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 § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 2, 7-10, 16, 26 and 27 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Sjolund, et al (U.S. Patent Application Publication 2015/0367145 A1).
Regarding claim 1, Sjolund discloses a quality assurance method (paragraph 0047) comprising:
Obtaining status information of a medical device (paragraph 0047);
Obtaining a target plan of a target subject (paragraph 0047);
Determining a prediction result based on the status information of the medical device and the target plan (paragraph 0047); and determining whether a quality assurance test is passed based on the prediction result (paragraph 0047; “if OARs receive too much radiation under an initial dose plan, the initial dose plan may be rejected).
Regarding claim 2, Sjolund discloses wherein the state of the medical device includes at least one of beam information corresponding to a plurality of dose rates, positioning accuracy information of at least one component of the medical device, or operational error information of the at least one component of the medical device (paragraphs 0047-0052).
Regarding claim 7, Sjolund discloses wherein
The target subject includes a plurality of regions of interest (paragraph 0045);
The prediction result includes dose distributions corresponding to the plurality of ROIs respectively (paragraphs 0045-0046); and
The determining whether a quality assurance test passes based on the prediction result comprises:
Determining a weight corresponding to each ROI of the plurality of ROIs (paragraphs 0045-0046); and
Determining whether the quality assurance passes based on the weights and the dose distributions corresponding to the plurality of ROIs respectively (paragraphs 0045-0047).
Regarding claim 8, Sjolund discloses wherein the determining a prediction result based on the state of the medical device and the target plan of the target subject comprises:
Determining the prediction result based on the state of the medical device and the target subject using a first model, wherein the first model is a machine learning model (paragraph 0109); and
The prediction result includes at least one of a predicted image of the target subject, a gamma passing rate, or a dose distribution (paragraph 0109).
Regarding claim 9, Sjolund discloses, in response to determining that the quality assurance test does not pass based on the prediction result, determining a reason that the quality assurance test does not pass based on the state of the medical device, the target plan of the target subject, and the prediction result using a second model (paragraph 0047).
Regarding claim 10, Sjolund discloses, adjusting, based on the reason that the quality assurance test does not pass, a value of a parameter associated with at least one of the medical device, the target plan, or a dose model (paragraph 0047);
Determining an updated prediction result based on an adjusted value of the parameter using the first model (paragraph 0030);
Determining whether the quality assurance test passes based on the updated prediction result (paragraph 0030); and
In response to determining that the quality assurance test passes, controlling the medical device to treat or scan the target subject according to an updated target plan, wherein the updated target plan is determined based on the adjusted value of the parameter (paragraph 0030).
Regarding claim 16, Sjolund discloses wherein the data set is determined based on a plurality of sample plans (paragraph 0047).
Regarding claim 26, Sjolund discloses wherein the prediction result includes at least a dose distribution (DVH); the method further comprising determining, based on the prediction result, a reason that the quality assurance test does not pass (paragraph 0047 – the dose in an OAR is too high) and a target adjustment mode for adjusting at least one or a parameter associated with at least one of the medical device, the target plan, or a dose model (paragraph 0047).
Regarding claim 27, the state of the medical device which corresponds to the DVH, relates to an operation state of the medical device (i.e. the configuration of the medical device being such that a particular dose is applied to a given volume).
Response to Arguments
Applicant's arguments filed 07/07/2026 have been fully considered but they are not persuasive. Applicant first argues that Sjolund does not teach a “state of a medical device” because Sjolund’s DVH (Dose Volume Histogram) is different from medical device hardware status. This is not persuasive, because claim 1 does not recite a “medical device hardware status” but rather merely “status information of a medical device.” The Dose Volume Histogram, containing information about the dose that the medical device applies, thus also contains information about the device’s current configuration to deliver a certain dose. This information falls within the broad recitation of “status information of a medical device.” Second, Applicant argues that Sjolund does not disclose the step of using an independently obtained device state together with a target plan to produce a prediction result. This is not persuasive, because Sjolund teaches, at paragraph 0047, using an objective parameter (i.e. a state of the device) to predict DVHs that are used to form a target plan and predict the dose that will be provided to each OAR. A quality assurance test is performed by checking the predicted dose provided to each OAR under the treatment plan, and the plan is rejected if the dose is too high. Thus, contrary to Applicant’s final assertion, Sjolund does teach a “quality assurance test” (or “quality assurance process” in the words of paragraph 0047) that determines pass/fail based on the prediction result (whether or not the predicted dose is too high in a given OAR).
Allowable Subject Matter
Claims 3,4, 5, 12, 13, 18, 21-25 are 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.
Conclusion
THIS ACTION IS MADE FINAL. 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 MICHAEL P MASKELL whose telephone number is (571)270-3210. The examiner can normally be reached M-F 10A-6P.
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/MICHAEL MASKELL/Primary Examiner, Art Unit 2878 19 September 2026
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