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 .
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.
Claim(s) 1 – 18 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Saha et al. (US 2019/0180442) in view of Dougherty et al. (US 2019/0318484).
Regarding independent claim 1, Saha teaches a system (Figure 3) comprising:
a processor (paragraph 52: processing unit 322 of a computer 320) configured to:
access {1}a three-dimensional (3D) model{1} of an anatomical structure (paragraph 71: The airway wall association of a skeletal branch is computed using an airway wall model in {1}CT imaging{1} as follows: a dark tubular structure, i.e., airway lumen, surrounded by a bright boundary or airway wall. Let us consider {1}a boundary voxel p of the segmentation volume V{1});
apply {2}a first detection process{2} to the 3D model to detect {1}a single-layer anatomical feature{1} in the anatomical structure (paragraph 71: {1}The airway wall association of a skeletal branch is computed using an airway wall model{1} in CT imaging as follows: a dark tubular structure, i.e., airway lumen, surrounded by a bright boundary or airway wall. Let us consider a boundary voxel p of the segmentation volume V. . . . {1}This augmentation process is illustrated in FIG. 7 in 2-D, where cyan represents boundary pixels, while those in blue and magenta are the 6-neighbors and radially augmented pixels{1} . . . {2}The airway wall association of a branch is computed as the fractional count of its boundary voxels with AW A(•)>0.6; the threshold value was determined experimentally over augmented neighborhoods of manually selected valid branches{2});
apply {1}a second detection process{1}, different from the first detection process, to the 3D model to detect {2}a non-single-layer anatomical feature{2} in the anatomical structure (paragraph 65: Local change in airway volume at the current iteration {1}is determined using the airway segmentation volumes CAV of the previous iteration, the initial rough segmentation of airway V{1}, at the current iteration, and their centerlines SCAV and S,, respectively; paragraph 73: The last step of leakage correction is to augment {2}the confident airway volume CAV{2} and its skeleton SCAV· First, the valid airway tree skeleton SCAV of the previous iteration is expanded within S, using tree traversal, where expansions along individual skeletal paths are terminated if a leakage location is faced or a terminal voxel is reached. Finally, CAV is expanded); and
provide a representation of the anatomical structure based on the 3D model, the detected single-layer anatomical feature, and the detected non-single-layer anatomical feature (paragraph 99 and Figures 11A – 11D: Airway segmentation results on a CT image using the new method after different iterations are shown in FIG. 11; paragraph 100 and Figures 12A, 12B: An airway tree up to segmental level and two-generations beyond is shown in FIG. 12A. Branches at segmental level and two-generations beyond along the five anatomic airway paths, used in our experiments, are shown in FIG. 12B); and
a display communicatively coupled to the processor (paragraph 52: display 328 of a computer 320) and configured to display the representation of the anatomical structure (Figures 11A-11D, 12A, 12B). Saha does not expressly disclose a representation of a potential path to be traversed by a medical instrument in the anatomical structure, however Saha does disclose valid airway centerline branches (paragraph 62). Dougherty discloses obtaining a 3D medical imaging of airway models of a lung (paragraph 66) and it is also envisioned that a path (or projected path) of steerable catheter 600, a percutaneous needle, and/or other medical devices may also be illustrated on the displayed image(s) (paragraph 128), wherein navigation pathway 416 may be an optimal endobronchial path to a target tissue (paragraph 75). It would have been obvious for one of ordinary skill in the art at the time of the invention (pre-AIA ) or at the time of the effective filing date of the application (AIA ) to modify Saha's system to determine a projected path from the entry airway to a desired location in the airways models as taught by Dougherty that could utilize the centerline of the airway of Saha. One would be motivated to do so because this would help plan a surgical pathway that would help avoid tissue damage.
Regarding dependent claim 2, Saha teaches wherein: the representation of the anatomical structure represents the detected single-layer anatomical feature (paragraph 53: airway walls of lung). Saha does not expressly disclose the potential path avoids the detected single-layer anatomical feature. Dougherty discloses the initial segmentation 1200 includes the initial treelike structure 1202 and a nodule or target 1204 (such as the target tissue 420 described above) and in order to access the target 1204, the navigation system 70 can determine the pathway 1206 (e.g., an initial navigation pathway such as pathway 416 described above) through the airway tree to reach the target (paragraph 146). It would have been obvious for one of ordinary skill in the art at the time of the invention (pre-AIA ) or at the time of the effective filing date of the application (AIA ) to further modify Saha's and Dougherty’s systems to determine a projected path within the airway tree thus avoiding pathing through airway walls. One would be motivated to do so because this would help plan a surgical pathway that would help avoid tissue damage.
Regarding dependent claim 3, Saha teaches wherein: the representation of the anatomical structure represents the detected non-single-layer anatomical feature (paragraph 53: the confident airway volume (CAV) of the lung). Saha does not expressly disclose at least part of the potential path is within the detected non-single-layer anatomical feature. Dougherty discloses the initial segmentation 1200 includes the initial treelike structure 1202 and a nodule or target 1204 (such as the target tissue 420 described above) and in order to access the target 1204, the navigation system 70 can determine the pathway 1206 (e.g., an initial navigation pathway such as pathway 416 described above) through the airway tree to reach the target (paragraph 146). It would have been obvious for one of ordinary skill in the art at the time of the invention (pre-AIA ) or at the time of the effective filing date of the application (AIA ) to further modify Saha's and Dougherty’s systems to determine a projected path within the airway tree thus avoiding pathing through airway walls. One would be motivated to do so because this would help plan a surgical pathway that would help avoid tissue damage.
Regarding dependent claim 4, Saha teaches wherein: the single-layer anatomical feature comprises a lung fissure (paragraph 53: mapping airway walls of lung would also comprise lung fissures since lung fissures have a strong correlation with airway walls); and the non-single-layer anatomical feature comprises an airway (paragraph 53: the confident airway volume (CAV) of the lung).
Regarding dependent claim 5, Saha does not expressly disclose wherein the representation of the potential path to be traversed by the medical instrument in the anatomical structure represents a path to be traversed by the medical instrument to obtain a biopsy of a nodule of a lung. Dougherty discloses a user may desire additional treelike structure information extending to the nodule, for example for navigation to the nodule for biopsy or treatment (paragraph 134). It would have been obvious for one of ordinary skill in the art at the time of the invention (pre-AIA ) or at the time of the effective filing date of the application (AIA ) to achieve a predictable result of generating a projected path for biopsy or treatment by further modifying the Saha's and Dougherty’s systems that generate a projected path to a desired tissue location to replace the desired tissue location to be a desired tissue location for biopsy or treatment as taught by Dougherty, and the result would have been predictable.
Regarding dependent claim 6, the combination of Saha’s and Dougherty’s systems teaches wherein the processor is configured to generate, based on the 3D model, the detected single-layer anatomical feature, and the detected non-single-layer anatomical feature, the representation of the potential path to be traversed by the medical instrument in the anatomical structure (Saha, paragraph 99 and Figures 11A – 11D: Airway segmentation results on a CT image using the new method after different iterations are shown in FIG. 11; paragraph 100 and Figures 12A, 12B: An airway tree up to segmental level and two-generations beyond is shown in FIG. 12A. Branches at segmental level and two-generations beyond along the five anatomic airway paths, used in our experiments, are shown in FIG. 12B; Dougherty, paragraph 128: it is also envisioned that a path (or projected path) of steerable catheter 600, a percutaneous needle, and/or other medical devices may also be illustrated on the displayed image(s)). Saha does not expressly disclose wherein the processor is configured to generate the representation of the potential path avoiding the detected single-layer anatomical feature. Dougherty discloses the initial segmentation 1200 includes the initial treelike structure 1202 and a nodule or target 1204 (such as the target tissue 420 described above) and in order to access the target 1204, the navigation system 70 can determine the pathway 1206 (e.g., an initial navigation pathway such as pathway 416 described above) through the airway tree to reach the target (paragraph 146). It would have been obvious for one of ordinary skill in the art at the time of the invention (pre-AIA ) or at the time of the effective filing date of the application (AIA ) to further modify Saha's and Dougherty’s systems to determine a projected path within the airway tree thus avoiding pathing through airway walls. One would be motivated to do so because this would help plan a surgical pathway that would help avoid tissue damage.
Regarding dependent claim 7, Saha teaches wherein: the display is configured to display the representation of the anatomical structure in a graphical user interface (paragraph 99 and Figures 11A – 11D: Airway segmentation results on a CT image using the new method after different iterations are shown in FIG. 11; paragraph 100 and Figures 12A, 12B: An airway tree up to segmental level and two-generations beyond is shown in FIG. 12A. Branches at segmental level and two-generations beyond along the five anatomic airway paths, used in our experiments, are shown in FIG. 12B). Saha does not expressly disclose the processor is configured to receive, by way of the graphical user interface, user input defining the potential path to be traversed by the medical instrument in the anatomical structure. Dougherty discloses a user can select the target point using a graphical user interface, such as I/0 component 78 of the navigation system 70 (paragraph 134). It would have been obvious for one of ordinary skill in the art at the time of the invention (pre-AIA ) or at the time of the effective filing date of the application (AIA ) to achieve a predictable result of generating a projected path for biopsy or treatment by further modifying the Saha's and Dougherty’s systems that generate a projected path to a desired tissue location to replace the desired tissue location to be a desired tissue location from a user input as taught by Dougherty, and the result would have been predictable.
Regarding dependent claim 8, Saha does not expressly disclose wherein the graphical user interface presents one or more of: a representation of the single-layer anatomical feature to be avoided by the potential path to be traversed by the medical instrument in the anatomical structure; or a representation of the non-single-layer anatomical feature as a potential pathway of at least part of the potential path to be traversed by the medical instrument in the anatomical structure. Dougherty discloses the initial segmentation 1200 includes the initial treelike structure 1202 and a nodule or target 1204 (such as the target tissue 420 described above) and in order to access the target 1204, the navigation system 70 can determine the pathway 1206 (e.g., an initial navigation pathway such as pathway 416 described above) through the airway tree to reach the target (paragraph 146). It would have been obvious for one of ordinary skill in the art at the time of the invention (pre-AIA ) or at the time of the effective filing date of the application (AIA ) to further modify Saha's and Dougherty’s systems to determine a projected path within the airway tree thus avoiding pathing through airway walls. One would be motivated to do so because this would help plan a surgical pathway that would help avoid tissue damage.
Regarding independent claim 9, Saha teaches a non-transitory computer-readable medium storing instructions executable by a processor (paragraph 52: software executed on a computer system; paragraph 52: processing unit 322 of a computer 320) to:
access {1}a three-dimensional (3D) model{1} of an anatomical structure (paragraph 71: The airway wall association of a skeletal branch is computed using an airway wall model in {1}CT imaging{1} as follows: a dark tubular structure, i.e., airway lumen, surrounded by a bright boundary or airway wall. Let us consider {1}a boundary voxel p of the segmentation volume V{1});
apply {2}a first detection process{2} to the 3D model to detect {1}a single-layer anatomical feature{1} in the anatomical structure (paragraph 71: {1}The airway wall association of a skeletal branch is computed using an airway wall model{1} in CT imaging as follows: a dark tubular structure, i.e., airway lumen, surrounded by a bright boundary or airway wall. Let us consider a boundary voxel p of the segmentation volume V. . . . {1}This augmentation process is illustrated in FIG. 7 in 2-D, where cyan represents boundary pixels, while those in blue and magenta are the 6-neighbors and radially augmented pixels{1} . . . {2}The airway wall association of a branch is computed as the fractional count of its boundary voxels with AW A(•)>0.6; the threshold value was determined experimentally over augmented neighborhoods of manually selected valid branches{2});
apply {1}a second detection process{1}, different from the first detection process, to the 3D model to detect {2}a non-single-layer anatomical feature{2} in the anatomical structure (paragraph 65: Local change in airway volume at the current iteration {1}is determined using the airway segmentation volumes CAV of the previous iteration, the initial rough segmentation of airway V{1}, at the current iteration, and their centerlines SCAV and S,, respectively; paragraph 73: The last step of leakage correction is to augment {2}the confident airway volume CAV{2} and its skeleton SCAV· First, the valid airway tree skeleton SCAV of the previous iteration is expanded within S, using tree traversal, where expansions along individual skeletal paths are terminated if a leakage location is faced or a terminal voxel is reached. Finally, CAV is expanded); and
generate a representation of the anatomical structure based on the 3D model, the detected single-layer anatomical feature, and the detected non-single-layer anatomical feature (paragraph 99 and Figures 11A – 11D: Airway segmentation results on a CT image using the new method after different iterations are shown in FIG. 11; paragraph 100 and Figures 12A, 12B: An airway tree up to segmental level and two-generations beyond is shown in FIG. 12A. Branches at segmental level and two-generations beyond along the five anatomic airway paths, used in our experiments, are shown in FIG. 12B).
Saha does not expressly disclose generate a representation of a path to be traversed by a medical instrument in the anatomical structure. Dougherty discloses obtaining a 3D medical imaging of airway models of a lung (paragraph 66) and it is also envisioned that a path (or projected path) of steerable catheter 600, a percutaneous needle, and/or other medical devices may also be illustrated on the displayed image(s) (paragraph 128), wherein navigation pathway 416 may be an optimal endobronchial path to a target tissue (paragraph 75). It would have been obvious for one of ordinary skill in the art at the time of the invention (pre-AIA ) or at the time of the effective filing date of the application (AIA ) to modify Saha's system to determine a projected path from the entry airway to a desired location in the airways models as taught by Dougherty that could utilize the centerline of the airway of Saha. One would be motivated to do so because this would help plan a surgical pathway that would help avoid tissue damage.
The combination of Saha’s and Dougherty’s systems teaches provide, to a display communicatively coupled to the processor (Saha, paragraph 52: display 328 of a computer 320), the representation of the anatomical structure (Saha, Figures 11A-11D, 12A, 12B) and the representation of the path to be traversed by the medical instrument in the anatomical structure (Dougherty, Figures 18, 19).
Regarding claims 10 - 16, claims 10 - 16 are similar in scope as to claims 2 - 8, thus the rejections for claims 2 - 8 hereinabove are applicable to claims 10 - 16.
Regarding independent claim 17, Saha teaches a method performed by a computer processor (paragraph 52: software executed on a computer system; paragraph 52: processing unit 322 of a computer 320), the method comprising:
accessing {1}a three-dimensional (3D) model{1} of an anatomical structure (paragraph 71: The airway wall association of a skeletal branch is computed using an airway wall model in {1}CT imaging{1} as follows: a dark tubular structure, i.e., airway lumen, surrounded by a bright boundary or airway wall. Let us consider {1}a boundary voxel p of the segmentation volume V{1});
applying {2}a first detection process{2} to the 3D model to detect {1}a single-layer anatomical feature{1} in the anatomical structure (paragraph 71: {1}The airway wall association of a skeletal branch is computed using an airway wall model{1} in CT imaging as follows: a dark tubular structure, i.e., airway lumen, surrounded by a bright boundary or airway wall. Let us consider a boundary voxel p of the segmentation volume V. . . . {1}This augmentation process is illustrated in FIG. 7 in 2-D, where cyan represents boundary pixels, while those in blue and magenta are the 6-neighbors and radially augmented pixels{1} . . . {2}The airway wall association of a branch is computed as the fractional count of its boundary voxels with AW A(•)>0.6; the threshold value was determined experimentally over augmented neighborhoods of manually selected valid branches{2});
applying {1}a second detection process{1}, different from the first detection process, to the 3D model to detect {2}a non-single-layer anatomical feature{2} in the anatomical structure (paragraph 65: Local change in airway volume at the current iteration {1}is determined using the airway segmentation volumes CAV of the previous iteration, the initial rough segmentation of airway V{1}, at the current iteration, and their centerlines SCAV and S,, respectively; paragraph 73: The last step of leakage correction is to augment {2}the confident airway volume CAV{2} and its skeleton SCAV· First, the valid airway tree skeleton SCAV of the previous iteration is expanded within S, using tree traversal, where expansions along individual skeletal paths are terminated if a leakage location is faced or a terminal voxel is reached. Finally, CAV is expanded); and
generating a representation of the anatomical structure based on the 3D model, the detected single-layer anatomical feature, and the detected non-single-layer anatomical feature (paragraph 99 and Figures 11A – 11D: Airway segmentation results on a CT image using the new method after different iterations are shown in FIG. 11; paragraph 100 and Figures 12A, 12B: An airway tree up to segmental level and two-generations beyond is shown in FIG. 12A. Branches at segmental level and two-generations beyond along the five anatomic airway paths, used in our experiments, are shown in FIG. 12B).
Saha does not expressly disclose generating a representation of a path to be traversed by a medical instrument in the anatomical structure. Dougherty discloses obtaining a 3D medical imaging of airway models of a lung (paragraph 66) and it is also envisioned that a path (or projected path) of steerable catheter 600, a percutaneous needle, and/or other medical devices may also be illustrated on the displayed image(s) (paragraph 128), wherein navigation pathway 416 may be an optimal endobronchial path to a target tissue (paragraph 75). It would have been obvious for one of ordinary skill in the art at the time of the invention (pre-AIA ) or at the time of the effective filing date of the application (AIA ) to modify Saha's system to determine a projected path from the entry airway to a desired location in the airways models as taught by Dougherty that could utilize the centerline of the airway of Saha. One would be motivated to do so because this would help plan a surgical pathway that would help avoid tissue damage.
The combination of Saha’s and Dougherty’s systems teaches providing, to a display communicatively coupled to the processor (Saha, paragraph 52: display 328 of a computer 320), the representation of the anatomical structure (Saha, Figures 11A-11D, 12A, 12B) and the representation of the path to be traversed by the medical instrument in the anatomical structure (Dougherty, Figures 18, 19).
Regarding dependent claim 18, the combination of Saha’s and Dougherty’s systems teaches providing, to a computer-assisted surgical system, data representative of at least one of the 3D model (Saha, Figures 11A-11D, 12A, 12B), the detected single-layer anatomical feature (Saha, Figures 11A-11D, 12A, 12B), the detected non-single-layer anatomical feature (Saha, Figures 11A-11D, 12A, 12B), or the path to be traversed by the medical instrument in the anatomical structure (Dougherty, Figures 18, 19).
Regarding dependent claim 20, Saha teaches wherein: the representation of the anatomical structure represents the detected single-layer anatomical feature (paragraph 53: airway walls of lung) and the detected non-single-layer anatomical feature (paragraph 53: the confident airway volume (CAV) of the lung). Saha does not expressly disclose the path avoids the detected single-layer anatomical feature; and at least part of the path is within the detected non-single-layer anatomical feature. Dougherty discloses the initial segmentation 1200 includes the initial treelike structure 1202 and a nodule or target 1204 (such as the target tissue 420 described above) and in order to access the target 1204, the navigation system 70 can determine the pathway 1206 (e.g., an initial navigation pathway such as pathway 416 described above) through the airway tree to reach the target (paragraph 146). It would have been obvious for one of ordinary skill in the art at the time of the invention (pre-AIA ) or at the time of the effective filing date of the application (AIA ) to further modify Saha's and Dougherty’s systems to determine a projected path within the airway tree thus avoiding pathing through airway walls. One would be motivated to do so because this would help plan a surgical pathway that would help avoid tissue damage.
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Saha et al. (US 2019/0180442) in view of Dougherty et al. (US 2019/0318484) and Official Notice.
Regarding dependent claim 19, Saha does not expressly disclose wherein the medical instrument comprises a teleoperated catheter. Examiner takes Official Notice that the concept of remote teleoperated catheter is well known and expected in the art. It would have been obvious for one of ordinary skill in the art at the time of the invention (pre-AIA ) or at the time of the effective filing date of the application (AIA ) to achieve a predictable result of using a teleoperated catheter to further modify Sasha’s and Dougherty's systems that provides projected path for many medical devices by replacing a catheter with a teleoperated catheter, and the result would have been predictable.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JEFFREY J CHOW whose telephone number is (571)272-8078. The examiner can normally be reached 11AM-7PM.
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/JEFFREY J CHOW/Primary Examiner, Art Unit 2618