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 Arguments
Applicant argues that the references cited do not disclose the 3D mask as recited by the amended language of the independent claims. Applicant argues specifically that Williamson’s density values extracted along the trajectories are not equivalent to a 3D mask, however, this is respectfully not agreed. The full context of that feature of Williamson describes utilizing a 3mm x 3mm square mask (a 2D mask) oriented normal to the trajectory, across the length of the trajectory, which is effectively projecting that square mask down the trajectory to create a 3D mask. This is maintained to fall within the scope of the claim language and be equivalent to a 3D mask, and is maintained to be used to filter the image data. In view of this, the prior cited references are maintained to disclose the claims as amended. See the 35 USC 103 section below for details.
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.
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 11-18 and 20-22 are rejected under 35 U.S.C. 103 as being unpatentable over Williamson (T. M. Williamson et al., "Estimation of Tool Pose Based on Force–Density Correlation During Robotic Drilling," in IEEE Transactions on Biomedical Engineering, vol. 60, no. 4, pp. 969-976, April 2013) in view of Dai (Y. Dai, Y. Xue and J. Zhang, "Milling State Identification Based on Vibration Sense of a Robotic Surgical System," in IEEE Transactions on Industrial Electronics, vol. 63, no. 10, pp. 6184-6193, Oct. 2016).
Regarding Claim 11:
Williamson teaches:
receiving an estimate of bone mineral density for an anatomical element; (Abstract, heterogeneous bone density in the mastoid extracted from 3-D image data; Section II.B., Cone-beam computed tomography (CBCT) (ProMax, Planmeca Oy, Helsinki, Finland) images (isometric voxel size 0.15 mm) of three cranial human cadaver specimens … Density values along the planned and candidate trajectories were extracted utilizing open-source libraries)
wherein the estimate of bone mineral density is based on filtering one or more images of the anatomical element using a three-dimensional mask; (examiner notes that the following citation is applying a square region of 3x3mm (a 2D mask) along the length of the trajectory, creating the equivalent of a roughly rectangular prism shaped 3D mask; p.970 col 2, Density values along the planned and candidate trajectories were extracted utilizing open-source libraries (VTK, Kitware, Clifton Park, NY). For a given trajectory, the corresponding axial density array was calculated by averaging all voxel intensity values in a given lateral plane (normal to the drilling trajectory), within a 0.8-mm radius (the radius of the drill to be used). The step size in the axial direction was determined by the length of the output array and the length of the planned trajectory; in this case, a total of 100 density values along the trajectory were generated. A square region of interest (3 × 3 mm) was defined around the planned entry position e0 . This allows all structures of interest within the facial recess to be included and covers a region approximately 3σ from the planned target,)
initiating a surgical maneuver on the anatomical element with the surgical robot; (Section II.B., Drilling was completed ... The robot tool position relative to the cadaver head was recorded both in the coordinate system of the optical tracking system (30 Hz) and in the coordinate system of the robot (100 Hz). This positioning data were transformed into the image coordinate system and combined with force data using time stamp information. )
receiving sensor information from a robotic sensor during the surgical maneuver; (Section II.B., Time-stamped force data were logged with a sampling rate of 40 Hz. The robot tool position relative to the cadaver head was recorded both in the coordinate system of the optical tracking system (30 Hz) and in the coordinate system of the robot (100 Hz). This positioning data were transformed into the image coordinate system and combined with force data using time stamp information.)
Williamson does not teach in particular, but Dai teaches:
comparing the sensor information with an anticipated sensor reading, wherein the anticipated sensor reading is determined based on the estimate of bone mineral density for the anatomical element; and (Section I.A., A typical bone structure is composed of hard cortical bone on the outside and less dense cancellous bone on the inside. Because the hardness of a material is one of the factors of varied cutting force, the force sensor can be used to determine whether the tool is located in one of cortical bone, cancellous bone, and cortical bone near a boundary with soft tissue.; Section III.B., The milling force is primarily affected by three factors: cutting conditions (spindle speed, feed rate, and depth of cut), cutting tool geometry, and mechanical properties of work material … It can be seen from (7) and ( 9) that the milling force is directly proportional to the vibration amplitude of the mass mb (i.e., the bone being cut) and the acceleration of OPD.)
controlling the surgical robot during the surgical maneuver based on the comparison of the sensor information with the anticipated sensor reading. (Section III.C., In order to determine different types of milling state, we couple the compensated wavelet energy to a SVM classifier, which can find a hyper plane for nonlinear features to separate predetermined classes. The measurement position of LDS may be located in the spinal cord, the muscle, the vertebra being cut, or the adjacent bony structure, so four classes should be identified.; Section IV.A., the robot is controlled to make the burr contact with the vertebra gradually, and at the same time the vibration of the vertebra is measured by the LDS.; Section IV.D., This speed is good enough for real-time analysis; Section VI., the robot knows which types of tissue will be cut by the burr, so the robot arm mounted with the OPD can stop moving before the burr encounters the vital anatomy (such as the spinal cord).)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed utilize the real-time control of Dai with the bone density material analysis of Williamson, in order to improve the safety of the system ("The safety of the robot-assisted orthopedic surgery is thus improved", Dai, Section VI.).
Regarding Claim 12:
Williamson teaches:
wherein the surgical maneuver comprises at least one of drilling, milling, and cutting the anatomical element. (Section I., a trajectory is drilled)
Regarding Claim 13:
Williamson teaches:
wherein the estimate of bone mineral density for the anatomical element is related to a particular volume of the anatomical element. (Section I., Thus, we present a method that enables the estimation of the current pose of a drill within the mastoid utilizing measurements derived from the DCA machining process (axial forces of the drilling tool) and variations in bone density as quantified using 3-D diagnostic image data; Section II.A., Further feedback is presented as drilling force and bone density data.; Section II.B., a total of 100 density values along the trajectory were generated.)
Regarding Claim 14:
Williamson teaches:
wherein the sensor information comprises at least one of drilling resistance, drilling torque, drilling depth, and force on an arm of the surgical robot. (Section III.B., The milling force is primarily affected by three factors: cutting conditions (spindle speed, feed rate, and depth of cut), cutting tool geometry, and mechanical properties of work material; Section III.B., dynamic milling force … the milling force is directly proportional to the vibration amplitude of the mass mb (i.e., the bone being cut) and the acceleration of OPD. The milling vibration is transmitted from the bone to its adjacent soft tissues. If the tissues are modeled as concentrated mass-spring systems, it is concluded that the milling force is also directly proportional to the vibration amplitude of the tissues)
Regarding Claim 15:
Williamson does not teach in particular, but Dai teaches:
wherein controlling the surgical robot comprises automatically stopping the surgical maneuver. (Section III.C., In order to determine different types of milling state, we couple the compensated wavelet energy to a SVM classifier, which can find a hyper plane for nonlinear features to separate predetermined classes. The measurement position of LDS may be located in the spinal cord, the muscle, the vertebra being cut, or the adjacent bony structure, so four classes should be identified.; Section IV.A., the robot is controlled to make the burr contact with the vertebra gradually, and at the same time the vibration of the vertebra is measured by the LDS.; Section IV.D., This speed is good enough for real-time analysis; Section VI., the robot knows which types of tissue will be cut by the burr, so the robot arm mounted with the OPD can stop moving before the burr encounters the vital anatomy (such as the spinal cord).)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed utilize the real-time control of Dai with the bone density material analysis of Williamson, in order to improve the safety of the system ("The safety of the robot-assisted orthopedic surgery is thus improved", Dai, Section VI.).
Regarding Claim 16:
Williamson does not teach in particular, but Dai teaches:
wherein controlling the surgical robot comprises allowing the surgical maneuver to continue in an autonomous fashion. (Section III.C., In order to determine different types of milling state, we couple the compensated wavelet energy to a SVM classifier, which can find a hyper plane for nonlinear features to separate predetermined classes. The measurement position of LDS may be located in the spinal cord, the muscle, the vertebra being cut, or the adjacent bony structure, so four classes should be identified.; Section IV.A., the robot is controlled to make the burr contact with the vertebra gradually, and at the same time the vibration of the vertebra is measured by the LDS.; Section IV.D., This speed is good enough for real-time analysis; Section VI., the robot knows which types of tissue will be cut by the burr, so the robot arm mounted with the OPD can stop moving before the burr encounters the vital anatomy (such as the spinal cord).)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed utilize the real-time control of Dai with the bone density material analysis of Williamson, in order to improve the safety of the system ("The safety of the robot-assisted orthopedic surgery is thus improved", Dai, Section VI.).
Regarding Claim 17:
Williamson does not teach in particular, but Dai teaches:
wherein the anatomical element comprises a vertebra. (Abstract, the success rate achieves 100% for the vertebra being milled)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed utilize the real-time control of Dai with the bone density material analysis of Williamson, in order to improve the safety of the system ("The safety of the robot-assisted orthopedic surgery is thus improved", Dai, Section VI.).
Regarding Claim 18:
Williamson teaches:
wherein the estimate of bone mineral density for the anatomical element is determined with a CT scan or x-ray of the anatomical element. (Abstract, heterogeneous bone density in the mastoid extracted from 3-D image data; Section II.B., Cone-beam computed tomography (CBCT) (ProMax, Planmeca Oy, Helsinki, Finland) images (isometric voxel size 0.15 mm) of three cranial human cadaver specimens … Density values along the planned and candidate trajectories were extracted utilizing open-source libraries)
Regarding Claim 20:
Williamson teaches:
a first sensor; (Fig. 1, Robotic system utilized for drilling … force-torque sensor; see also Dai Section II., The LDS LK-H082 (Keyence Corporation, Osaka, Japan) is introduced for noncontact tissue vibration measurement during spine surgery.)
a surgical tool; (Fig. 1, Robotic system utilized for drilling)
receive an estimate of bone mineral density for an anatomical element, (Abstract, heterogeneous bone density in the mastoid extracted from 3-D image data; Section II.B., Cone-beam computed tomography (CBCT) (ProMax, Planmeca Oy, Helsinki, Finland) images (isometric voxel size 0.15 mm) of three cranial human cadaver specimens … Density values along the planned and candidate trajectories were extracted utilizing open-source libraries)
wherein the estimate of bone mineral density is based on filtering one or more images of the anatomical element using a three-dimensional mask; (examiner notes that the following citation is applying a square region of 3x3mm (a 2D mask) along the length of the trajectory, creating the equivalent of a roughly rectangular prism shaped 3D mask; p.970 col 2, Density values along the planned and candidate trajectories were extracted utilizing open-source libraries (VTK, Kitware, Clifton Park, NY). For a given trajectory, the corresponding axial density array was calculated by averaging all voxel intensity values in a given lateral plane (normal to the drilling trajectory), within a 0.8-mm radius (the radius of the drill to be used). The step size in the axial direction was determined by the length of the output array and the length of the planned trajectory; in this case, a total of 100 density values along the trajectory were generated. A square region of interest (3 × 3 mm) was defined around the planned entry position e0 . This allows all structures of interest within the facial recess to be included and covers a region approximately 3σ from the planned target,)
initiate a surgical maneuver on the anatomical element with the surgical tool; (Section II.B., Drilling was completed ... The robot tool position relative to the cadaver head was recorded both in the coordinate system of the optical tracking system (30 Hz) and in the coordinate system of the robot (100 Hz). This positioning data were transformed into the image coordinate system and combined with force data using time stamp information. )
receive information from the first sensor during the surgical maneuver; (Section II.B., Time-stamped force data were logged with a sampling rate of 40 Hz. The robot tool position relative to the cadaver head was recorded both in the coordinate system of the optical tracking system (30 Hz) and in the coordinate system of the robot (100 Hz). This positioning data were transformed into the image coordinate system and combined with force data using time stamp information.)
Williamson does not teach in particular, but Dai teaches:
a processor; and a memory including data stored thereon that, when processed by the processor, cause the processor to: (Section IV.B., executed on a computer with a 3.7 GHz Intel Xeon Quad-core CPU, 16 GB RAM, and an operating system of Windows 8.1 (64-bit). )
compare the information with an anticipated sensor reading, wherein the anticipated sensor reading is determined based on the estimate of bone mineral density for the anatomical element; and (Section I.A., A typical bone structure is composed of hard cortical bone on the outside and less dense cancellous bone on the inside. Because the hardness of a material is one of the factors of varied cutting force, the force sensor can be used to determine whether the tool is located in one of cortical bone, cancellous bone, and cortical bone near a boundary with soft tissue.; Section III.B., The milling force is primarily affected by three factors: cutting conditions (spindle speed, feed rate, and depth of cut), cutting tool geometry, and mechanical properties of work material … It can be seen from (7) and ( 9) that the milling force is directly proportional to the vibration amplitude of the mass mb (i.e., the bone being cut) and the acceleration of OPD.)
control the surgical tool during the surgical maneuver based on the comparison of the information with the anticipated sensor reading. (Section III.C., In order to determine different types of milling state, we couple the compensated wavelet energy to a SVM classifier, which can find a hyper plane for nonlinear features to separate predetermined classes. The measurement position of LDS may be located in the spinal cord, the muscle, the vertebra being cut, or the adjacent bony structure, so four classes should be identified.; Section IV.A., the robot is controlled to make the burr contact with the vertebra gradually, and at the same time the vibration of the vertebra is measured by the LDS.; Section IV.D., This speed is good enough for real-time analysis; Section VI., the robot knows which types of tissue will be cut by the burr, so the robot arm mounted with the OPD can stop moving before the burr encounters the vital anatomy (such as the spinal cord).)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed utilize the real-time control of Dai with the bone density material analysis of Williamson, in order to improve the safety of the system ("The safety of the robot-assisted orthopedic surgery is thus improved", Dai, Section VI.).
Regarding Claim 21:
Williamson does not teach in particular, but Dai teaches:
wherein the sensor information comprises a sensor reading, and (Section II.B., Time-stamped force data were logged with a sampling rate of 40 Hz. The robot tool position relative to the cadaver head was recorded both in the coordinate system of the optical tracking system (30 Hz) and in the coordinate system of the robot (100 Hz). This positioning data were transformed into the image coordinate system and combined with force data using time stamp information.)
wherein the method further comprises: determining a difference between the sensor reading and the anticipated sensor reading; comparing the difference to a threshold value; and (Section III.A., after a predictor for the even indexed samples is defined, the difference between the predicted results and the odd samples is the detail coefficients of the signal; examiner notes the following section demonstrates that the reference is relying on there being a "large enough difference" in harmonic energy for its comparisons, equivalent to a minimum threshold: Section V., shown in Fig. 6, the 2nd and 3rd harmonics energy corresponding to the adjacent bony structure is close to that corresponding to the muscle, as well as there is not a large difference between the 1st harmonic energy, so the classifier cannot identify these two types of tissue correctly.)
generating an alert when the difference meets or exceeds the threshold value. (Section VI, the robot knows which types of tissue will be cut by the burr, so the robot arm mounted with the OPD can stop moving before the burr encounters the vital anatomy (such as the spinal cord).; examiner is interpreting generating the control signal inherently required by the reference's system to stop the robot moving (see above citation - the reference's system stops the robot moving, and in the context of their computer control based robot, a control signal is inherently required for that to work) to fall within the broadest reasonable interpretation of an alert)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed utilize the real-time control of Dai with the bone density material analysis of Williamson, in order to improve the safety of the system ("The safety of the robot-assisted orthopedic surgery is thus improved", Dai, Section VI.).
Regarding Claim 21:
Williamson does not teach in particular, but Dai teaches:
automatically disabling the surgical robot when the alert is generated. (Section VI, the robot knows which types of tissue will be cut by the burr, so the robot arm mounted with the OPD can stop moving before the burr encounters the vital anatomy (such as the spinal cord).)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed utilize the real-time control of Dai with the bone density material analysis of Williamson, in order to improve the safety of the system ("The safety of the robot-assisted orthopedic surgery is thus improved", Dai, Section VI.).
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Williamson (T. M. Williamson et al., "Estimation of Tool Pose Based on Force–Density Correlation During Robotic Drilling," in IEEE Transactions on Biomedical Engineering, vol. 60, no. 4, pp. 969-976, April 2013) in view of Dai (Y. Dai, Y. Xue and J. Zhang, "Milling State Identification Based on Vibration Sense of a Robotic Surgical System," in IEEE Transactions on Industrial Electronics, vol. 63, no. 10, pp. 6184-6193, Oct. 2016), and further in view of Souza (US 20150348259 A1).
Regarding Claim 19:
Williamson in view of Dai does not teach in particular, but Souza teaches:
wherein the estimate of bone mineral density for the anatomical element is determined preoperatively as a dual-energy x-ray absorptiometry (DXA) t-score. (¶62 a statistical index such as a T-score or a Z-score is computed according to the BMD assessment data. This standardized information can be used to compare bone mineral content measurements obtained from the volume image with conventional BMD values obtained from a DXA system.)
It would have been obvious to one of ordinary skill in the art at the time the invention was filed utilize the T-score analysis of Souza with the bone density material analysis of Williamson as modified by Dai above, in order to provide improved tools for assessment, monitoring and 3-D visualization of BMD results from volume imaging data (Souza ¶14).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 BIJAN MAPAR whose telephone number is (571)270-3674. The examiner can normally be reached Monday - Thursday, 11:00-8:30.
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/BIJAN MAPAR/ Primary Examiner, Art Unit 2189
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