osteoarthritis Initiative, published 2020), and determining a composite score, or C-score, is also known in the art (Reach, US 2011/0125003 A1) discloses “For example, various joints may be associated with pre-determined impact values indicative of the impact harvesting bone-cartilage from that joint would have on a patient's mobility or wellbeing. In some embodiments, a composite score that factors in the various scores derived for a particular joint using the matching criteria may be determined.” However, none of the previously cited prior art explicitly teaches generating a predicted procedure based on the determined BMD, patient data, and both B-score and a C-score, as required per the interpretation consistent with Superguide, described above. That is, although individual components of Claim 9 are recited in the prior art, there is no motivation to teach the combination recited in Claim 9.
Thus, none of the previously cited references, alone or in combination, provide a motivation to teach the ordered combination of “The method of claim 1, further comprising determining, using the imaging data, at least one parameter of the patient's anatomy, the at least one parameter including at least one of a B- score and a C-score, and generating the predicted procedure for the patient based at least in part on the determined BMD of the bone, the patient data, and the at least one parameter.”
Regarding Claim 11,determining a B-score from image data is known in the art, as cited in the Specification paragraph [0081] of the instant application (Bowes et al. Machine- learning, MRI bone shape and important clinical outcomes in osteoarthritis: data from the Osteoarthritis Initiative, published 2020), and determining a composite score, or C-score, is also known in the art (Reach, US 2011/0125003 A1) discloses “For example, various joints may be associated with pre-determined impact values indicative of the impact harvesting bone-cartilage from that joint would have on a patient's mobility or wellbeing. In some embodiments, a composite score that factors in the various scores derived for a particular joint using the matching criteria may be determined.” However, none of the previously cited prior art explicitly teaches a parameter including both a B-score and a C-score, as required per the interpretation consistent with Superguide, described above. That is, although individual components of Claim 11 are recited in the prior art, there is no motivation to teach the combination recited in Claim 11. Additionally, in light of the rejection under 35 U.S.C. 112(b) rejection above for lack of antecedent basis, it is not clear what parameter the B-score and C-score refer to, or are used for.
Thus, none of the previously cited references, alone or in combination, provide a motivation to teach the ordered combination of “The method of claim 8, wherein the at least one parameter includes a B-score and a C- score”
Regarding Claim 12, determining a composite score, or C-score, is known in the art (Reach, US 2011/0125003 A1) discloses “For example, various joints may be associated with pre-determined impact values indicative of the impact harvesting bone-cartilage from that joint would have on a patient's mobility or wellbeing. In some embodiments, a composite score that factors in the various scores derived for a particular joint using the matching criteria may be determined.” However, none of the previously cited prior art explicitly teaches a plurality of C-scores. That is, although individual components of Claim 12 are recited in the prior art, there is no motivation to teach the combination recited in Claim 12. Additionally, in light of the rejection under 35 U.S.C. 112(b) rejection above for lack of antecedent basis, it is not clear what parameter the plurality of C-scores refer to, or are used for.
Thus, none of the previously cited references, alone or in combination, provide a motivation to teach the ordered combination of “The method of claim 8, wherein the at least one parameter includes a plurality of C- scores.”
Regarding Claim 13, determining a composite score, or C-score, is known in the art (Reach, US 2011/0125003 A1) discloses “For example, various joints may be associated with pre-determined impact values indicative of the impact harvesting bone-cartilage from that joint would have on a patient's mobility or wellbeing. In some embodiments, a composite score that factors in the various scores derived for a particular joint using the matching criteria may be determined.” However, none of the previously cited prior art explicitly teaches a plurality of C-scores including two or more of a medial tibiofemoral C-score, a lateral tibiofemoral C-score, a medial patellofemoral C-score, and a lateral patellofemoral C-score. That is, although individual components of Claim 13 are recited in the prior art, there is no motivation to teach the combination recited in Claim 13. Additionally, in light of the rejection under 35 U.S.C. 112(b) rejection above for lack of antecedent basis, it is not clear what parameter the plurality of C-scores refer to, or are used for.
Finally, the second sentence of the claim is recited in the prior art (Farley et al. US 2021/0307833 A1) discloses a method “a computer-assisted surgical system that includes various hardware and software components that work together to enhance surgical workflows. The disclosed techniques may be applied to, for example, shoulder, hip, and knee arthroplasties, as well as other surgical interventions” (paragraph [0002]). However, in light of the allowable subject matter of the first sentence of the claim, and the rejection of Claim 13 under 35 U.S.C. 112(b) for improper form, the claim as a whole is considered to contain allowable subject matter.
Thus, none of the previously cited references, alone or in combination, provide a motivation to teach the ordered combination of “The method of claim 10, wherein the plurality of C-scores includes two or more of a medial tibiofemoral C-score, a lateral tibiofemoral C-score, a medial patellofemoral C-score, and a lateral patellofemoral C-score. The method of claim 1, wherein the predicted procedure is either a partial knee arthroplasty or a total knee arthroplasty.”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CAROLINE TABANCAY DUFFY whose telephone number is (703)756-1859. The examiner can normally be reached Monday - Friday 8:00 am - 5:30 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Amandeep Saini can be reached at 5712723382. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/CAROLINE TABANCAY DUFFY/Examiner, Art Unit 2662
/AMANDEEP SAINI/Supervisory Patent Examiner, Art Unit 2662
