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 .
Response to Amendment
The amendment of 08/26/2025 has been entered and fully considered by the examiner. Claims 1, and 14-16 have been amended. Claim 7 has been canceled. Claims 1-6 and 8-17 are currently pending in the application with claims 1, 14 and 16 being independent claims.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-9, 11, 13-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 of the subject matter eligibility test (see MPEP 2106.03).
Claim 1 is directed to an “apparatus” which describes one of the four statutory categories of patentable subject matter, i.e., a machine.
Claim 14 is directed to a “method” which describes one of the four statutory categories of patentable subject matter, i.e., a process.
Claim 16 is directed to an “an apparatus” which describes one of the four statutory categories of patentable subject matter, i.e., a machine
Step 2A of the subject matter eligibility test (see MPEP 2106.04).
Prong One:
Claims 1, 14, and 16 recite (“sets forth” or “describes”) the abstract idea of a mental process, substantially as follows: “calculating a diaphragm thickness metric based on the received ultrasound imaging data of the diaphragm of the patient referenced to the reference frame using the patient-specific registration model (the calculated diaphragm thickness metric being indicative of whether or not to wean the patient off of the mechanical ventilation therapy)”.
In claims 1, 14, and 16, the above recited steps can be practically performed in the human mind, with the aid of a pen and paper or with a generic computer, in a computer environment, or merely using the generic computer as a tool to perform the steps. If a person were to visually examine, i.e., perform an observation, the ultrasound imaging data, he/she would be able to estimate several parameters regarding respiration of the patient and based on them calculate a diaphragm thickness based on the data using a patient specific predetermined model. There is nothing recited in the claim to suggest an undue level of complexity in the patient specific registration model or the calculation process. Therefore, a person would be able to perform the calculation steps mentally or with a generic computer.
Prong Two: Claims 1, 14, and 16 do not include additional elements that integrate the mental process into a practical application.
This judicial exception is not integrated into a practical application. In particular, the claims recite (1) additional element of a storage medium storing a model which is constructed using neural network (ANN) model (2) receiving ultrasound imaging data of a diaphragm of a patient while the patient undergoes mechanical ventilation therapy and (3) further an additional step of displaying the result of the calculation process as the diaphragm thickness metric.
The element in (1) is merely a generic computer storage system which includes a model; the fact that the model is generated using ANN does not make turn the mental process into a practical application as the element is merely a memory storing an already generated ANN model. Step (2) represents merely data gathering or pre-solution activities that are necessary for use of the recited judicial exception and are recited at a high level of generality with conventionally used tools (see below Step IIB for further details). The step in (3 represents merely notification outputting by a processor as a post-solution activity and is recited at a high level of generality.
As a whole, the additional elements merely serve to gather and feed information to the abstract idea and to output a notification based on the abstract idea, while generically implementing it on conventionally used tools. There is no practical application because the abstract idea is not applied, relied on, or used in a meaningful way. No improvement to the technology is evident, and the estimated bio-information is not outputted in any way such that a practical benefit is realized. Therefore, the additional elements, alone or in combination, do not integrate the abstract idea into a practical application.
Step 2B of the subject matter eligibility test (see MPEP 2106.05).
Claims 1, 14, and 16 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claims recite additional steps of a memory containing ANN constructed model, receiving ultrasound imaging data (in claims 1 and 14) and acquiring ultrasound imaging data by an ultrasound imaging device (claim 16), and outputting the calculated information (claims 1, 14, and 16).
These steps represent a generic memory element containing pre-constructed model, and the steps of mere data gathering, data outputting or pre/post/extra-solution activities that are necessary for use of the recited judicial exception and are recited at a high level of generality.
Accordingly, these additional steps and tools for imaging using an ultrasound device, and displaying the calculated result amount to no more than insignificant conventional extra-solution activity. Mere insignificant conventional extra-solution activity cannot provide an inventive concept. The claims hence are therefore not patent eligible.
Dependent Claims
The following dependent claims merely further define the abstract idea and are, therefore, directed to an abstract idea for similar reasons:
Details of the calculation of the diaphragm thickness metric (claims 2-3)
Construction of a registration model (claim 5-6).
Spatially registration of ultrasound data to a reference frame (claim 9) – this limitation is recited at a high level of generality and could be performed by a practitioner using only pen and paper as the ultrasound image data can be mentally or on paper registered to a reference image that was previously known by the practitioner.
The following dependent claims merely further describe the extra-solution activities and therefore, do not amount to significantly more than the judicial exception or integrate the abstract idea into a practical application for similar reasons:
describes an ultrasound imaging device to acquire the ultrasound image data while the patient is undergoing ventilation (claim 4)- This feature is a general ultrasound imaging device acquiring general ultrasound data. The claim does not positively recite the ventilation device and as a whole the generic ultrasound device fails to add significantly more to the abstract idea;
includes “receiving” additional calibration data acquired with ultrasound data (claim 5)- This feature is recited at a high level of generality using a general-purpose ultrasound probe and merely feeds data into the abstract idea of construction of the model. Therefore, as a whole it fails to add significantly more to the abstract idea;
includes “receiving” additional CT data of a patient (claim 6)- This feature is recited at a high level of generality merely receives CT data and feeds them into the abstract idea of construction of the model. Therefore, as a whole it fails to add significantly more to the abstract idea;
repeating the measurement data and outputting an outlier (claim 15)
the use of a general mechanical ventilator (claim 13)
Taken alone and in combination, the additional elements do not integrate the judicial exception into a practical application at least because the abstract idea is not applied, relied on, or used in a meaningful way. They also do not add anything significantly more than the abstract idea. Their collective functions merely provide computer/electronic implementation and processing, and no additional elements beyond those of the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements individually. There is no indication that the combination of elements improves the functioning of a computer, output device, improves technology other than the technical field of the claimed invention, etc. Therefore, the claims are rejected as being directed to non-statutory subject matter.
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.
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.
Claims 1-4, 12-14, 16 and 17 are rejected under 35 U.S.C. 103 as being obvious over Filyk et al. (UA Publication No. UA 123529 C2) hereinafter “Filyk” in view of Errico et al. (International Publication No. WO 2021/110576) hereinafter “Errico” and Osawa et al. (the citations below are from the equivalent of US20180289336A1) hereinafter “Osawa”.
Regarding claim 1, Filyk discloses a diaphragm measurement device, [see abstract of Filyk] comprising:
storing a patient-specific registration model for referencing ultrasound imaging data to a reference frame; and [see page 6, last paragraph continued in page 7 disclosing comparing the determined ultrasound data to a threshold range as a reference frame which is equivalent to the claimed registration model]
programmed to perform a diaphragm measurement method [see page 6, third paragraph] including:
receiving ultrasound imaging data of a diaphragm of a patient during inspiration and expiration [see page 6, third paragraph] while the patient undergoes mechanical ventilation therapy with a mechanical ventilator; [see page 6, first paragraph disclosing that the method is performed on children under ventilation]
calculating a diaphragm thickness metric based on the received ultrasound imaging data of the diaphragm of the patient referenced to the reference frame using the patient-specific registration model; and [two parameters OtTe (fraction of diaphragm thinning and OT the ratio of thickness of diaphragm in inspiration to expiration is calculated; see page 6, last 3 paragraphs of the page]
Even though, it is apparent that the method of Filyk is performed using a computer and therefore, it includes a memory and processor, Filyk does not expressly disclose a non-transitory storage medium at least one electronic processor. displaying, on a display device, a representation of the calculated diaphragm thickness metric. And an artificial neural network (ANN).
Errico, directed towards monitoring diaphragm during ventilation [see abstract of Errico] further discloses a non-transitory storage medium [memory 130; see Fig. 1] at least one electronic processor [processor 110; see fig. 1]. displaying, on a display device, a representation of the calculated diaphragm thickness metric. [see claim 8 of Errico; display 200; see page 12, line 15 to the end of the page especially last paragraph]
In the same field of endeavor, Osawa et al. teaches, wherein the patient-specific registration model is constructed as an anatomical model or as an artificial neural network (ANN) model. (“wherein the classification unit has a discriminator that is deep-learned so as to classify the plurality of types of cases, and classifies the target region into a plurality of types of case regions using the discriminator.”[See Claim 6 of Osawa]; also “ Therefore, in the present embodiment, it is assumed that a region of a structure itself showing a specific form, such as the heart and the diaphragm, is also included in the case region.” [See Specification [0049] of Osawa; also “pleural thickening, chest wall, heart, diaphragm, and blood vessel.” [See Specification [0049]; Also see fig 3 below “FIG. 3 is a diagram showing an example of a multilayered neural network.”).
It would have been obvious to a person of ordinary skill level in the art at the time of the filing of the invention to modify the device of Filyk further such that it includes a non-transitory storage medium at least one electronic processor. displaying, on a display device, a representation of the calculated diaphragm thickness metric according to the teaching of Errico in order to process the steps using a computer with higher efficiency and provide feedback to the user by displaying the information.
It would have been obvious to an ordinary skilled in the art before the invention was made to modify the method and/or device of the modified combination of reference(s) as outlined above with artificial neural network (ANN) as taught by Osawa because by using the deep - learned neural network in this manner , it is possible to classify each target pixel of the input three - dimensional image into any of the plurality of types of structures([Background of Osawa [0008]). One would have motivation to combine because it is also desired to accurately perform comparative observation over time using the result of mapping between the past image and the latest image.
Regarding claim 2, Filyk further discloses that the diaphragm thickness metric includes a diaphragm thickening ratio indicative of a diaphragm thickness during inspiration relative to a diaphragm thickness during expiration. [see page 6, last 3 paragraphs of the page; parameter OT is the ratio of the thickness of the diaphragm during inspiration relative to expiration]
Regarding claim 3, Filyk further discloses that the diaphragm thickness metric includes a mean diaphragm thickness over multiple respiratory cycle. [see page 8, paragraph penultimate disclosing that the average value of the thinning fraction is calculated]
Regarding claim 4, Filyk further discloses that an ultrasound imaging device [see page 8, third paragraph disclosing a probe that is placed relative to the chest], wherein the at least one electronic processor controls the ultrasound imaging device to receive the ultrasound imaging data of the diaphragm of the patient acquired while the patient undergoes mechanical ventilation therapy with the mechanical ventilator from the handheld ultrasound transducer.[see page 8, second and third paragraph disclosing imaging and receiving imaging data while the patient is under ventilation]
Filyk does not expressly disclose that the ultrasound transducer is handheld.
Errico further discloses that the ultrasound transducer is handheld [see FIG. 1; probe 100 is a handheld probe]
It would have been obvious to a person of ordinary skill level in the art at the time of the filing of the invention to modify the device of Filyk further such that the ultrasound probe is handheld according to the teachings of Errico in order to provide ease of use and portability for the sonographer.
Regarding claim 12, Filyk further discloses control a mechanical ventilator to adjust one or more parameters of the mechanical ventilation therapy delivered to the patient based on the calculated diaphragm thickness metric. [see page 9, the third paragraph]
Regarding claim 13, Filyk further discloses a mechanical ventilator configured to deliver mechanical ventilation therapy to the patient [see abstract and claim 1; the ventilation device is used for the patients under study]
Regarding claim 14, A diaphragm measurement method [see abstract of Filyk] comprising,:
receiving ultrasound imaging data of a diaphragm of a patient during inspiration and expiration [see page 6, third paragraph] while the patient undergoes mechanical ventilation therapy with a mechanical ventilator; [see page 6, first paragraph disclosing that the method is performed on children under ventilation]
calculating a diaphragm thickness metric based on the received ultrasound imaging data of the diaphragm of the patient [two parameters OtTe (fraction of diaphragm thinning and OT the ratio of thickness of diaphragm in inspiration to expiration is calculated; see page 6, last 3 paragraphs of the page] referenced to a reference frame using a patient-specific registration model, [see page 6, last paragraph continued in page 7 disclosing comparing the determined ultrasound data to a threshold range as a reference frame which is equivalent to the claimed registration model]
the calculated diaphragm thickness metric being indicative of whether or not to wean the patient off of the mechanical ventilation therapy; and [see abstract and page 5 of Filyk]
Filyk does not expressly disclose displaying, on a display device, a representation of the calculated diaphragm thickness metric. And an artificial neural network (ANN).
Errico, directed towards monitoring diaphragm during ventilation [see abstract of Errico] further discloses with at least one electronic controller [processor 110; see Fig. 1] displaying, on a display device, a representation of the calculated diaphragm thickness metric. [see claim 8 of Errico; display 200; see page 12, line 15 to the end of the page especially last paragraph]
In the same field of endeavor, Osawa et al. teaches, wherein the patient-specific registration model is constructed as an anatomical model or as an artificial neural network (ANN) model. (“wherein the classification unit has a discriminator that is deep-learned so as to classify the plurality of types of cases, and classifies the target region into a plurality of types of case regions using the discriminator.”[See Claim 6 of Osawa]; also “ Therefore, in the present embodiment, it is assumed that a region of a structure itself showing a specific form, such as the heart and the diaphragm, is also included in the case region.” [See Specification [0049] of Osawa; also “pleural thickening, chest wall, heart, diaphragm, and blood vessel.” [See Specification [0049]; Also see fig 3 below “FIG. 3 is a diagram showing an example of a multilayered neural network.”).
It would have been obvious to a person of ordinary skill level in the art at the time of the filing of the invention to modify the device of Filyk further such that it includes displaying, on a display device, a representation of the calculated diaphragm thickness metric according to the teaching of Errico in order provide feedback to the user by displaying the information.
It would have been obvious to an ordinary skilled in the art before the invention was made to modify the method and/or device of the modified combination of reference(s) as outlined above with artificial neural network (ANN) as taught by Osawa because by using the deep - learned neural network in this manner , it is possible to classify each target pixel of the input three - dimensional image into any of the plurality of types of structures([Background of Osawa [0008]). One would have motivation to combine because it is also desired to accurately perform comparative observation over time using the result of mapping between the past image and the latest image.
Regarding claim 16, a diaphragm measurement device, [see abstract of Filyk] comprising:
an ultrasound medical imaging device configured to acquire ultrasound imaging data of a diaphragm of a patient see page 8, third paragraph disclosing a probe that is placed relative to the chest], during inspiration and expiration while the patient undergoes mechanical ventilation therapy delivered by an associated mechanical ventilator [see page 8, second and third paragraph disclosing imaging and receiving imaging data while the patient is under ventilation]
storing a patient-specific registration model for referencing ultrasound imaging data to a reference frame; [see page 6, last paragraph continued in page 7 disclosing comparing the determined ultrasound data to a threshold range as a reference frame which is equivalent to the claimed registration model]
programmed to perform a diaphragm measurement method [see page 6, third paragraph] including:
receiving ultrasound imaging data of a diaphragm of a patient during inspiration and expiration [see page 6, third paragraph] while the patient undergoes mechanical ventilation therapy with a mechanical ventilator; [see page 6, first paragraph disclosing that the method is performed on children under ventilation]
calculating a diaphragm thickness metric based on the received ultrasound imaging data of the diaphragm of the patient referenced to the reference frame using the patient-specific registration model; and [two parameters OtTe (fraction of diaphragm thinning and OT the ratio of thickness of diaphragm in inspiration to expiration is calculated; see page 6, last 3 paragraphs of the page]
Even though, it is apparent that the method of Filyk is performed using a computer and therefore, it includes a memory and processor, Filyk does not expressly disclose a non-transitory storage medium at least one electronic processor. displaying, on a display device, a representation of the calculated diaphragm thickness metric.
Errico, directed towards monitoring diaphragm during ventilation [see abstract of Errico] further discloses a non-transitory storage medium [memory 130; see Fig. 1] at least one electronic processor [processor 110; see fig. 1]. displaying, on a display device, a representation of the calculated diaphragm thickness metric. [see claim 8 of Errico; display 200; see page 12, line 15 to the end of the page especially last paragraph]
It would have been obvious to a person of ordinary skill level in the art at the time of the filing of the invention to modify the device of Filyk further such that it includes a non-transitory storage medium at least one electronic processor. displaying, on a display device, a representation of the calculated diaphragm thickness metric according to the teaching of Errico in order to process the steps using a computer with higher efficiency and provide feedback to the user by displaying the information.
Regarding claim 17, Filyk further discloses that wherein the at least one electronic processor is further programmed to control the associated mechanical ventilator to adjust one or more parameters of the mechanical ventilation therapy delivered to the patient by the associated mechanical ventilator based on the calculated diaphragm thickness metric. [see page 9, the third paragraph]
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Filyk et al. (UA Publication No. UA 123529 C2) hereinafter “Filyk” in view of Errico et al. (International Publication No. WO 2021/110576) hereinafter “Errico” as applied to claim 4 above, and further in view of Maxwell et al. (US Publication No. 2023/0071643).
Regarding Claim 5, Filyk in view of Errico discloses al the limitations of claim 4 [see rejection of claim 4 above]
Filyk in view of Errico does not expressly disclose over a calibration time period, receive calibration ultrasound imaging data of the diaphragm of the patient during inspiration and expiration while the patient undergoes mechanical ventilation therapy with the mechanical ventilator, wherein the calibration ultrasound imaging data are acquired with the handheld ultrasound transducer positioned at a plurality of different positions respective to the diaphragm of the patient; receive calibration respiratory cycle data tracking respiration of the patient during the calibration time period; and construct the patient-specific registration model based on the calibration ultrasound imaging data and the calibration respiratory cycle data.
Maxwell, directed towards detecting movements of the diaphragm using ultrasound [see abstract of Maxwell] further discloses over a calibration time period, receive calibration ultrasound imaging data of the diaphragm of the patient during inspiration and expiration while the patient undergoes mechanical ventilation therapy with the mechanical ventilator, (“These acoustic impedance measurements are dynamically (i.e., in real-time) categorized by the signal processor 30 into one of three categories: air, tissue, or bone. Because the acoustic impedances of these elements are widely divergent, with air at 0.0004 MZ, lung tissues at approximately 0.18 MZ, liver tissues at 1.65 Z, adipose at 1.34 Z, and bone at 7.8 Z, a wide margin (three orders of magnitude) separates the acoustic impedance for tissue and air and a wide margin (one order of magnitude) still separate lung from other, non-aerated tissues” [See Specification [0011] of Maxwell];)
wherein the calibration ultrasound imaging data are acquired with the handheld ultrasound transducer positioned at a plurality of different positions respective to the diaphragm of the patient; receive calibration respiratory cycle data tracking respiration of the patient during the calibration time period; and (wherein the signal processor is configured to dynamically detect and identify a location of the patient's diaphragm and generate an output indicative of information selected from the group consisting of the patient's respiratory rate and the lung's location.” [ See Claim 3 of Maxwell])
construct the patient-specific registration model based on the calibration ultrasound imaging data and the calibration respiratory cycle data. (“further comprising an output device coupled to the signal processor configured to present information indicative of the quality of the patient's lung function selected from the group consisting of still images, moving images, text, numerical data, and audible sound” [See Claim 7 of Maxwell]).
It would have been obvious to an ordinary skilled in the art before the invention was made to modify the device of Filyk as modified by Errico further such that it includes over a calibration time period, receive calibration ultrasound imaging data of the diaphragm of the patient during inspiration and expiration while the patient undergoes mechanical ventilation therapy with the mechanical ventilator, wherein the calibration ultrasound imaging data are acquired with the handheld ultrasound transducer positioned at a plurality of different positions respective to the diaphragm of the patient; receive calibration respiratory cycle data tracking respiration of the patient during the calibration time period; and construct the patient-specific registration model based on the calibration ultrasound imaging data and the calibration respiratory cycle data according to the teachings of Maxwell in order to provide a calibrated reference as a baseline for the measurements and thereby increase the accuracy of further measurements.
Claims 6, 8-11, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Filyk et al. (UA Publication No. UA 123529 C2) hereinafter “Filyk” in view of Errico et al. (International Publication No. WO 2021/110576) hereinafter “Errico” as applied to claim 1 above, and further in view of Laghi et al (Ultrasound and non-ultrasound imaging techniques in the assessment of diaphragmatic dysfunction. BMC Pulm Med 21, 85 (2021)) hereinafter “Laghi”.
Regarding Claim 6, Filyk in view of Errico discloses all the limitations of claim 1 [see rejection of claim 1 above]
Filyk in view of Errico does not disclose receiving a computed tomography (CT) image of a torso of the patient.
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However, in the same field of endeavor, Laghi et al. teaches, wherein the at least one electronic processor is further programmed to: receive a computed tomography (CT) image of a torso of the patient; [“Plain chest radiographs and CT imaging generate still images of the diaphragm and, thus, they provide information about shape and position of the muscle” [See Page 22 of Laghi et al.]; also see Fig 10 of Laghi for CT imaging of diaphragm thickness below.]
Additionally, Laghi teaches, and construct the patient-specific registration model as an anatomical model of the patient including the diaphragm and surrounding organs based on the CT image. (“Intra- and interobserver agreement of measurements of diaphragm thickness obtained at a single sitting in healthy adults [26, 29] and in ventilated patients [28] are high as long as the operator marks the site and all subsequent images are recorded from that mark” [See page 3 of Laghi et al.])
It would have been obvious to an ordinary skilled in the art before the invention was made to modify the method and/or device of the modified combination of reference(s) as outlined above with CT torso images as taught by Laghi because while diaphragm imaging modalities attempt to meet this challenge, refinement of these techniques is required before its use can be broadly advocated for in clinical practice (Page 24 Future Directions of Laghi). One would have motivation to combine because non-ultrasound imaging techniques allow visualization of the entire diaphragm which is impossible with ultrasonography.
Regarding Claim 8, Filyk in view of Errico discloses all the limitations of claim 1 [see rejection of claim 1 above]
Filyk in view of Errico does not disclose using imaging data of the diaphragm of the patient to the reference frame using the patient-specific registration model.
Laghi further discloses wherein the referencing of the received ultrasound imaging data of the diaphragm of the patient to the reference frame using the patient-specific registration model includes: (“Recordings of diaphragm thickening during voluntary contractions, two-dimensional speckle tracking imaging and shear wave elastography are ultrasound-based techniques that have been used to estimate diaphragm strength.” [See Page 3 of Laghi et al.])
Additionally, Laghi teaches, spatially registering the received ultrasound imaging data to the reference frame comprising a reference orientation of an ultrasound probe respective to the diaphragm. (“This technique takes advantage of the fact that ultrasound images are made up of different grey-scale pixels called speckles. A speckle-tracking software follows unique groups of these pixels (known as ‘kernels’) to measure their displacement in relation to one another (deformation)” [See page 4 of Laghi et al.])
It would have been obvious to an ordinary skilled in the art before the invention was made to modify the method and/or device of the modified combination of reference(s) as outlined above with using imaging data of the diaphragm of the patient to the reference frame using the patient-specific registration model as taught by Laghi because selecting the appropriate imaging technique for a given clinical scenario is a critical step in the evaluation of patients suspected of having diaphragm dysfunction (Abst. Laghi et al.). One would have motivation to combine because it would provide a plurality of imagines of the reference frames using speckle tracking to compare image data, leading to a more accurate diagnosis.
Regarding Claim 9, Filyk in view of Errico discloses all the limitations of claim 1 [see rejection of claim 1 above]
Filyk in view of Errico does not disclose spatially registering the received ultrasound imaging data.
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Laghi further discloses spatially registering the received ultrasound imaging data to the reference frame comprising a reference ultrasound probe orientation respective to the diaphragm of the patient using the patient-specific registration model. (“This technique takes advantage of the fact that ultrasound images are made up of different grey-scale pixels called speckles. A speckle-tracking software follows unique groups of these pixels (known as ‘kernels’) to measure their displacement in relation to one another (deformation)” [See page 4 of Laghi et al.]; also see Fig 5 of Laghi “. The stronger the contraction of the diaphragm, the closer kernels come together (strain) [See page 5 of Laghi].
It would have been obvious for one of ordinary skilled in the art before the invention was made to modify the method and/or device of the modified combination of reference(s) as outlined above with spatially registering the received ultrasound imaging data as taught by Laghi because speckle tracking has the potential to describe this longitudinal shortening during diaphragm contractions (Page 3 Background of Laghi). One would have motivation to combine because it would provide a plurality of images of the reference frames using speckle tracking to efficiently compare image data.
Regarding Claim 10, Filyk in view of Errico and Laghi discloses all the limitations of claim 9 [see rejection of claim 9 above]
Laghi further discloses wherein the patient-specific registration model is configured to apply a simultaneous localization and mapping (SLAM) process to spatially register the received ultrasound imaging data to the reference ultrasound probe orientation (“To standardize how normative data is presented, ultrasound measurement and spirometry should be performed simultaneously” [ See Page 24 of Laghi])
It would have been obvious to an ordinary skilled in the art before the invention was made to modify the method and/or device of the modified combination of reference(s) as outlined above with simultaneous localization and mapping process (SLAM) as taught by Laghi because as tidal volume is generated by both the diaphragm and by the extradiaphragmatic muscles, concurrent ultrasound assessment of the diaphragm and the extradiaphragmatic muscles, could be of interest (Abst Laghi et al.) One would have motivation to combine because it allows one to visualize and may afford generalizability of assessment of this muscle group.
Regarding Claim 11, Filyk in view of Errico discloses all the limitations of claim 1 [see rejection of claim 1 above]
Filyk in view of Errico does not disclose generating a trendline for the calculated thickness metric.
Laghi further discloses repeat the diaphragm measurement method for successive sessions and to generate a trendline for the calculated diaphragm thickness metric; (” investigators have published a growing number of studies on the use of ultrasonography to monitor the thickness of the diaphragm in the zone of apposition, the motion of the dome and to estimate diaphragm strength and recruitment” [See Page 2 of Laghi et al.])
and display, in the display, an indication of an outlier if a repetition of the diaphragm measurement method calculates the diaphragm thickness metric deviating from the trendline by greater than a threshold deviation. ([See figure 1 and figure 3])
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It would have been obvious to an ordinary skilled in the art before the invention was made to modify the method and/or device of the modified combination of reference(s) as outlined above with diaphragm thickness metric includes a mean diaphragm thickness as taught by Laghi because diaphragm muscle dysfunction is increasingly recognized as an important element of several diseases including neuromuscular disease, chronic obstructive pulmonary disease and diaphragm dysfunction in critically ill patients. Functional evaluation of the diaphragm is challenging. Use of volitional maneuvers to test the diaphragm can be limited by patient effort which the modification would help overcome these challenges (abst of Laghi). One would have motivation to combine because gathering average or mean data for diaphragm thickness to predict accurate measurement results.
Regarding Claim 15 Maxwell teaches all of the claim limitations except generating a trendline.
However, in the same field of endeavor, Laghi teaches, repeating the diaphragm measurement method for successive sessions and to generate a trendline for the calculated diaphragm thickness metric; (“investigators have published a growing number of studies on the use of ultrasonography to monitor the thickness of the diaphragm in the zone of apposition, the motion of the dome and to estimate diaphragm strength and recruitment” [See Page 2 of Laghi et al.])
Additionally, in the same field of endeavor, Laghi also teaches and displaying, in the device, an indication of an outlier if a repetition of the diaphragm measurement method calculates the diaphragm thickness metric deviating from the trendline by greater than a threshold deviation. (“Relationship between the thickening of the diaphragm recorded with ultrasonography and changes in the pressure–time product of the diaphragm (PTPdi) in 12 patients during pressure support ventilation” [See page 14 of Laghi and Fig 16 below.])
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It would have been obvious to an ordinary skilled in the art before the invention was made to modify the method and/or device of the modified combination of reference(s) as outlined above with diaphragm thickness metric includes a mean diaphragm thickness as taught by Laghi because diaphragm muscle dysfunction is increasingly recognized as an important element of several diseases including neuromuscular disease, chronic obstructive pulmonary disease and diaphragm dysfunction in critically ill patients. Functional evaluation of the diaphragm is challenging. Use of volitional maneuvers to test the diaphragm can be limited by patient effort which the modification would help overcome these challenges (abstract of Laghi). One would have motivation to combine because gathering average or mean data for diaphragm thickness to predict accurate measurement results.
Response to Arguments
Applicant's arguments filed 08/26/2025 with regards to the rejection of claims have been fully considered but they are not persuasive.
Rejection of Claims under U.S.C. 101 (abstract idea)
With regards to the rejection of claims under U.S.C. 101 as being directed to an abstract idea, the applicant has argued that the addition of a limitation reciting that the patient-specific model is an ANN model would overcome the abstract idea.
In response, the examiner notes that what is being claimed is a memory that is used to store a model. The fact that the model is an ANN model does not change the memory in any way. There is no limitation in the claim that requires training or generation of an ANN model and it recites merely storing it on a memory. As a result, the claims fail to add an element that would add significantly to the abstract idea.
Rejection of Claims under U.S.C. 103
With regards to the rejection of independent claims in view of modification of Filyk in view of Osawa, the applicant has argued that the combination constitutes impermissible hindsight reasoning because one skilled in the art would not replace the formulas of Filyk with the neural network of Osawa.
In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971).
In this particular case, the motivation to combine would be to improve the model from a simple formula to a more sophisticated trained neural network model that can classify each target pixel of the inputted 3D image into any of the plurality of types of structures([Background of Osawa [0008]). One would have motivation to combine because it is also desired to accurately perform comparative observation over time using the result of mapping between the past image and the latest image.
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.
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/MARJAN SABOKTAKIN/Examiner, Art Unit 3797
/MICHAEL J CAREY/Supervisory Patent Examiner, Art Unit 3795