Prosecution Insights
Last updated: August 17, 2026
Application No. 18/288,693

IMPROVED SYSTEMS AND METHODS OF NAVIGATING A MEDICAL DEVICE IN A BODY LUMEN USING FUZZY LOGIC COMBINED WITH DEVICE PARAMETERS, DIRECT USER INPUTS, AND DISTRIBUTED ANONYMIZED DATA

Non-Final OA §103
Filed
Oct 27, 2023
Priority
May 27, 2021 — provisional 63/194,119 +1 more
Examiner
CATTUNGAL, SANJAY
Art Unit
3798
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Covidien L.P.
OA Round
3 (Non-Final)
83%
Grant Probability
Favorable
3-4
OA Rounds
3m
Est. Remaining
95%
With Interview

Examiner Intelligence

Grants 83% — above average
83%
Career Allowance Rate
865 granted / 1038 resolved
+13.3% vs TC avg
Moderate +11% lift
Without
With
+11.3%
Interview Lift
resolved cases with interview
Typical timeline
3y 1m
Avg Prosecution
19 currently pending
Career history
1062
Total Applications
across all art units

Statute-Specific Performance

§101
2.0%
-38.0% vs TC avg
§103
35.8%
-4.2% vs TC avg
§102
30.3%
-9.7% vs TC avg
§112
6.6%
-33.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1038 resolved cases

Office Action

§103
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 . Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 05/04/26 has been entered. Response to Arguments Applicant's arguments filed 05/04/26 have been fully considered but are moot in view of new grounds of rejection. Applicant argues that Popovic does not teach the newly claimed limitation “determining multiple candidate paths using machine learning; displaying candidate paths and selecting a candidate path”. Examiner would like to point out that Sganga para 0090 teaches using machine learning model for determining multiple candidate paths and selecting one of the paths, as such meets claim limitations and the rejection is made FINAL. 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. Claim(s) 1-5, and 15-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over U. S. Patent No. 10182704 to Popovic in view of U. S. Publication No. 2018/0235561 to Lavi et al. Regarding claims 1, and 15, Popovic teaches a method comprising: receiving image data corresponding to a branched structure; receiving procedure information (Figs. 1, 2, 5 and 6 teaches receiving procedure information); determining possible navigation paths for navigating a medical device within the branched structure to a target for medical procedure and the procedure information (abstract and figs. 1- teaches multiple navigation paths). Popovic does not expressly teaches using machine learning model to determine possible navigation paths and displaying the possible navigation paths and controls for user selection of one of the plurality of possible navigation paths. Lavi teaches using machine learning model to determine possible navigation paths and displaying the possible navigation paths and controls for user selection of one of the plurality of possible navigation paths (para 063, 71, 72, 084-087 and 136 and figs. 1, 2, 3a and 3b teaches a machine learning/ artificial intelligence algorithm to determine the best pathways for selection by the user). It would be obvious to one of ordinary skill in the art at the time of filing to modify Popovic with a setup of using machine learning model for determining multiple candidate paths as taught by Lavi since such a setup would result in precise planning of the navigation path. Regarding Claim 2, Popovic teaches all of the above claimed limitations but does not expressly teach that the procedure information includes medical device physical characteristics, medical device physical behaviors, tissue information, previous procedure data, published peer-reviewed results or path tortuosity (col. 3 lines 15-30 teaches vascular tortuosity as a physical behavior). Regarding claim 3, Popovic teaches displaying maximum distances of the possible navigation paths (col. 6 lines 57-63 teaches distance between nodes of a path). Regarding claim 4, Popovic teaches device physical characteristics include bend radius, stiffness for axial or transverse loads applied to a distal end portion of the medical device, multiplanar or single planar behavior, articulating section length, or number of articulation joints (col. 3 lines 48-56 teaches number of articulating joints). Regarding claim 5, Popovic teaches determining a probability of success for navigation from all of the possible navigation paths for navigation based on physical characteristics of the medical device and tissue information; and displaying an indication of a probability for success for navigation for each path (fig. 2 and col. 7 lines 5-30 teaches multiple navigation paths, and an indication of success for the selected path). Regarding claims 16 and 17, Popovic teaches determining that a current procedure is ended; in response to determining that the current procedure is ended, prompt a current clinician to input procedure performance information of the current procedure; and store the current procedure performance information in association with the previous procedure information (figs. 1 and 2 shows endoscopic procedure). Regarding claims 18 and 19, Popovic teaches determining a control mode for the human-controlled medical device based on the preoperative image data (col. 2 lines 53-64 teaches preoperative data); and display a message requesting a current clinician to confirm whether to proceed in the control mode (col. 5 lines 55-65 teaches a display and figs. 1-3 teaches control of the endoscope). Regarding claim 20, Popovic teaches prompt a current clinician to input patient information relevant to a current procedure (col. 1 lines 66 through col. 2 line 20 teaches previous procedure data being acquired); receive patient information; and store the patient information in association with previous procedure information (col. 1 lines 66 through col. 2 line 20 teaches previous procedure data for planning). Allowable Subject Matter Claims 6-14 are allowed. The following is an examiner’s statement of reasons for allowance: the closest prior art of record are U. S. Patent No. 10182704 to Popovic; U. S. Patent No. 11147635 to Sganga et al.; U. S. Publication No. 2017/0018079 to Li none of the prior art alone or in combination teaches the limitations of the independent claim specifically “receiving image data; receiving procedure information; receiving previous clinician experience data; determining possible navigation plans for navigating a medical device within a branched structure based on the image data and the procedure information; determining, for each possible navigation plan, a score for a difficulty to a clinician of carrying out the possible navigation plan using machine learning based on previous clinician experience data; and displaying the score for each possible navigation plan”. Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.” Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to SANJAY CATTUNGAL whose telephone number is (571)272-1306. The examiner can normally be reached M-F 9-5 EST. 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, Keith Raymond can be reached at 571-270-1790. 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. /SANJAY CATTUNGAL/Primary Examiner, Art Unit 3798
Read full office action

Prosecution Timeline

Oct 27, 2023
Application Filed
May 20, 2025
Non-Final Rejection mailed — §103
Aug 20, 2025
Response Filed
Dec 03, 2025
Final Rejection mailed — §103
Feb 04, 2026
Response after Non-Final Action
May 04, 2026
Request for Continued Examination
May 06, 2026
Response after Non-Final Action
Jul 29, 2026
Non-Final Rejection mailed — §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
83%
Grant Probability
95%
With Interview (+11.3%)
3y 1m (~3m remaining)
Median Time to Grant
High
PTA Risk
Based on 1038 resolved cases by this examiner. Grant probability derived from career allowance rate.

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