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 Arguments
Applicant’s argument on Page 15 regarding the objection to the drawings has been fully considered. While some of the issues were addressed, not all were. Therefore, the objection to the drawings is maintained as below.
Applicant’s argument on Page 15 regarding the objection to the specification has been fully considered. The objection to the specification is withdrawn in view of the amendments.
Applicant’s argument on Page 15 regarding the objection to Claim 37 has been fully considered. However, the objection is improperly addressed. There is a grammatical issue in Line 3 of Claim 37. Claim 45 was incorrectly objected to in the previous Office Action. Therefore, the objection to Claims 37 is maintained as below.
Applicant’s argument on Pages 15-16 regarding the rejection of Claims 42 and 53 under 35 U.S.C. 112(a) has been fully considered. The rejection of Claims 42 and 53 under 35 U.S.C. 112(a) is withdrawn in view of the argument.
Applicant’s argument on Page 16 regarding the rejection of Claim 47 under 35 U.S.C. 112(d) has been fully considered. The rejection of Claim 47 under 35 U.S.C. 112(d) is withdrawn in view of the amendments.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description: 126 (Fig. 2) and 46 (Fig. 11). Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Color photographs and color drawings are not accepted in utility applications unless a petition filed under 37 CFR 1.84(a)(2) is granted. Any such petition must be accompanied by the appropriate fee set forth in 37 CFR 1.17(h), one set of color drawings or color photographs, as appropriate, if submitted via the USPTO patent electronic filing system or three sets of color drawings or color photographs, as appropriate, if not submitted via the via USPTO patent electronic filing system, and, unless already present, an amendment to include the following language as the first paragraph of the brief description of the drawings section of the specification:
The patent or application file contains at least one drawing executed in color (Figs. 34-39 red and blue data points, as disclosed in [0077], and Figs. 28-30 calcific nodules colored yellow, aortic root colored red and bioprosthetic surgical valve implanted colored grey, as disclosed in [0074]). Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.
Color photographs will be accepted if the conditions for accepting color drawings and black and white photographs have been satisfied. See 37 CFR 1.84(b)(2).
Claim Objections
Claim 37 is objected to because of the following informalities: minor grammatical error and minor error in antecedent basis. The claim should be amended to “[…] evaluating at least one patient specific [[at least one]] clinical outcome […] wherein the at least one patient-specific predictive criteria [[of confirmed at least one]] clinical outcome” in order to make sense grammatically and establish proper antecedent basis. Appropriate correction is required.
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.
Claims 37-38, 48-49, and 57-61 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Mansi et al. (US 20120232386).
Regarding Claim 37, Mansi teaches a method of planning a surgical procedure using a simulation system, (Abstract “Valve treatment simulation is performed from patient specific imaging data for therapy planning.”), the method comprising:
a) evaluating patient-specific least one clinical outcome during or after a surgical procedure involving at least one surgical object according to simulated parameters selected from options comprising at least one of: type, size, deployment configuration, and positioning of the at least one surgical object ([0039] “To capture a broad spectrum of morphological variations, the model is parameterized by three coarse-to-fine components: i) three transformations B for global location, orientation and scale over the cardiac cycle; ii) the trajectories of ten anatomical landmarks L(B)=(I1 . . . I10).epsilon.R.sup.3.times.10 (two trigones, one posterior annulus mid-point, two commissures, two leaflet tips and two papillary tips (see FIG. 4); and iii) a triangulated surface mesh S.sub.LA(B, L) to represent the left atrial (LA) surface of both anterior and posterior leaflets. The positions of the vertices of the LA surface are constrained by the anatomical landmarks, resulting in an anatomically consistent parameterization (.OMEGA., u, v) that ensures intra- and inter-patient point correspondence” and [0134] “The parameters defining these added structures may be predetermined or user selectable. The processor 12 may receive an indication of one or more parameters. The indication may be by processing data. For example, different values of a parameter are attempted.”);
b) displaying a virtualization of the surgical procedure that allows a clinician to have a visual feedback of simulated results of the surgical procedure, (Claim 20 “a display configured to generate a visualization of the closure with the valve clip”), wherein different simulated parameters are selectively varied, and corresponding deformed analytical models and corresponding simulated results are generated for display and direct comparison (Claim 13 “simulating comprises simulating valve deformation due to the clip according to biomechanical model,” [0037] “a physiological model of the aortic and mitral valves is designed to capture complex morphological, dynamical and pathological variations,” [0076] “clips arranged at various locations are tested to identify one or more recommended locations. The recommended locations may then be presented to the user,” [0084] “Possible validation may be achieved by comparing simulation outcomes with patient specific data representing data operating with the treatment,” and [0134] “The parameters defining these added structures may be predetermined or user selectable. The processor 12 may receive an indication of one or more parameters. The indication may be by processing data. For example, different values of a parameter are attempted.”); and
c) planning the surgical procedure based on the direct comparison of the displayed corresponding deformed analytical models and simulated results to optimize the at least one clinical outcome, wherein the at least one clinical outcome are predicted using the simulation system every time the simulated parameters are selected, based on a computer-implemented method, ([0027] “After input of therapy location, the framework is applied to MitralClip planning by simulating the intervention. The output prediction may be used for treatment planning, such as attempting to locate the clip position with a more likely positive outcome in terms of residual mitral regurgitation” and [0091] “By providing an integrated way to perform MV simulation, the proposed system may constitute a surrogate tool for model validation and therapy planning.”), comprising: executing, by at least a processor, program code stored in a non-transitory computer-readable-medium to perform a simulation in responding to a selection of simulated parameters, ([0010] “a non-transitory computer readable storage medium has stored therein data representing instructions executable by a programmed processor for valve treatment simulation from medical diagnostic imaging data.”), the simulation comprising:
i) generating analytical model data comprising a three-dimensional mesh and parametric measurements based on image data characterizing anatomical regions of a heart or blood vessels of a patient (Fig. 4, of a mitral valve (anatomical region of a heart), and [0050] “The anatomy model may include a mesh fit to the valve based on the detected anatomy”);
ii) generating, using a numerical analysis engine, a deformed analytical model based on the analytical model data and based on a three-dimensional mesh of a virtually deployed at least one surgical object ([0027] “As a first step towards patient-specific MV FEM, the proposed integrated framework combines efficient machine-learning with a biomechanical model of the valve apparatus to simulate MV function and therapies in patients. FIG. 1 shows an example of this framework for simulating the effect of therapy on MV closure. First, a comprehensive anatomical model of MV apparatus, including papillary tips, is estimated from medical images representing a particular patient. Second, a detailed volumetric model comprising leaflet fibers and chordae is automatically built. MV closure is then simulated based on a biomechanical model. After input of therapy location, the framework is applied to MitralClip planning by simulating the intervention,” [0060] “The biomechanical model is a dynamics system,” and [0083] “The leaflet deformations are computed according to the biomechanical model”); and
iii) predicting the at least one clinical outcome based on patient-specific criteria, wherein the patient-specific predictive criteria of confirmed at least one clinical outcome has been established from a database of image data from patients with and without at least one clinical outcome during or after the surgical procedure, by determining a data fitting model (Fig. 2 and [0082] “In act 38, the processor predicts the effect of placement of the valve clip or therapy on the valve position and in terms of regurgitation. By performing the simulation of act 32 with the treatment locations designated, the effect of placement is simulated. Using the volumetric model as applied to the biomechanical model, the closure of the valve with the treatment is simulated.”).
Regarding Claim 38, Mansi teaches all limitations of Claim 37, as discussed above. Furthermore, Mansi teaches wherein the at least one clinical outcome comprise at least one risk of at least one clinical complication ([0082] “In act 38, the processor predicts the effect of placement of the valve clip or therapy on the valve position and in terms of regurgitation” and [0110] “MV closure is considered to predict residual regurgitation after therapy.”).
Regarding Claim 48, Mansi teaches a simulation system for planning a surgical procedure, (Abstract “Valve treatment simulation is performed from patient specific imaging data for therapy planning,” Fig. 9, and [0111] “a system for valve treatment simulation from medical diagnostic imaging data”), comprising:
a) at least one processor ([0111] “processor 12”);
b) a non-transitory computer readable medium having stored thereon, a computer program having at least one code section, for predicting at least one surgical outcome during or after the surgical procedure involving at least one surgical object deployed into a heart or blood vessels of a patient, the at least one code section being executable by the at least one processor, causing the simulation system to perform simulations every time the simulated parameters are selected, (Fig. 2, [0010] “a non-transitory computer readable storage medium has stored therein data representing instructions executable by a programmed processor for valve treatment simulation from medical diagnostic imaging data,” and [0082] “In act 38, the processor predicts the effect of placement of the valve clip or therapy on the valve position and in terms of regurgitation. By performing the simulation of act 32 with the treatment locations designated, the effect of placement is simulated. Using the volumetric model as applied to the biomechanical model, the closure of the valve with the treatment is simulated.”), the simulations comprising steps of:
i) generating analytical model data comprising a three-dimensional mesh and parametric measurements based on image data characterizing anatomical regions of a heart or blood vessels of a patient (Fig. 4, of a mitral valve (anatomical region of a heart), and [0050] “The anatomy model may include a mesh fit to the valve based on the detected anatomy”);
ii) generating, using a numerical analysis engine, a deformed analytical model based on the analytical model data and based on a three-dimensional mesh of a virtually deployed at least one surgical object ([0027] “As a first step towards patient-specific MV FEM, the proposed integrated framework combines efficient machine-learning with a biomechanical model of the valve apparatus to simulate MV function and therapies in patients. FIG. 1 shows an example of this framework for simulating the effect of therapy on MV closure. First, a comprehensive anatomical model of MV apparatus, including papillary tips, is estimated from medical images representing a particular patient. Second, a detailed volumetric model comprising leaflet fibers and chordae is automatically built. MV closure is then simulated based on a biomechanical model. After input of therapy location, the framework is applied to MitralClip planning by simulating the intervention,” [0060] “The biomechanical model is a dynamics system,” and [0083] “The leaflet deformations are computed according to the biomechanical model”); and
iii) predicting the at least one clinical outcome based on the patient-specific criteria, wherein the patient-specific predictive criteria of confirmed at least one clinical outcome has been established from a database of image data from patients with and without at least one clinical outcome during or after the surgical procedure, by determining a data fitting model (Fig. 2 and [0082] “In act 38, the processor predicts the effect of placement of the valve clip or therapy on the valve position and in terms of regurgitation. By performing the simulation of act 32 with the treatment locations designated, the effect of placement is simulated. Using the volumetric model as applied to the biomechanical model, the closure of the valve with the treatment is simulated.”); and
c) a display for displaying a virtualization of the surgical procedure that allows a clinician to have a visual feedback of simulated results of the surgical procedure, (Claim 20 “a display configured to generate a visualization of the closure with the valve clip”), wherein different simulated parameters are selectively varied, and corresponding deformed analytical models and corresponding simulated results are displayed for direct comparison (Claim 13 “simulating comprises simulating valve deformation due to the clip according to biomechanical model,” [0037] “a physiological model of the aortic and mitral valves is designed to capture complex morphological, dynamical and pathological variations,” [0076] “clips arranged at various locations are tested to identify one or more recommended locations. The recommended locations may then be presented to the user,” [0084] “Possible validation may be achieved by comparing simulation outcomes with patient specific data representing data operating with the treatment,” and [0134] “The parameters defining these added structures may be predetermined or user selectable. The processor 12 may receive an indication of one or more parameters. The indication may be by processing data. For example, different values of a parameter are attempted.”).
Regarding Claim 49, Mansi teaches all limitations of Claim 37, as discussed above. Furthermore, Mansi teaches wherein the at least one clinical outcome comprise at least one risk of at least one clinical complication ([0082] “In act 38, the processor predicts the effect of placement of the valve clip or therapy on the valve position and in terms of regurgitation” and [0110] “MV closure is considered to predict residual regurgitation after therapy.”).
Regarding Claim 56, Mansi teaches all limitations of Claim 48, as discussed above. Furthermore, Mansi teaches wherein the display comprises a virtual reality device ([0139] “The display 16 is a CRT, LCD, plasma, projector, printer, or other output device for showing an image. The display 16 displays an image of the detected anatomy, such as an image of a valve rendered from medical data and overlaid or highlighted based on the estimates of the valve position. The display 16 displays a sequence of renderings to generate a visualization of the valve motion through the sequence.”).
Regarding Claim 57, Mansi teaches all limitations of Claim 37, as discussed above. Furthermore, Mansi teaches wherein the clinician selectively varies the simulated parameters to generate the corresponding deformed analytical models and corresponding simulated results ([0060] “The biomechanical model is a dynamics system. For example, the biomechanical model is MU+C{dot over (U)}+KU=F.sub.c+F.sub.p, where U is the displacement vector of the free vertices of the MV mesh, {dot over (U)} is the velocity vector, and U is the acceleration vector. M is the lumped mass matrix. Any mass matrix may be used, including uniform mass or mass with spatial variation. In one embodiment, a uniform mass density .rho.=1.04 g/mL is used. The mass parameter can be set by the user. K is the stiffness matrix of the internal elastic forces. C is a Rayleigh damping matrix defined by C=0.1M+0.1K. F.sub.c and F.sub.p are the forces developed by the chordae and heart pressure, respectively. Additional, different, or fewer forces may be used” and [0078] “The user may select an amount or type of force.”).
Regarding Claim 58, Mansi teaches all limitations of Claim 37, as discussed above. Furthermore, Mansi teaches wherein generating the analytical model data comprises identifying anatomical structures from the image data and extracting geometric features of the identified anatomical structures ([0031] “Once activated, the anatomy is identified through a sequence of images for estimating the anatomy model in act 20, the volumetric model is created from the anatomy model in act 22, and the closure of the valve is simulated in act 32 without further user input. Some user input may be provided, such as correcting the anatomy estimation if necessary, adjusting chordae properties (e.g., length) or other parameters of the model. User input of locations of the anatomy in any of the scan data may be avoided, but the user may acknowledge proper location determination by a processor and/or input anatomy relative to one or more images or the user may be provided the opportunity to edit or input locations” and [0120] “Different devices making up the processor 12 may perform different functions, such as an automated anatomy detector and a separate device for performing measurements associated with the detected anatomy.”).
Regarding Claim 59, Mansi teaches all limitations of Claim 37, as discussed above. Furthermore, Mansi teaches wherein the displayed virtualization includes color- coded visual indicators corresponding to the simulated results ([0087] “ Color coding or other display modulation may be used with or in addition to an overlay. For example, different surfaces of the valve are rendered from B-mode data in gray scale with color modulation specific to the simulated surface. One surface may be rendered in one color and another in another color.”).
Regarding Claim 60, Mansi teaches all limitations of Claim 37, as discussed above. Furthermore, Mansi teaches displaying orientation information indicative of a relative orientation associated with acquisition of the image data ([0071] “The user can interact with the imaging processor, to choose the view and orientation” and [0072] “Other viewing directions may be used and chosen interactively by the user.”).
Regarding Claim 61, Mansi teaches all limitations of Claim 60, as discussed above. However, Mansi does not explicitly teach therein the orientation is indicated by displaying the image data in an aortic view, ([0037] “a physiological model of the aortic and mitral valves is designed to capture complex morphological, dynamical and pathological variations” and [0071] “In act 34, an image of the valve is generated. The image is from the acquired scan data, from the anatomy model, and/or from the volumetric model. For example, the position of anatomy of the valve with the valve as open is determined and used to generate an image. In another example, the mesh representing the valve may be used for imaging. Alternatively, the scan data from the time (e.g., end diastole) at which the valve is open and beginning to close is used. The image may be dynamic, showing the motion of the valve. The user can interact with the imaging processor, to choose the view and orientation.”), and/or a ventricular view.
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.
Claims 39-40, 43-44, 50-51, and 54-55 are rejected under 35 U.S.C. 103 as being unpatentable over Mansi et al. (US 20120232386) in view of Mortier (US 20150112659).
Regarding Claim 39, Mansi teaches all limitations of Claim 37, as discussed above. However, Mansi does not explicitly teach wherein the at least one clinical outcome comprise at least one risk of at least one clinical complication.
In an analogous pre-operative simulation of trans-catheter implantation field of endeavor, Mortier teaches a method of planning a surgical procedure using a simulation system, ([0110] “virtually deploying said implant model into each of a plurality of the patient specific anatomical models maintained in said library to evaluate said implant model for a percutaneous implantation procedure.”), wherein the at least one clinical complication comprise one or more of: coronary obstruction, ([0101] “the risk of coronary obstruction, […] is predicted by virtually deploying an implant model representing an implant into the patient-specific anatomical model.”), paravalvular leakage, thrombosis, conduction abnormalities, ([0101] “ the risk of […] conduction abnormalities is predicted by virtually deploying an implant model representing an implant into the patient-specific anatomical model.”), and cerebrovascular events.
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the clinical complication of Mortier because predicting such complications results in better health and safety of the patient, as such complications can be fatal.
Regarding Claim 40, Mansi teaches all limitations of Claim 37, as discussed above. Furthermore, Mortier teaches wherein the at least one clinical outcome comprise blood flow information indicative of one or more of: a paravalvular leakage, ([0097] “In a further preferred step, the amount of paravalvular regurgitation is predicted based on a geometrical analysis of said blood mesh. Hemodynamic performance of the implant can be predicted by quantifying paravalvular leakages […] across the aortic prosthesis” and [0140]-[0142] “It is the aim of the current invention to provide a report to the medical doctor, comprising: figures of the implanted device(s), colour plots of the incomplete apposition of the device(s). These plots give insight into possible paravalvular leaks”), thrombosis, pressure gradient, ([0097] “In a further preferred step, the amount of paravalvular regurgitation is predicted based on a geometrical analysis of said blood mesh. Hemodynamic performance of the implant can be predicted by quantifying […] effective orifice […] gradients across the aortic prosthesis.”), energy loss, and effective orifice area ([0097] “In a further preferred step, the amount of paravalvular regurgitation is predicted based on a geometrical analysis of said blood mesh. Hemodynamic performance of the implant can be predicted by quantifying […] effective orifice […] across the aortic prosthesis.”).
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the clinical outcome of Mortier because predicting such outcomes result in better health and safety of the patient, as such risks can be fatal.
Regarding Claim 43, Mansi teaches all limitations of Claim 37, as discussed above. Furthermore, Mortier teaches wherein the deployment configuration comprises different depths, yaw, and pitch angles relative to one of the anatomical regions of the heart or blood vessels where the at least one surgical object is deployed (Claim 12 “determining a position and an orientation for implanting the implant based on the complications” and [0159] “The model parameters were adjusted until a good correlation was obtained between the deformed stent frame as predicted by the simulations and the geometry of the stent frame as observed from the post-operative image data”).
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the deployment configuration of Mortier because the modification is customizable for each patient, providing an accurate and precise fit for heart valve placement.
Regarding Claim 44, Mansi teaches all limitations of Claim 37, as discussed above. Furthermore, Mortier teaches wherein the at least one surgical object is selected from options comprising at least one of a surgical bioprosthetic heart valve, ([0004] “Trans-catheter aortic valve implantation (TAVI) or trans-catheter aortic valve repair (TAVR) is a minimally-invasive procedure for treating aortic stenosis: (1) the valve (e.g. a bioprosthetic valve made of porcine pericardium sutured on a metal stent) is crimped inside a catheter”), a trans-catheter heart valve, ([0004] “Trans-catheter aortic valve implantation (TAVI) or trans-catheter aortic valve repair (TAVR) is a minimally-invasive procedure for treating aortic stenosis: (1) the valve (e.g. a bioprosthetic valve made of porcine pericardium sutured on a metal stent) is crimped inside a catheter”), an artificial root, a surgical instrument, and a stent graft ([0159] “predicted stent frame 50”).
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the surgical object selection of Mortier because the repairs with such surgical objections can greatly improve the health and safety of the patient, as taught by Mortier in [0002].
Regarding Claim 50, Mansi teaches all limitations of Claim 49, as discussed above. However, Mansi does not explicitly teach wherein the at least one clinical outcome comprise at least one risk of at least one clinical complication.
In an analogous pre-operative simulation of trans-catheter implantation field of endeavor, Mortier teaches a simulation system for planning a surgical procedure using a simulation system, ([0110] “virtually deploying said implant model into each of a plurality of the patient specific anatomical models maintained in said library to evaluate said implant model for a percutaneous implantation procedure.”), wherein the at least one clinical complication comprise one or more of: coronary obstruction, ([0101] “the risk of coronary obstruction, […] is predicted by virtually deploying an implant model representing an implant into the patient-specific anatomical model.”), paravalvular leakage, thrombosis, conduction abnormalities, ([0101] “ the risk of […] conduction abnormalities is predicted by virtually deploying an implant model representing an implant into the patient-specific anatomical model.”), and cerebrovascular events.
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the clinical complication of Mortier because predicting such complications results in better health and safety of the patient, as such complications can be fatal.
Regarding Claim 51, Mansi teaches all limitations of Claim 48, as discussed above. Furthermore, Mortier teaches wherein the at least one clinical outcome comprise blood flow information indicative of one or more of: a paravalvular leakage, ([0097] “In a further preferred step, the amount of paravalvular regurgitation is predicted based on a geometrical analysis of said blood mesh. Hemodynamic performance of the implant can be predicted by quantifying paravalvular leakages […] across the aortic prosthesis” and [0140]-[0142] “It is the aim of the current invention to provide a report to the medical doctor, comprising: figures of the implanted device(s), colour plots of the incomplete apposition of the device(s). These plots give insight into possible paravalvular leaks”), thrombosis, pressure gradient, ([0097] “In a further preferred step, the amount of paravalvular regurgitation is predicted based on a geometrical analysis of said blood mesh. Hemodynamic performance of the implant can be predicted by quantifying […] effective orifice […] gradients across the aortic prosthesis.”), energy loss, and effective orifice area ([0097] “In a further preferred step, the amount of paravalvular regurgitation is predicted based on a geometrical analysis of said blood mesh. Hemodynamic performance of the implant can be predicted by quantifying […] effective orifice […] across the aortic prosthesis.”).
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the clinical outcome of Mortier because predicting such outcomes result in better health and safety of the patient, as such risks can be fatal.
Regarding Claim 54, Mansi teaches all limitations of Claim 48, as discussed above. Furthermore, Mortier teaches wherein the deployment configuration comprises different depths, yaw, and pitch angles relative to one of the anatomical regions of the heart or blood vessels where the at least one surgical object is deployed (Claim 12 “determining a position and an orientation for implanting the implant based on the complications” and [0159] “The model parameters were adjusted until a good correlation was obtained between the deformed stent frame as predicted by the simulations and the geometry of the stent frame as observed from the post-operative image data”).
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the deployment configuration of Mortier because the modification is customizable for each patient, providing an accurate and precise fit for heart valve placement.
Regarding Claim 55, Mansi teaches all limitations of Claim 48, as discussed above. Furthermore, Mortier teaches wherein the at least one surgical object is selected from options comprising at least one of a surgical bioprosthetic heart valve, ([0004] “Trans-catheter aortic valve implantation (TAVI) or trans-catheter aortic valve repair (TAVR) is a minimally-invasive procedure for treating aortic stenosis: (1) the valve (e.g. a bioprosthetic valve made of porcine pericardium sutured on a metal stent) is crimped inside a catheter”), a trans-catheter heart valve, ([0004] “Trans-catheter aortic valve implantation (TAVI) or trans-catheter aortic valve repair (TAVR) is a minimally-invasive procedure for treating aortic stenosis: (1) the valve (e.g. a bioprosthetic valve made of porcine pericardium sutured on a metal stent) is crimped inside a catheter”), an artificial root, a surgical instrument, and a stent graft ([0159] “predicted stent frame 50”).
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the surgical object selection of Mortier because the repairs with such surgical objections can greatly improve the health and safety of the patient, as taught by Mortier in [0002].
Claims 41, 45, 47, and 52 are rejected under 35 U.S.C. 103 as being unpatentable over Mansi et al. (US 20120232386) in view of Zaeuner et al. (US 20110153286).
Regarding Claim 41, Mansi teaches all limitations of Claim 37, as discussed above. However, Mansi does not explicitly teach wherein the virtualization of the surgical procedure comprises real time comparisons of the simulated parameters of a transcatheter aortic valve (TAV) including a type of the TAV, a size of the TAV, and positioning of the TAV, and each corresponding to one of the at least one clinical outcome.
In an analogous virtual percutaneous valve implantation field of endeavor, Zaeuner teaches a method of planning a surgical procedure using a simulation system, ([0019] “FIG. 1 illustrates a method of virtual valve implantation according to an embodiment of the present invention. The method of FIG. 1 transforms 3D medical image data representing a patient's anatomy to generate a patient-specific anatomical model and uses the anatomical model to virtually simulate the implantation of one or more implants (also referred to herein as "stents").”), wherein the virtualization of the surgical procedure comprises real time comparisons of the simulated parameters of a transcatheter aortic valve (TAV), ([0028] “In order to simulate valve replacement under various conditions, different implant models can be selected from the library and virtually deployed under different parameters, into the extracted patient-specific model.”), including a type of the TAV, (Abstract “The implant models maintained in the library are virtually deployed into the patient specific anatomical model of the heart valve to select an implant type […] for percutaneous valve implantation.”), a size of the TAV, (Abstract “The implant models maintained in the library are virtually deployed into the patient specific anatomical model of the heart valve to select an implant […] size […] for percutaneous valve implantation.”), and positioning of the TAV, (Abstract “The implant models maintained in the library are virtually deployed into the patient specific anatomical model of the heart valve to select […] deployment location and orientation for percutaneous valve implantation.”), and each corresponding to one of the at least one clinical outcome ([0031] “Returning to FIG. 1, at step 108, the virtual implant model deployment results are output. The virtual implant deployment results can provide quantitative and qualitative information used in planning and performing the percutaneous valve implantation. For example, using the virtual-deployment framework various implants can be tested and compared to select the best implant and implant size. Further, the virtual implantation can provide an optimal position and orientation for the selected implant with respect to the patient-specific model. Quantitatively, the forces that hold the stent to the wall can be calculated after virtual deployment. Hemodynamic performance of the implant can be predicted by quantifying paravalvular leakages, valve insufficiency, and effective orifice and systolic gradients across the aortic prosthesis.”).
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the real time comparisons of the simulated parameters of a TAV of Zaeuner because the modification avoids improper placement of the implant (surgical object), which may result in a life threatening ischemic condition, poor hemodynamic performance, high gradients and suboptimal effective orifice, damaged vessel tissue, and/or arterial dissection, as taught by Zaeuner in [0004].
Regarding Claim 45, Mansi teaches a method of computer assisted procedure using a simulation system, ([0010] “a non-transitory computer readable storage medium has stored therein data representing instructions executable by a programmed processor for valve treatment simulation from medical diagnostic imaging data.”), the method comprising:
a) evaluating patient-specific at least one clinical outcome during or after a surgical procedure involving at least one surgical object according to simulated parameters selected from options comprising at least one of: type, size, deployment configuration, and positioning of the at least one surgical object ([0039] “To capture a broad spectrum of morphological variations, the model is parameterized by three coarse-to-fine components: i) three transformations B for global location, orientation and scale over the cardiac cycle; ii) the trajectories of ten anatomical landmarks L(B)=(I1 . . . I10).epsilon.R.sup.3.times.10 (two trigones, one posterior annulus mid-point, two commissures, two leaflet tips and two papillary tips (see FIG. 4); and iii) a triangulated surface mesh S.sub.LA(B, L) to represent the left atrial (LA) surface of both anterior and posterior leaflets. The positions of the vertices of the LA surface are constrained by the anatomical landmarks, resulting in an anatomically consistent parameterization (.OMEGA., u, v) that ensures intra- and inter-patient point correspondence” and [0134] “The parameters defining these added structures may be predetermined or user selectable. The processor 12 may receive an indication of one or more parameters. The indication may be by processing data. For example, different values of a parameter are attempted.”);
b) predicting at least one clinical outcome based on the patient-specific criteria, wherein the patient-specific predictive criteria of confirmed at least one clinical outcome has been established from a database of image data from patients with and without at least one clinical outcome during or after the surgical procedure, by determining a data fitting model (Fig. 2 and [0082] “In act 38, the processor predicts the effect of placement of the valve clip or therapy on the valve position and in terms of regurgitation. By performing the simulation of act 32 with the treatment locations designated, the effect of placement is simulated. Using the volumetric model as applied to the biomechanical model, the closure of the valve with the treatment is simulated.”); and
c) displaying corresponding simulated procedural visualizations and corresponding simulated results for direct comparison based on different selectively varied simulated parameters (Claim 20 “a display configured to generate a visualization of the closure with the valve clip” and Claim 13 “simulating comprises simulating valve deformation due to the clip according to biomechanical model,” [0037] “a physiological model of the aortic and mitral valves is designed to capture complex morphological, dynamical and pathological variations,” [0076] “clips arranged at various locations are tested to identify one or more recommended locations. The recommended locations may then be presented to the user,” [0084] “Possible validation may be achieved by comparing simulation outcomes with patient specific data representing data operating with the treatment,” and [0134] “The parameters defining these added structures may be predetermined or user selectable. The processor 12 may receive an indication of one or more parameters. The indication may be by processing data. For example, different values of a parameter are attempted.”).
However, Mansi does not explicitly teach performing the surgical procedure according to the simulated parameters selected based on direct comparison to optimize the at least one clinical outcome.
In an analogous virtual percutaneous valve implantation field of endeavor, Zaeuner teaches a method of computer assisted procedure using a simulation system, ([0017] “Accordingly, is to be understood that embodiments of the present invention may be performed within a computer system using data stored within the computer system” and [0019] “FIG. 1 illustrates a method of virtual valve implantation according to an embodiment of the present invention. The method of FIG. 1 transforms 3D medical image data representing a patient's anatomy to generate a patient-specific anatomical model and uses the anatomical model to virtually simulate the implantation of one or more implants (also referred to herein as "stents").”), the method comprising: performing the surgical procedure according to the simulated parameters that optimize the at least one clinical outcome ([0018] “In the pre-operative framework, pre-operative medical images, such as cardiac CT images, are acquired, a patient-specific anatomical model of the valve is estimated, and in-silico valve implantation under various interventional procedure conditions is performed for identification of an optimal device type of the prosthetic valve, size and deployment location, and treatment outcome prediction.”).
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the performing step of Zaeuner because the modification avoids improper placement of the implant (surgical object), which may result in a life threatening ischemic condition, poor hemodynamic performance, high gradients and suboptimal effective orifice, damaged vessel tissue, and/or arterial dissection, as taught by Zaeuner in [0004].
Regarding Claim 47, the modified method of Mansi teaches all limitations of Claim 45, as discussed above. Furthermore, Zaeuner teaches updating a procedural plan by modifying one or more of the simulated parameters in response to the predicted at least one clinical outcome to mitigate a risk associated with the surgical procedure ([0018] “In the pre-operative framework, pre-operative medical images, such as cardiac CT images, are acquired, a patient-specific anatomical model of the valve is estimated, and in-silico valve implantation under various interventional procedure conditions is performed for identification of an optimal device type of the prosthetic valve, size and deployment location, and treatment outcome prediction.”).
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the updating step of Zaeuner because the modification avoids improper placement of the implant (surgical object), which may result in a life threatening ischemic condition, poor hemodynamic performance, high gradients and suboptimal effective orifice, damaged vessel tissue, and/or arterial dissection, as taught by Zaeuner in [0004].
Regarding Claim 52, Mansi teaches all limitations of Claim 48, as discussed above. However, Mansi does not explicitly teach wherein the virtualization of the surgical procedure comprises real time comparisons of the simulated parameters of a transcatheter aortic valve (TAV) including a type of the TAV, a size of the TAV, and positioning of the TAV, and each corresponding to one of the at least one clinical outcome.
In an analogous virtual percutaneous valve implantation field of endeavor, Zaeuner teaches a system for planning a surgical procedure using a simulation system, (Abstract “A method and system for virtual percutaneous valve implantation”), wherein the virtualization of the surgical procedure comprises real time comparisons of the simulated parameters of a transcatheter aortic valve (TAV), ([0028] “In order to simulate valve replacement under various conditions, different implant models can be selected from the library and virtually deployed under different parameters, into the extracted patient-specific model.”), including a type of the TAV, (Abstract “The implant models maintained in the library are virtually deployed into the patient specific anatomical model of the heart valve to select an implant type […] for percutaneous valve implantation.”), a size of the TAV, (Abstract “The implant models maintained in the library are virtually deployed into the patient specific anatomical model of the heart valve to select an implant […] size […] for percutaneous valve implantation.”), and positioning of the TAV, (Abstract “The implant models maintained in the library are virtually deployed into the patient specific anatomical model of the heart valve to select […] deployment location and orientation for percutaneous valve implantation.”), and each corresponding to one of the at least one clinical outcome ([0031] “Returning to FIG. 1, at step 108, the virtual implant model deployment results are output. The virtual implant deployment results can provide quantitative and qualitative information used in planning and performing the percutaneous valve implantation. For example, using the virtual-deployment framework various implants can be tested and compared to select the best implant and implant size. Further, the virtual implantation can provide an optimal position and orientation for the selected implant with respect to the patient-specific model. Quantitatively, the forces that hold the stent to the wall can be calculated after virtual deployment. Hemodynamic performance of the implant can be predicted by quantifying paravalvular leakages, valve insufficiency, and effective orifice and systolic gradients across the aortic prosthesis.”).
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the real time comparisons of the simulated parameters of a TAV of Zaeuner because the modification avoids improper placement of the implant (surgical object), which may result in a life threatening ischemic condition, poor hemodynamic performance, high gradients and suboptimal effective orifice, damaged vessel tissue, and/or arterial dissection, as taught by Zaeuner in [0004].
Claims 42 and 53 are rejected under 35 U.S.C. 103 as being unpatentable over Mansi et al. (US 20120232386) in view of Chaturvedi et al. (“MRI evaluation prior to Transcatheter Aortic Valve Implantation […]”).
Regarding Claims 42 and 53, Mansi teaches all limitations of Claims 37 and 48, as discussed above. However, Mansi does not explicitly teach wherein generating the deformed analytical model comprises: calculating a first set of size measurements of the virtually deployed surgical at least one object in deployment comprising respective gap sizes, α2D1 and α2D2, each corresponding to a two-dimensional distance between a tip of a coronary leaflet and a coronary ostium of a coronary artery; calculating a second set of size measurements of the virtually deployed surgical at least one object in deployment comprising respective gap sizes, α3D1 and α3D2, each corresponding to a shortest three-dimensional distance between the coronary ostium of the coronary artery and a potential obstruction; and performing systematic data-fitting on at least the first and second sets of size measurements, and determining the data fitting model further comprises determining a statistical correlation, R2, based on the systematic data-fitting.
In an analogous evaluation prior to TAVI field of endeavor, Chaturvedi teaches wherein generating the deformed analytical model comprises:
a) calculating a first set of size measurements of the virtually deployed surgical at least one object in deployment comprising respective gap sizes, α2D1 and α2D2, each corresponding to a two-dimensional distance between a tip of a coronary leaflet and a coronary ostium of a coronary artery (Fig. 3, where measurements are understood to be taken from both left and right coronary arteries, and Coronary ostia “minimum distance values of 10-14 mm between the coronary ostia and leaflet insertion are usually suggested.”);
b) calculating a second set of size measurements of the virtually deployed surgical at least one object in deployment comprising respective gap sizes, α3D1 and α3D2, each corresponding to a shortest three-dimensional distance between the coronary ostium of the coronary artery and a potential obstruction (Aortic annulus “The annular plane is identified by the end systolic image below the insertion of leaflets by scrolling through this cine stack (Fig. 2c). This slice is used for assessing the minor & major diameters, area, and perimeter of the annulus. Annular diameters can also be obtained from a navigator-assisted free breathing diastolic phase 3-D SSFP sequence”); and
c) performing systematic data-fitting on at least the first and second sets of size measurements, and determining the data fitting model further comprises determining a statistical correlation, R2, based on the systematic data-fitting (Aortic annulus “Measurement of the annulus is important for correct selection of prosthesis size, type, and to avoid damage of the annulus if the valve is oversized and avoid paravalvular regurgitation if the valve is undersized,” Coronary ostia “The distance from the annulus to the coronary ostia is of importance to prevent occlusion of the coronary arteries by the displacement of the native aortic valve leaflets by the prosthesis,” and Post TAVI paravalvular regurgitation “Aortic regurgitation (AR) is the most frequent post procedural complication after TAVI and is linked to ad verse outcomes and mortality.”).
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the generation of the deformed analytical model of Chaturvedi because the modification ensures minimal complications following the procedure by ensuring the proper sizing and location.
Claims 46 are rejected under 35 U.S.C. 103 as being unpatentable over Mansi et al. (US 20120232386) in view of, Zaeuner et al. (US 20110153286), as applied to Claim 45, further in view of Mortier (US 20150112659).
Regarding Claim 46, the modified method of Mansi teaches all limitations of Claim 45, as discussed above. However, the modified method of Mansi does not explicitly teach wherein the at least one clinical outcome comprise at least one risk of at least one clinical complication.
In an analogous pre-operative simulation of trans-catheter implantation field of endeavor, Mortier teaches a method of planning a surgical procedure using a simulation system, ([0110] “virtually deploying said implant model into each of a plurality of the patient specific anatomical models maintained in said library to evaluate said implant model for a percutaneous implantation procedure.”), wherein the at least one clinical outcome comprise at least one risk of at least one clinical complication comprising one or more of: coronary obstruction, [0101] “the risk of coronary obstruction […] is predicted by virtually deploying an implant model representing an implant into the patient-specific anatomical model.”), paravalvular leakage, ([0097] “In a further preferred step, the amount of paravalvular regurgitation is predicted based on a geometrical analysis of said blood mesh. Hemodynamic performance of the implant can be predicted by quantifying paravalvular leakages […] across the aortic prosthesis” and [0140]-[0142] “It is the aim of the current invention to provide a report to the medical doctor, comprising: figures of the implanted device(s), colour plots of the incomplete apposition of the device(s). These plots give insight into possible paravalvular leaks”), thrombosis, conduction abnormalities, [0101] “the risk of […] conduction abnormalities is predicted by virtually deploying an implant model representing an implant into the patient-specific anatomical model.”), cerebrovascular events, and blood flow information indicative of one or more of: a paravalvular leakage, ([0097] “In a further preferred step, the amount of paravalvular regurgitation is predicted based on a geometrical analysis of said blood mesh. Hemodynamic performance of the implant can be predicted by quantifying paravalvular leakages […] across the aortic prosthesis” and [0140]-[0142] “It is the aim of the current invention to provide a report to the medical doctor, comprising: figures of the implanted device(s), colour plots of the incomplete apposition of the device(s). These plots give insight into possible paravalvular leaks”), thrombosis, pressure gradient, ([0097] “In a further preferred step, the amount of paravalvular regurgitation is predicted based on a geometrical analysis of said blood mesh. Hemodynamic performance of the implant can be predicted by quantifying […] effective orifice […] gradients across the aortic prosthesis.”), energy loss, and effective orifice area ([0097] “In a further preferred step, the amount of paravalvular regurgitation is predicted based on a geometrical analysis of said blood mesh. Hemodynamic performance of the implant can be predicted by quantifying […] effective orifice […] across the aortic prosthesis.”).
It would have been obvious to one of ordinary skill in the art at the time of applicant’s filing to modify the teachings of Mansi with the clinical complication of Mortier because predicting such complications results in better health and safety of the patient, as such complications can be fatal.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
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/MARIA CHRISTINA TALTY/Examiner, Art Unit 3797
/MICHAEL J CAREY/Supervisory Patent Examiner, Art Unit 3795
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