Prosecution Insights
Last updated: April 19, 2026
Application No. 18/723,146

PATIENT POSITIONING APPARATUS FOR A RADIOTHERAPY SYSTEM

Non-Final OA §103
Filed
Jun 21, 2024
Examiner
GUNBERG, EDWIN C
Art Unit
2884
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Elekta Beijing Medical Systems Co. Ltd.
OA Round
1 (Non-Final)
78%
Grant Probability
Favorable
1-2
OA Rounds
2y 6m
To Grant
84%
With Interview

Examiner Intelligence

Grants 78% — above average
78%
Career Allow Rate
481 granted / 618 resolved
+9.8% vs TC avg
Moderate +7% lift
Without
With
+6.7%
Interview Lift
resolved cases with interview
Typical timeline
2y 6m
Avg Prosecution
22 currently pending
Career history
640
Total Applications
across all art units

Statute-Specific Performance

§101
2.1%
-37.9% vs TC avg
§103
51.8%
+11.8% vs TC avg
§102
30.0%
-10.0% vs TC avg
§112
13.0%
-27.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 618 resolved cases

Office Action

§103
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. Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Saracen et al. (2005/0228255) in view of Chen et al. (CN 110152211 A)(cited by Applicant). Regarding claim 1, Saracen teaches a method for calibrating a radiotherapy patient positioning apparatus, the radiotherapy patient positioning apparatus comprising: a patient support surface; (Saracen, couch 110) a sensor for measuring a position of the patient support surface; (Saracen, sensor system 150) a movement mechanism for moving the patient support surface (Saracen, actuators 160); Saracen lacks explicit teaching of an encoder for encoding an internal position of the movement mechanism, wherein a smallest change of the internal position that the encoder is able to resolve causes a positional change in the patient support surface that is smaller than the smallest change in position of the patient support surface that the sensor is able to resolve, the method comprising: taking one or more readings from the sensor and encoder at a first position of the patient support surface; using the movement mechanism to move the patient support surface to a second position and taking one or more readings from the sensor and encoder at the second position; and analyzing the one or more readings from the sensor and encoder at the first position of the patient support surface and the one or more readings from the sensor and encoder at the second position of the patient support surface to determine a relationship between each of the encoder readings and the respective positions of the patient support surface. Chen teaches an encoder for encoding an internal position of the movement mechanism (Chen, absolute encoder 10), wherein a smallest change of the internal position that the encoder is able to resolve causes a positional change in the patient support surface that is smaller than the smallest change in position of the patient support surface that the sensor is able to resolve, the method comprising: taking one or more readings from the sensor and encoder at a first position of the patient support surface; Chen, “he absolute encoder 10, which is mounted on the six joint medical robot arm, angle or position the real-time data transmission of each joint to the controller 11 in the detection result of the absolute encoder 10 is not affected by the mechanical arm transmission system error, can effectively improve the absolute positioning accuracy of medical mechanical arm end”) using the movement mechanism to move the patient support surface to a second position and taking one or more readings from the sensor and encoder at the second position; and analyzing the one or more readings from the sensor and encoder at the first position of the patient support surface and the one or more readings from the sensor and encoder at the second position of the patient support surface to determine a relationship between each of the encoder readings and the respective positions of the patient support surface. (Chen, throughout, most concisely summarized in claim 3) It would have been obvious to one of ordinary skill in the art before the filing date of the claimed invention to use the correction system of Chen to enhance the robotic patient motion system of Saracen in order to increase the precision thereof. (Chen, “by changing the medical mechanical arm joint angle of 2-3 to obtain the simulation result under different pose state; at the same time, the finite element simulation used in the joint angle and the patient weight parameter into the compliance error model to calculate to obtain the medical robot arm as shown in FIG. 7” note that despite translation issues, it is noted that the matrix mathematics shown require modeled or sensed data for several locations to populate the matrix.) Regarding claim 2, the combination of Saracen and Chen further teaches the method further comprises: using the movement mechanism to move the patient support surface to a third position; making a first estimate of the third position, the first estimate based on at least one of the one or more readings from the sensor; using the determined relationship to make a second estimate of the third position, the second estimate based on at least one of the one or more readings from the encoder; and comparing the first estimate and the second estimate of the third position. (implied in Chen: for the mathematics to work sufficient data must be taken to populate the response matrix for the system – this is necessarily at least as many datapoints as parameters, certainly more than three) Regarding claim 5, the combination of Saracen and Chen further teaches the sensor is arranged to measure an absolute position of the patient support surface along a linear track. (Saracen, [0042], the disclosed three-axis sensor system is fully capable of detecting the linear position of the support surface) Regarding claim 6, the combination of Saracen and Chen further teaches the sensor is arranged to measure an absolute rotational position of the patient support surface. (Saracen, [0042]) Regarding claim 7, the combination of Saracen and Chen further teaches the sensor is arranged to measure the absolute rotational position of the patient support surface with respect to the direction of gravity towards earth. (Saracen, [0042]) Regarding claim 8, the combination of Saracen and Chen further teaches the sensor includes an inclinometer. (Saracen, [0042], note that determination of the absolute position of an object that translates and rotates in three dimensions – see Saracen, [0059] definitionally includes an inclinometer as the sensor measures the position and orientation of the object) Regarding claim 9, the combination of Saracen and Chen further teaches determining the relationship between each of the encoder readings and the respective positions the output of the encoder and the position of the patient support surface comprises determining at least one parameter, the at least one parameter being representative of a characteristic of the radiotherapy patient positioning apparatus. (Chen, calculations include rotational position of all arm joints, derivation of deflection amounts due to force applied to the end of the arm, etc.) Regarding claim 10, the combination of Saracen and Chen further teaches the at least one parameter comprises a plurality of parameters, each parameter being representative of a respective characteristic of the radiotherapy patient support positioning apparatus. (id.) Regarding claim 11, the combination of Saracen and Chen further teaches the method further comprises; taking one or more readings from the sensor and encoder at a plurality of positions, wherein the number of positions of the plurality of positions is equivalent to at least the number of parameters of the plurality of parameters. (implied in Chen: for the mathematics to work sufficient data must be taken to populate the response matrix for the system – this is necessarily at least as many datapoints as parameters) Regarding claim 12, the combination of Saracen and Chen further teaches the at least one parameter is representative of a characteristic of the movement mechanism. (id.) Regarding claim 13, the combination of Saracen and Chen further teaches the characteristic is at least one of: movement mechanism backlash or encoder offset. (Chen, calculations include rotational position of all arm joints, derivation of deflection amounts due to force applied to the end of the arm, etc., which appear equivalent to the claimed parameters) Regarding claim 14, the combination of Saracen and Chen teaches a system comprising: a radiotherapy apparatus, the radiotherapy apparatus comprising: a patient support surface; a sensor configured to measure a position of the patient support surface; a movement mechanism configured to move the patient support surface; an encoder configured to encode an internal position of the movement mechanism; a processor; and memory, with instructions stored thereon which, when performed by the processor, cause the processor to: memory, with instructions stored thereon which, when performed by the processor, cause the processor to: take one or more readings from the sensor and the encoder at a first position of the patient support surface; cause the movement mechanism to move the patient support surface to a second position; take one or more readings from the sensor and the encoder at the second position; and analyze the one or more readings from the sensor and encoder at the first position and the one or more readings from the sensor and encoder at the second position to determine a relationship between each of the encoder readings and the respective positions of the patient support surface. (See above with respect to claim 1) Regarding claim 15, the combination of Saracen and Chen teaches a non-transitory computer-readable medium containing instructions that, when executed by a processor, cause a radiotherapy systemtake one or more readings from a sensor and an encoder of the radiotherapy system at a first position of a patient support surface of the radiotherapy system;cause a movement mechanism of the radiotherapy system to move the patient support surface to a second position;take one or more readings from the sensor and the encoder at the second position; andanalyze the one or more readings from the sensor and encoder at the first position and the one or more readings from the sensor and encoder at the second position to determine a relationship between each of the encoder readings and the respective positions of the patient support surface. (See above with respect to claim 1) Regarding claim 16, the combination of Saracen and Chen further teaches a smallest change of the internal position that the encoder is able to resolve causes a positional change in the patient support surface that is smaller than the smallest change in the patient support surface that the sensor is able to resolve. (Chen, “The absolute encoder 10, which is mounted on the six joint medical robot arm, angle or position the real-time data transmission of each joint to the controller 11 in the detection result of the absolute encoder 10 is not affected by the mechanical arm transmission system error, can effectively improve the absolute positioning accuracy of medical mechanical arm end”) Regarding claim 17, the combination of Saracen and Chen further teaches the instructions further cause the processor to:cause the movement mechanism to move the patient support surface to a third position; make a first estimate of the third position based at least in part on at least one of the one or more readings from the sensor; use the determined relationship to make a second estimate of the third position, wherein the second estimate is based at least in part on at least one of the one or more readings from the encoder; and compare the first estimate and the second estimate of the third position. (implied in Chen: for the mathematics to work sufficient data must be taken to populate the response matrix for the system – this is necessarily at least as many datapoints as parameters, certainly more than three) Regarding claim 19, the combination of Saracen and Chen further teaches a smallest change of an internal position of the movement mechanism that the encoder is able to resolve causes a positional change in the patient support surface that is smaller than the smallest change in the patient support surface that the sensor is able to resolve. (Chen, “he absolute encoder 10, which is mounted on the six joint medical robot arm, angle or position the real-time data transmission of each joint to the controller 11 in the detection result of the absolute encoder 10 is not affected by the mechanical arm transmission system error, can effectively improve the absolute positioning accuracy of medical mechanical arm end”) Regarding claims 3, 4, 18, and 20, the combination of Saracen and Chen further teaches the calculation of the error between the actual position of the object and its intended position. (Chen, “the maximal phase difference of two groups of data does not exceed 0.3mm, i.e., performing error compensation, medical robot arm under the gravity and the influence of 1000N load, any pose axis direction location error maximum error is not more than ±0.3mm, which effectively improves the locating precision of the mechanical arm.”) It would therefore be obvious to one of ordinary skill in the art before the filing date of the claimed invention to notify the user in a circumstance when the positional deviation of the patient support system is greater than some acceptable threshold in order to ensure patient safety. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to EDWIN C GUNBERG whose telephone number is (571)270-3107. The examiner can normally be reached Monday-Friday, 8:30AM-5:00PM. 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, Uzma Alam can be reached at 571-272-2995. 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. /EDWIN C GUNBERG/Primary Examiner, Art Unit 2884
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Prosecution Timeline

Jun 21, 2024
Application Filed
Mar 21, 2026
Non-Final Rejection — §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

1-2
Expected OA Rounds
78%
Grant Probability
84%
With Interview (+6.7%)
2y 6m
Median Time to Grant
Low
PTA Risk
Based on 618 resolved cases by this examiner. Grant probability derived from career allow rate.

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