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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 2/4/2026 with claim set and remarks of 12/19/2025 has been entered.
Response to Amendment
This office action is responsive to the amendment filed on 12/19/2025. As directed by the amendment, the status of the claim(s) are:
Claim(s) 1, 14 has/have been amended;
Claim(s) 4 is/are cancelled;
Claim(s) 1-3, 5-21 is/are presently pending.
Response to Arguments
Applicant argues on p. 7 of remarks that Nair is teaching electrodes and so does not meet the amended claim limitation of “respective distinct treatment energies, each generated by respectively controllable energy sources”. After review this is not persuasive. Nair [0052] (emphasis added) teaches ““other embodiments may include any number of ablative elements positioned in any of a variety of arrangements along the body 120. The ablative element may employ any ablative method known in the art, including…lasers…laser ablators… the ablative element is configured to employ more than one type of ablative energy… the ablation catheter 110 employs multiple ablative elements capable of using different ablative energies. In some embodiments, the ablation catheter 110 may have multiple ablative elements that operate separately or in concert to form the desired lesions during an ablation procedure.” which would mean that Nair contemplates different energy settings for the different ablative elements which can include lasers and other ablative energy sources other than electrical/thermal energy delivered via electrodes.
Applicant further argues on p. 8 of remarks that Nair does not teach the recited “determining distinct compositions at spatially distinct portions of the same target”. After review, this is not persuasive. Nair teaches multiple imaging elements/sensors to analyze the target and specifically describes analyzing the different components within a target ([0010] “different tissue components”; [0011] “classification conditions stored in a data structure”; [0078] “various signal characteristics that may identify associated tissue types within and adjacent the scanned object…identify, in real-time, the various components of the scanned object 405. The signal analyzer logic 465 is configured to identify various types of tissue and/or tissue components and to provide an assessment…based on the type of tissues and/or tissue components identifies; [0086] “employs two imaging apparatuses positioned on either side of the ablative element…identifying different signal characteristics along each scan line allows for a correlation to the type of tissue and a certain level of ablation…different types of components and ablative effects within an object”; [0093]; [0094] “types of components within the object…determination as to the location of the corresponding tissue within the object…certain components may indicate a greater need for higher levels of ablation than others”). Each imaging elements/sensor provides a scan of the component of the target and so Nair meets the limitation because the imaging elements/sensor are spatially distinct from one another and the component is contemplated as being different within a target object; e.g. a imaging element/sensor identifies one component and the next adjacent imaging element/sensor identifies another component.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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, 5-8, 11-21 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Nair (US 20140180273 A1; 6/26/2014; cited in previous office action).
Regarding claim 1, Nair teaches an internet-enabled surgical control system ([0062] “network connection…downloading software”; [0216] “network”), comprising:
a feedback analyzer in operative communication with an internet-of-things (IoT) system that maintains a database library of composition characteristic data of anatomical tissue or calculi structures (Note, Wikipedia (https://en.wikipedia.org/wiki/Internet_of_things) defines internet of things as “Internet of things (IoT) describes devices with sensors, processing ability, software and other technologies that connect and exchange data with other devices and systems over the Internet or other communication networks.” which is how the claim term is interpreted; Fig. 1; Fig. 3; Fig. 10-11; Fig. 19; Fig.29b; [0010]; [0080]; [0093]; [0094] “type of vascular component…calcified-necrosis”; [0209]; [0062] “network connection…downloading software”; [0071] “plurality of databases and/or remotely located characterization application”; [0216] “network”), the feedback analyzer configured to:
receive a reflected signal from a target in response to electromagnetic radiation incident on the target (Fig. 1; Fig. 3; Fig. 10-11; Fig. 19; Fig.29b; [0010]; [0054] “electromagnetic radiation”; [0080]; [0093]; [0094] “type of vascular component…calcified-necrosis”; [0209]);
communicate with the IoT system to access the database library ([0062] “network connection…downloading software”; [0071] “plurality of databases and/or remotely located characterization application”; [0216] “network”); and
determine two or more distinct types of composition at two or more distinct portions of the same target using the received reflected signal and the composition characteristic data from the database library (Fig. 6 Fig. 12-14; [0010] “different tissue components”; [0011] “classification conditions stored in a data structure”; [0078] “various signal characteristics that may identify associated tissue types within and adjacent the scanned object…identify, in real-time, the various components of the scanned object 405. The signal analyzer logic 465 is configured to identify various types of tissue and/or tissue components and to provide an assessment…based on the type of tissues and/or tissue components identifies; [0086] “employs two imaging apparatuses positioned on either side of the ablative element…identifying different signal characteristics along each scan line allows for a correlation to the type of tissue and a certain level of ablation…different types of components and ablative effects within an object”; [0093]; [0094] “types of components within the object…determination as to the location of the corresponding tissue within the object…certain components may indicate a greater need for higher levels of ablation than others”; the reference is teaching using multiple imaging elements/sensors and so reads on the limitation); and
a controller circuit configured to generate a control signal to a treatment device to deliver respective distinct treatment energies, each generated by respectively controllable energy sources, to the two or more distinct portions of the same target based at least in part on the determined two or more distinct types of composition (Fig. 10-11; Fig. 19; Fig. 20b; Fig. 26; Fig.29b; [0052] “other embodiments may include any number of ablative elements positioned in any of a variety of arrangements along the body 120. The ablative element may employ any ablative method known in the art, including…lasers… the ablative element is configured to employ more than one type of ablative energy… the ablation catheter 110 employs multiple ablative elements capable of using different ablative energies. In some embodiments, the ablation catheter 110 may have multiple ablative elements that operate separately or in concert to form the desired lesions during an ablation procedure.”; [0093]-[0094]; [0143] “At least one electrode 1030 and at least one sensor 1035 may be positioned on at least one of the support arms 1025. The at least one electrode 1030 comprises an ablative element. The at least one electrode 1030 and at least one sensor 1035 will be described in further detail below with reference to FIGS. 26 and 27.”; [0209]; the reference is teaching using multiple imaging element/sensors with multiple ablation elements and so read on the limitation).
Regarding claim 2, Nair teaches wherein the treatment device is a laser system ([0052] “laser ablators”),
wherein the controller circuit is configured to generate the control signal to adjust a laser operating mode of the laser system based at least in part on the determined two or more distinct types of composition, and to deliver laser energy to the target in accordance with the laser operating mode (Fig. 10-11; Fig. 19; Fig.29b; [0093]-[0094]; [0209]).
Regarding claim 5, Nair teaches wherein the composition characteristic data includes composition spectral data (Fig. 9; [0054] “spectroscopy”; [0080] “spectroscopy”; [0093]-[0095]; [0209]),
wherein the feedback analyzer is associated with a spectroscopic sensor configured to collect spectral data from the received reflected signal, and the feedback analyzer is configured to determine the two or more distinct types of composition of the target based at least in part on a comparison between (i) the collected spectral data of the received reflected signal and (ii) the composition spectral data from the database library (Fig. 9; [0054] “spectroscopy”; [0080] “spectroscopy”; [0093]-[0095]; [0209]).
Regarding claim 6, Nair teaches wherein the database library is stored in a cloud computing and storage device of the IoT system ([0062] “network connection…downloading software”; [0071] “plurality of databases and/or remotely located characterization application”; [0216] “network”),
wherein the feedback analyzer is configured to access the database library via the cloud computing and storage device ([0062] “network connection…downloading software”; [0071] “plurality of databases and/or remotely located characterization application”; [0216] “network”).
Regarding claim 7, Nair teaches wherein to access the database library includes to receive therefrom cloud services ([0062] “network connection…downloading software”; [0071] “plurality of databases and/or remotely located characterization application”; [0216] “network”) including a target composition recognition algorithm ([0010]-[0011]; [0080]; [0093]-[0095]),
wherein the feedback analyzer is configured to determine the two or more distinct types of composition of the target ([0080]; [0093]-[0095]) using the cloud services (([0062] “network connection…downloading software”; [0071] “plurality of databases and/or remotely located characterization application”; [0216] “network”).
Regarding claim 8, Nair teaches wherein the target composition recognition algorithm includes an artificial-intelligence (AI) or machine-learning (ML) based algorithm for recognizing or classifying a target composition ([0093] “artificial neural network”).
Regarding claim 11, Nair teaches wherein to access the database library includes to receive therefrom ([0062] “network connection…downloading software”; [0071] “plurality of databases and/or remotely located characterization application”; [0216] “network”) information about respective setups of the treatment device corresponding to different types of composition ([0093]-[0095]; [0209]),
wherein the controller circuit is configured to generate the control signal to determine a setup of the treatment device using the received information about respective setups of the treatment device corresponding to the different types of composition, and to deliver the treatment to the target in accordance with the determined setup (Fig. 10-11; Fig. 19; Fig.29b; [0093]-[0095]; [0209]).
Regarding claim 12, Nair teaches wherein the respective setups of the treatment device include respective laser operating modes of a laser system ([0052] “laser ablators”) corresponding to the different types of composition (Fig. 10-11; Fig. 19; Fig.29b; [0093]-[0095]; [0209]).
Regarding claim 13, Nair teaches wherein to access the database library includes to receive therefrom cloud services of remote monitoring and maintenance of one or more the feedback analyzer or the controller circuit ([0062] “network connection…downloading software”; [0071] “plurality of databases and/or remotely located characterization application”; [0216] “network”).
Regarding claim 14, Nair teaches a method of controlling an internet-enabled surgical system ([0062] “network connection…downloading software”; [0216] “network”), the method comprising:
directing electromagnetic radiation at a target (Fig. 1; Fig. 3; Fig. 10-11; Fig. 19; Fig.29b; [0010]; [0054] “electromagnetic radiation”; [0080]; [0093]; [0094] “type of vascular component…calcified-necrosis”; [0209]);
receiving a reflected signal from the target in response to the electromagnetic radiation at the target (Fig. 1; Fig. 3; Fig. 10-11; Fig. 19; Fig.29b; [0010]; [0054] “electromagnetic radiation”; [0080]; [0093]; [0094] “type of vascular component…calcified-necrosis”; [0209]);
establishing a communication between a feedback analyzer and an internet-of-things (IoT) system and accessing a database library of composition characteristic data of anatomical tissue or calculi structures in the IoT system (Note, Wikipedia (https://en.wikipedia.org/wiki/Internet_of_things) defines internet of things as “Internet of things (IoT) describes devices with sensors, processing ability, software and other technologies that connect and exchange data with other devices and systems over the Internet or other communication networks.” which is how the claim term is interpreted; Fig. 1; Fig. 3; Fig. 10-11; Fig. 19; Fig.29b; [0010]; [0080]; [0093]; [0094] “type of vascular component…calcified-necrosis”; [0209]; [0062] “network connection…downloading software”; [0071] “plurality of databases and/or remotely located characterization application”; [0216] “network”);
determining two or more distinct types of composition at two or more distinct portions of the same target using the received reflected signal and the composition characteristic data from the database library (Fig. 6; Fig. 12-14; [0010] “different tissue components”; [0011] “classification conditions stored in a data structure”; [0078] “various signal characteristics that may identify associated tissue types within and adjacent the scanned object…identify, in real-time, the various components of the scanned object 405. The signal analyzer logic 465 is configured to identify various types of tissue and/or tissue components and to provide an assessment…based on the type of tissues and/or tissue components identifies; [0086] “employs two imaging apparatuses positioned on either side of the ablative element…identifying different signal characteristics along each scan line allows for a correlation to the type of tissue and a certain level of ablation…different types of components and ablative effects within an object”; [0093]; [0094] “types of components within the object…determination as to the location of the corresponding tissue within the object”; the reference is teaching using multiple imaging elements/sensors and so reads on the limitation); and
generating, via a controller circuit, a control signal to a treatment device to deliver respective distinct treatment energies, each generated by respectively controllable energy sources, to the two or more distinct portions of the same target based at least in part on the determined two or more distinct types of composition (Fig. 10-11; Fig. 19; Fig. 20b; Fig. 26; Fig.29b; [0052] “other embodiments may include any number of ablative elements positioned in any of a variety of arrangements along the body 120. The ablative element may employ any ablative method known in the art, including…lasers… the ablative element is configured to employ more than one type of ablative energy… the ablation catheter 110 employs multiple ablative elements capable of using different ablative energies. In some embodiments, the ablation catheter 110 may have multiple ablative elements that operate separately or in concert to form the desired lesions during an ablation procedure.”; [0093]-[0094]; [0143] “At least one electrode 1030 and at least one sensor 1035 may be positioned on at least one of the support arms 1025. The at least one electrode 1030 comprises an ablative element. The at least one electrode 1030 and at least one sensor 1035 will be described in further detail below with reference to FIGS. 26 and 27.”; [0209]; the reference is teaching using multiple imaging element/sensors with multiple ablation elements and so read on the limitation).
Regarding claim 15, Nair teaches wherein the treatment includes surgical laser treatment ([0052] “laser ablators”), the method further comprising, in response to the control signal:
adjusting a laser operating mode based at least in part on the determined two or more distinct types of composition; and delivering, via the treatment device, laser energy to the target in accordance with the laser operating mode (Fig. 10-11; Fig. 19; Fig.29b; [0093]-[0094]; [0209]).
Regarding claim 16, Nair teaches wherein the composition characteristic data includes composition spectral data, the method further comprising collecting spectral data from the received reflected signal using a spectroscopic sensor (Fig. 9; [0054] “spectroscopy”; [0080] “spectroscopy”; [0093]-[0095]; [0209]),
wherein determining the two or more distinct types of composition of the target is based at least in part on a comparison between (i) the collected spectral data of the received reflected signal and (ii) the composition spectral data from the database library (Fig. 9; [0054] “spectroscopy”; [0080] “spectroscopy”; [0093]-[0095]; [0209]).
Regarding claim 17, Nair teaches wherein accessing the database library includes receiving therefrom cloud services ([0062] “network connection…downloading software”; [0071] “plurality of databases and/or remotely located characterization application”; [0216] “network”) including a target composition recognition algorithm ([0010]-[0011]; [0080]; [0093]-[0095]),
wherein determining the two or more distinct types of composition of the target includes using the cloud services ([0080]; [0093]-[0095]) using the cloud services (([0062] “network connection…downloading software”; [0071] “plurality of databases and/or remotely located characterization application”; [0216] “network”).
Regarding claim 18, Nair teaches wherein the target composition recognition algorithm includes an artificial-intelligence (AI) or machine-learning (ML) based algorithm for recognizing or classifying a target composition ([0093] “artificial neural network”).
Regarding claim 19, Nair teaches wherein accessing the database library includes receiving therefrom ([0062] “network connection…downloading software”; [0071] “plurality of databases and/or remotely located characterization application”; [0216] “network”) information about respective setups of the treatment device corresponding to different types of composition ([0093]-[0095]; [0209]), the method including, in response to the control signal:
determining a setup of the treatment device using the information about respective setups of the treatment device corresponding to the different types of composition (Fig. 10-11; Fig. 19; Fig.29b; [0093]-[0095]; [0209]); and
delivering, via the treatment device, the treatment to the target in accordance with the determined setup (Fig. 10-11; Fig. 19; Fig.29b; [0093]-[0095]; [0209]).
Regarding claim 20, Nair teaches wherein accessing the database library includes receiving therefrom cloud services including remote monitoring and maintenance of one or more the feedback analyzer or the controller circuit of the internet-enabled surgical system ([0062] “network connection…downloading software”; [0071] “plurality of databases and/or remotely located characterization application”; [0216] “network”).
Regarding claim 21, Nair teaches wherein the two or more distinct compositions include distinct first and second compositions of respective first and second portions within the same target ([0010] “different tissue components”; [0011] “classification conditions stored in a data structure”; [0086] “employs two imaging apparatuses positioned on either side of the ablative element…identifying different signal characteristics along each scan line allows for a correlation to the type of tissue and a certain level of ablation”; [0093]; [0094] “types of components within the object…determination as to the location of the corresponding tissue within the object”; the reference is teaching using multiple imaging elements/sensors and so reads on the limitation),
wherein the controller circuit is configured to generate a control signal causing the treatment device to deliver a treatment to the first portion while the feedback analyzer analyzes and determines the second composition of the second portion (Fig. 6-7; Fig. 10; Fig. 12-14; [0052] “other embodiments may include any number of ablative elements positioned in any of a variety of arrangements along the body 120. The ablative element may employ any ablative method known in the art, including…lasers… the ablation catheter 110 employs multiple ablative elements capable of using different ablative energies. In some embodiments, the ablation catheter 110 may have multiple ablative elements that operate separately or in concert to form the desired lesions during an ablation procedure.”; [0094] “types of components within the object…determination as to the location of the corresponding tissue within the object”; [0104] “Depending upon the real-time score, the user and/or the processor 220 (shown in FIG. 1) may decide to continue ablative therapy at the same level of ablative energy, reduce the level of ablative energy, increase the level of ablative energy, or discontinue ablative therapy at that location. The score may also be recorded and stored in the memory 245, and later used to create an anatomical mapping of the ablation procedure. In one example, the user may set the desired score to a specific number, i.e. 6, and the system will continue ablation in a ROI until the score 6 is reached without user input.”; [0105] “the tissue characterization 485 may output a tissue characterization of the object 405 as a vascular plaque 600 containing a focal area of calcification 605. Based on the tissue characterization 485 and/or the ablation assessment 755 (shown in FIG. 11), the user and/or the system 400 may alter the level of ablation applied next to the object 405. In some embodiments, the system may accomplish this by appropriately tuning the ablative element 180 and/or the amount of energy provided by the ablation source 225 (shown in FIG. 1). For example, in FIG. 6, once the tissue characterization of an area of calcification was reported by the characterization application 250, the user and/or the processor 220 may increase the level of ablative energy emitted from the ablative element 180 in order to more effectively ablate the calcified area 605.”; [0106]-[0108]; [0205] “the imaging apparatus 980, the characterization application 250, and the sensors 1035, 1040 to create a closed feedback loop wherein the processor 220 continuously or intermittently refines the treatment plan and application of thermal energy by directing an individual electrode or a particular combination of electrodes to deliver a particular type, magnitude, and duration of thermal energy depending upon the data received from the sensors 1035, 1040, the imaging apparatus 980, and the characterization application 250.”; [0209] “feedback”; the reference is teaching using imaging elements/sensors to characterize tissue and modify ablation in a feedback loop and so reads on the limitation.).
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) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nair as applied to claim 2 above, in view of Chia (US 20150289937 A1; 10/15/2015; cited in previous office action).
Regarding claim 3, Nair does not teach a multi-fiber accessory configured to direct one or more of the electromagnetic radiation or the laser energy via respective fibers. However, Chia teaches in the same field of endeavor (Abstract; Fig. 1) a multi-fiber accessory configured to direct one or more of the electromagnetic radiation or the laser energy via respective fibers (Fig. 2; [0031] “laser…optical fiber”; [0057] “imaging fiber”). Thus it would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Nair to include these features as taught by Chia because this enables delivering of laser for ablation and electromagnetic radiation for tissue characterization (Fig. 1-2; [0031]; [0057]).
Claim(s) 9-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nair as applied to claim 8 above, in view of McLaughlin (US 20190290210 A1; 9/26/2019; cited in previous office action).
Regarding claim 9, Nair does not teach wherein the AI or ML based algorithm includes a trained ML model being trained by an ML engine in the cloud computing and storage device using a training dataset comprising the composition characteristic data stored in the database library. However, McLaughlin teaches in the same field of endeavor ([0045]) wherein the AI or ML based algorithm includes a trained ML model being trained by an ML engine in the cloud computing and storage device using a training dataset comprising the composition characteristic data stored in the database library (Fig. 4; [0067]-[0068]; [0095]). Thus it would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Nair to include these features as taught by McLaughlin because this enables using diverse data set to avoid systematic biases ([0095]).
Regarding claim 10, the combination of Nair and McLaughlin teaches wherein the training dataset includes composition spectral data of anatomical tissue or calculi structures collected from a patient population (Nair [0093]-[0095]; McLaughlin [0045]; [0067]-[0068]; [0095]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Rauniyar (US 20180325619 A1; issued as US 10881482 B2) teaches in claim 12 "wherein the object includes one or more stones, the characteristic includes a measure of stone burden, stone size, or stone burden associated with the one or more stones, and the computer application is configured to modify the control signal based on the measure; and wherein the characteristic includes a composition of the one or more stones, and the computer application is configured to further modify the control signal based on the composition."
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/JONATHAN T KUO/Primary Examiner, Art Unit 3792
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