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.
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, 3-11, 13-17, and 20-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lu et al. (US 2017/0169566; hereinafter Lu) in view of Gopinath (US 2018/0085170) and Amis et al. (US 2021/0042927; hereinafter Amis).
Lu shows a medical system and method comprising: a catheter that includes a sensor and can be inserted into a luminal organ ([0026]-[0027]); a display apparatus ([0057], [0067]); and an image processing apparatus configured to: store a plurality of pieces of support information each related to a medical operation or diagnosis on the luminal organ and associated with a type of an object ([0037]-[0039]; Table 1), generate an image of the luminal organ based on a signal output from the sensor of the catheter ([0026], [0056], [0060]), input the generated image to a machine learning model and acquire an output indicating a type of an object that is present in the image ([0062]), acquire input information indicating a medical operation or diagnosis to be performed ([0057]), determine one of the pieces of support information corresponding to the type of the object and the medical operation or diagnosis indicated by the input information, and cause the display apparatus to display said one of the pieces of support information ([0057], [0067]).
Lu also shows wherein the image processing apparatus is configured to: store a plurality of application programs corresponding to the plurality of pieces of support information, and execute a corresponding one of the application programs for displaying said one of the pieces of support information ([0062]-[0067]); wherein the type of the object includes at least one of: an epicardium, a side branch, a vein, a guide wire, a stent, a plaque deviating into a stent, a lipid plaque, a fibrous plaque, a calcified portion, blood vessel dissociation, thrombus, and a blood type ([0019]); wherein the medical operation or diagnosis is related to a stent placed in the luminal organ, and the image processing apparatus is configured to: determine whether the stent is present in the image ([0032]), in response to determining that the stent is present, determining support information regarding endpoint determination as said one of the pieces of support information to be displayed, and in response to determining that the stent is not present, determining support information regarding stent implant as said one of the pieces of support information to be displayed ([0026], [0057], [0067]); wherein the image processing apparatus cause the display apparatus to display the image in association with said one of the pieces of support information ([0067]); the image processing apparatus stores a table in which each of the plurality of pieces of support information is associated with the corresponding type of the object ([0037]-[0041]); the image processing apparatus is configured to: cause the display apparatus to display a plurality of candidates of support information corresponding to the type of the object and the medical operation or diagnosis indicated by the input information, and receive a selection of one of the candidates of support information as said one of the pieces of support information to be displayed ([0057], [0060], [0067]); the luminal organ is a blood vessel ([0019]-[0020], [0026]); wherein the sensor of the catheter includes an optical transmitter and receiver, and the image processing apparatus is configured to generate an optical coherence tomographic image of the blood vessel based on a signal that is output from the sensor ([0026]-[0027]).
Lu fails to show acquire input information indicating what medical operation or diagnosis is to be performed on the object in the generated image, determine one of the pieces of support information that corresponds to the medical operation or diagnosis indicated by the input information. Also, store in a memory a plurality of application programs each causing, when executed, the display apparatus to display a corresponding one of the plurality of pieces of support information, and upon determining one of the pieces of support information corresponding to the type of the object and the medical operation or diagnosis indicated by the input information, execute one of the application programs corresponding to said one of the pieces of support information.
Lu fails to show storing in a memory a plurality of application programs each of which is executable independently and selecting, from the plurality of application programs stored in the memory, one of the application programs that displays information corresponding to the type of the object and the medical operation or diagnosis indicated by the input information. Lu also fails to show determine two or more candidates of the application programs that display the information corresponding to the type of the object and the medical operation or diagnosis indicated by the input information, cause the display apparatus to display names of the two or more candidates; wherein the image processing apparatus is configured to execute the selected one of the application programs to: calculate a plaque burden for each of frames of the generated image, specify one or more of the frames having the calculated plaque burden equal to or larger than a threshold, specify reference frames positioned on a distal side and a proximal side of the one or more of the frames, and cause the display apparatus to display information indicating the specified reference frames; wherein the image processing apparatus is configured to execute the selected one of the application programs to: determine an expansion diameter of a stent included in the image, specify a recommended expansion pressure based on the determined expansion diameter, and cause the display apparatus to display the recommended expansion pressure; wherein the output from the machine learning model indicates the presence of a plurality of different types of objects in the generated image, and the image processing apparatus is further configured to select and execute two or more of the application programs that respectively correspond to the plurality of different types of objects.
Lu also fails to show wherein the sensor of the catheter includes an ultrasound transmitter and receiver, and the image processing apparatus is configured to generate an ultrasonic tomographic image of the blood vessel based on a signal that is output from the sensor.
Gopinath discloses stent planning systems and methods. Gopinath teaches acquire input information indicating what medical operation or diagnosis is to be performed on the object in the generated image, determine one of the pieces of support information that corresponds to the medical operation or diagnosis indicated by the input information (user select stent planning user interface icon, system displays corresponding stent planning graphical information; [0111]). Also, store in a memory a plurality of application programs each causing, when executed, the display apparatus to display a corresponding one of the plurality of pieces of support information, and upon determining one of the pieces of support information corresponding to the type of the object and the medical operation or diagnosis indicated by the input information, execute one of the application programs corresponding to said one of the pieces of support information (graphic user interface; [0118], [0120], [0122]-[0126]); wherein the output from the machine learning model indicates the presence of a plurality of different types of objects in the generated image, and the image processing apparatus is further configured to select and execute two or more of the application programs that respectively correspond to the plurality of different types of objects ([0108]).
Gopinath also teaches show wherein the sensor of the catheter includes an ultrasound transmitter and receiver, and the image processing apparatus is configured to generate an ultrasonic tomographic image of the blood vessel based on a signal that is output from the sensor ([0040], [0049], [0085], [0117]).
Amis discloses IVUS/OCT imaging and display of calcium plaque burden. Amis teaches a memory storing a plurality of application programs each of which is executable independently and selecting, from the plurality of application programs stored in the memory ([0049]-[0051]), one of the application programs that displays information corresponding to the type of the object and the medical operation or diagnosis indicated by the input information ([0028], [0056]-[0057], [0059], [0088], [0111], [0116]-[0117]). Amis also teaches determine two or more candidates of the application programs that display the information corresponding to the type of the object and the medical operation or diagnosis indicated by the input information, cause the display apparatus to display names of the two or more candidates ([0056]-[0057], [0111], [0116]-[0117]); wherein the image processing apparatus is configured to execute the selected one of the application programs to: calculate a plaque burden for each of frames of the generated image, specify one or more of the frames having the calculated plaque burden equal to or larger than a threshold, specify reference frames positioned on a distal side and a proximal side of the one or more of the frames, and cause the display apparatus to display information indicating the specified reference frames ([0041]-[0044], [0054], [0063], [0077], [0080], [0089]-[0090], [0102]-[0105], [0118]-[0119], [0122]-[0126]); wherein the image processing apparatus is configured to execute the selected one of the application programs to: determine an expansion diameter of a stent included in the image, specify a recommended expansion pressure based on the determined expansion diameter, and cause the display apparatus to display the recommended expansion pressure ([0106], [0116]).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the invention of Lu to acquire input information indicating what medical operation is to be performed on the object in the generated image as taught by Gopinath, as a user input provides greater control to the user over the system, and allows for the system to display corresponding graphical user interface medical diagnostic information suited to the user’s selection.
Furthermore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the invention of Lu to utilize an ultrasound system as taught by Gopinath, as Gopinath teaches that intravascular ultrasound (IVUS) provides a suitable equivalent alternative to OCT, as IVUS similarly provides images of the objects in the blood vessel region from a catheter located within the blood vessel, and where such images may be processed with image analysis techniques.
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the combined invention of Lu and Gopinath to select application programs corresponding with various diagnostic measurements related to stent planning, including by accounting for plaque burden and expansion pressure as taught by Amis, as Amis teaches that stent expansion may be influenced by various factors including the plaque burden (Amis, [0101]) and factors related to the balloon diameter and pressure ([0106]). By accounting for various factors in the machine learning system such as plaque burden and balloon pressure, the overall accuracy of the diagnostic procedure is increased to provide the user with an improved risk assessment ([0116]-[0117]). Furthermore, it would be an obvious design choice to one of ordinary skill in the art, to display any of the parameters related to the stenting planning/procedure as desired by the user, such as specifying reference frames or expansion pressure, as different users may prefer to have different pieces of diagnostic information readily presented to the user. Amis recognizes that use of reference frames, plaque burden, and balloon size/pressure are critical factors in the stent planning procedure ([0059], [0088], [0106], [0121]).
Claim(s) 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lu et al. (US 2017/0169566; hereinafter Lu) in view of Gopinath (US 2018/0085170) and Amis et al. (US 2021/0042927; hereinafter Amis) as applied to claim 1 above, and further in view of Baba et al. (US 2015/0220794; hereinafter Baba).
Amis fails to show wherein the image processing apparatus is configured to: generate a determination flag value indicating presence or absence for each of a plurality of types of objects, generate a combination code by concatenating the generated determination flag values, and select said one of the application programs by comparing the generated combination code with a combination table stored in the memory.
Baba discloses image processing apparatus and methods for detecting a moving object in an image. Baba teaches wherein the image processing apparatus is configured to: generate a determination flag value indicating presence or absence for each of a plurality of types of objects, generate a combination code by concatenating the generated determination flag values, and select said one of the application programs by comparing the generated combination code with a combination table stored in the memory (moving object identifier number for each object stored in concatenation management table; [0054]-[0058], [0117]-[0118], [0132], [0136], [0143], [0182]-[0185], [0189], [0210]-[0212]).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the combined invention of Lu, Gopinath, and Amis, to utilize codes and tables for storing information in a memory as taught by Baba, as Baba teaches that this will improve the accuracy of identifying moving objects in an image ([0007], [0051], [0189]).
Response to Arguments
Applicant's arguments filed 4/7/26 have been fully considered but they are not persuasive.
In response to applicant’s arguments regarding storing in a memory, the examiner notes that each of Lu ([0006]), Gopinath ([0120], [0122]-[0126]), and Amis ([0049]-[0051]) teach that it is known in the art to utilize computer type devices including memories for storing information and executing corresponding applications in various formats.
In regards to claim 23, it is noted that Gopinath teaches wherein the output from the machine learning model indicates the presence of a plurality of different types of objects in the generated image, and the image processing apparatus is further configured to select and execute two or more of the application programs that respectively correspond to the plurality of different types of objects ([0108]).
Applicant’s arguments with respect to claim(s) 24 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 JONATHAN CWERN whose telephone number is (571)270-1560. The examiner can normally be reached Monday - Friday, 8:00 am - 5:00 pm.
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/JONATHAN CWERN/ Primary Examiner, Art Unit 3797
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