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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 2/13/2026 has been entered.
Applicant' s arguments, filed 2/13/2026, have been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Applicants have amended their claims, filed 2/13/2026, and therefore rejections newly made in the instant office action have been necessitated by amendment.
Claims 1-19 are the currently pending claims herby under examination. Claims 20-22 have been canceled.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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 1-19 are rejected under 35 U.S.C. 103 as obvious over Petroff et al. (US 20220061670 A1), hereto referred as Petroff, and further in view of Cohen et al. (US 20140094689 A1), hereto referred as Cohen.
Regarding claim 1, Petroff teaches that the method comprises: receiving, by one or more processors, a plurality of extravascular images of the vessel during a pullback of an intravascular imaging probe having a defined pullback length along a first region of the vessel (Petroff, [0253]: "System 10 can provide high resolution morphological images and other high-resolution morphological information, such as are produced using at least OCT data gathered by probe 100"; [0240]: "System 10 can add lengths, by turning the time-points of each snap-shot into distances. For example, for a zero-order: the pullback speed is used to convert to distance... a radiopaque marker of probe 100 can be identified at the start of pullback and at the end of the pullback, and an angiography image (frame) closest in time to the respective trigger... The distance traversed between the radiopaque marker at sequence (ii) and (iv) is the pullback distance (e.g. a distance of 50 mm). System 10 can map this known pullback distance along the artery shape, such as in a linear fashion", demonstrating that Petroff receives both extravascular images and determines and uses a defined pullback length, where the pullback length is explicitly calculated and known for mapping to the vessel geometry (angiography) and intravascular images (OCT) during a defined pullback length; [0125]: "processor 52... perform any type of data processing", [0123]: "store software routines, algorithms... and data acquired...", Petroff further teaches that processor 52 performs data processing on the acquired imaging data thereby performing the recited step by one or more processors); and detecting, by the one or more processors, locations of one or more markers in the plurality of extravascular images (Petroff, [0113]: "Imaging probe 100 can comprise one or more visualizable markers along its length (e.g. along shaft 120), markers 131 a-b shown (marker 131 herein). Marker 131 can comprise markers selected from the group consisting of: radiopaque markers; ultrasonically reflective markers; magnetic markers; ferrous material; and combinations of one or more of these", [0115]: "In some embodiments, tip 119 can comprise a radiopaque marker configured to increase the visibility of imaging probe 100 under an X-ray or fluoroscope", [0240]: "...the radiopaque marker of probe 100 can be identified at the start of pullback and at the end of the pullback, and an angiography image (frame) closest in time to the respective trigger...", [0184]: "In some embodiments, the data can be registered using the location, size, and shape of one or more side branches of the selected artery", showing that Petroff uses both physical markers visible in extravascular images (e.g., radiopaque markers on the probe in angiography) and anatomical landmarks (side branches) seen in extravascular imaging as registration points for detection and localization; [0125]: "processor 52... perform any type of data processing", [0123]: "store software routines, algorithms... and data acquired...", Petroff further teaches that processor 52 performs data processing on the acquired imaging data thereby performing the recited step by one or more processors).
Also regarding claim 1, Petroff does not fully teach correlating, by the one or more processors, an apparent length of the first region of the vessel represented in the plurality of extravascular images with the defined pullback length based on the location of the one or more markers in the plurality of extravascular images. Rather, Petroff determines a known pullback length and explicitly maps that known pullback length onto the vessel geometry represented in the extravascular images (Petroff, [0240]: "The distance traversed... is the pullback distance... System 10 can map this known pullback distance along the artery shape"; [0184]: "OCT data and Non-OCT data (e.g. angiography data) can be registered (e.g. correlated)"; [0125]: "processor 52... perform any type of data processing"; [0123]: "store software routines, algorithms... and data acquired..."), where Petroff performs the recited correlating step by one or more processors. Thus, Petroff correlates a physically defined pullback length with the vessel as represented in the extravascular images using marker-based localization in combination with pullback-derived distance calculations based on speed and time, mapping a known physical length onto the image representation in a one-directional manner from physical space to image space, without establishing a bidirectional calibration relationship between the apparent image length and the physical length. In Petroff, the locations of the radiopaque markers anchor the pullback-derived length within the extravascular image, such that any correlation between physical length and image representation is based on the locations of the one or more markers in the plurality of extravascular images (Petroff, [0240]: "a radiopaque marker of probe 100 can be identified at the start of pullback and at the end of the pullback... The distance traversed... is the pullback distance"; [0113]: "Imaging probe 100 can comprise one or more visualizable markers along its length..."). However, Petroff does not derive a relationship between the apparent image length (i.e., a length as represented in the extravascular image) and the defined pullback length, and therefore does not explicitly teach correlating an apparent length in the extravascular image with the defined pullback length to derive a calibration relationship between image representation and physical length.
Cohen teaches that calibration factors are determined by relating image-based representations to known physical dimensions (Cohen, ¶[0093]: "determine... calibration factors... based upon a known physical distance between two or more of the identified features"; ¶[0092]: "based upon a known physical dimension associated with one or more of the identified features"; ¶[0090]: "based upon a known speed at which the endoluminal device is moved through the lumen"), thereby establishing a relationship between apparent image dimensions and actual physical dimensions (¶[0044]: "determine... local calibration factors associated with respective portions of the roadmap image"), where the identified features include visible markers or anatomical landmarks whose locations are used to derive the calibration relationship.
Petroff provides a known pullback length and extravascular image representation, while Cohen teaches using known physical lengths, including motion-derived distances, to calibrate image representations and thereby correlate apparent image dimensions with actual physical dimensions.
It would have been prima facie obvious before the effective filing date of the claimed invention to have modified Petroff in view of Cohen to correlate an apparent length of a vessel in an extravascular image with a defined pullback length using calibration techniques, because Petroff already provides the known pullback length and image framework, and Cohen teaches using known physical distances to calibrate image representations. Such a modification would have been feasible because both references operate on co-registered intravascular and extravascular imaging data and rely on spatial relationships within the same imaging environment. The motivation for combining is to improve dimensional accuracy and correct projection-related distortions in extravascular imaging, thereby enabling more accurate vessel measurements.
Also regarding claim 1, the modified Petroff does not fully teach determining, by the one or more processors, a size of a second region of the vessel represented in the plurality of extravascular images based on the correlation of the apparent length of the first region of the vessel represented in the plurality of extravascular images with the defined pullback length. Rather, the modified Petroff determines characteristics of regions outside the pullback using angiography (Petroff, [0232]: "angiography data can be analyzed to determine the extent of stenosis proximal and distal to the clear portion of the pullback"; [0185]-[0187]: "cardiovascular flow dynamics can be calculated... estimate microvascular resistance distal to the selected artery"; [0125]: "processor 52... perform any type of data processing"; [0123]: "store software routines, algorithms... and data acquired..."), where Petroff performs the recited determining step by one or more processors. Thus, the modified Petroff determines parameters of second regions based on extravascular image data that is spatially related to the pullback-derived geometry of the vessel, which provides the spatial framework upon which the calibration relationship described above can be applied. However, it does not explicitly teach that the determination of the size of the second region is based on a correlation between apparent image length and pullback length, nor does it teach using a calibration relationship between image-based length and physical length when determining the size of the second region.
Cohen teaches that once calibration factors relating apparent image dimensions to actual physical dimensions are determined, those calibration relationships are used to derive measurements of portions of the lumen, including lengths (Cohen, ¶[0070]: "determine a length of a portion of the lumen that corresponds to a portion of the stack"; ¶[0067]-¶[0069]: "determine a parameter... including length... based upon the co-registering of the endoluminal data points").
Petroff provides determination of characteristics of regions outside the primary region using extravascular images, while Cohen teaches that calibrated relationships between image and physical dimensions are used to determine lengths of vessel portions. Thus, Petroff as modified by Cohen teaches determining a size of a second region based on the correlation, using the calibration relationship described above between apparent image length and actual physical length.
It would have been prima facie obvious before the effective filing date of the claimed invention to have further modified the modified Petroff in view of Cohen to determine a size of a second region of the vessel based on a correlation between apparent image length and pullback length because once calibration between image and physical dimensions is established, applying that calibration to measure additional regions is a predictable use of known techniques. This modification would have been feasible because Petroff already analyzes regions outside the pullback using a pullback-derived spatial framework and Cohen provides the calibration framework needed to convert apparent image-based representations into actual physical measurements based on that framework. The motivation for combining is to improve the accuracy and reliability of measurements of vessel regions beyond the primary imaging area, thereby enhancing diagnostic and analytical capabilities.
Regarding claim 2, the modified Petroff teaches that the size of the second region of the vessel includes at least one of a length of the second region, a cross-section diameter within the second region, and a cross-sectional area within the second region (Petroff, [0232]: "angiography data can be analyzed to determine the extent of stenosis proximal and distal to the clear portion of the pullback. Subsequently, Rd is calculated for these areas outside of the delineated pullback", showing that the system determines the extent or length of disease in a second region (Petroff uses “extent of stenosis” in reference to vessel regions, and a person of ordinary skill in the art would understand this to include the length of affected vessel, not merely severity at a single point), as well as the resistance (Rd, [0217]) which uses a diameter (cross-section diameter) and by extension, cross-sectional area, in a region outside of the primary pullback zone).
Regarding claim 3, the modified Petroff implicitly, inherently, or obviously teaches that the method further comprises computing, by the one or more processors, a virtual flow reserve (VFR) of the vessel based on a plurality of images captured by the intravascular imaging probe and based on the determined size of the second region of the vessel (Petroff, [0185]: "In Step 1320, cardiovascular flow dynamics can be calculated based on the analyzed data (e.g. the OCT data and/or Non-OCT data collected and/or analyzed). In some embodiments, system 10 is configured to estimate microvascular resistance distal to the selected artery", showing that system 10 (which operates via one or more processors, [0123] and [0125]) calculates flow reserve using as inputs the analyzed data (including measurements of size and attributes of additional vessel regions (the 'second region')) so that the calculation is performed based on the determined size of the second region; [0249]: "For example, system 10 can be configured to produce pre and post-treatment FFR data. In some embodiments, system 10 compares information produced based on image data (e.g. OCT data and/or non-OCT data) gathered prior to treatment, to information produced based on image data (e.g. OCT Data and/or non-OCT data) gathered after a treatment has been performed", the modified Petroff discloses that the system’s processors generate FFR (VFR) by using analyzed image data from before and after an intervention, and this process is dependent on the characteristics ,including size, of the second region, thereby satisfying the requirement that VFR is computed based on the determined size of the second region; [0253]: "In some embodiments, the high-resolution information produced by system 10 is based on OCT data and non-OCT data (e.g. at least angiography data)" the modified Petroff confirms that the virtual flow reserve calculation performed by the processors utilizes both intra- and extravascular images, and incorporates the measured vessel characteristics of the second region as part of the computation). Although the modified Petroff does not use the phrasing “based on the determined size of the second region,” a person of ordinary skill in the art would understand that computation of virtual flow reserve (FFR/VFR) necessarily requires the measured size (diameter, area, length) of the relevant vessel region as an input, since these attributes are fundamental to any hemodynamic calculation.
Regarding claim 4, the modified Petroff implicitly, inherently, or obviously teaches that the VFR of the vessel is computed based on a distance between a vessel centerline and a boundary of the vessel within the second region of the vessel identified in at least one of the plurality of extravascular images (Petroff, [0232]: "If the tissue at the end portions is diseased, angiography data can be analyzed to determine the extent of stenosis proximal and distal to the clear portion of the pullback", the modified Petroff demonstrates that a “second region”, meaning any area proximal or distal to the intravascular pullback zone, is identified and analyzed using extravascular imaging, with boundaries determined for VFR calculation; [0183]: "In some embodiments, non-OCT data is analyzed to identify one or more of the following: vessel geometries (e.g. curves, tapers, and/or trajectories)... vessel diameters...", the modified Petroff teaches that extravascular images are analyzed to determine vessel boundaries and diameters, which, when paired with a vessel centerline, provide the data necessary for centerline-to-boundary measurements in the second region; [0185]: "In Step 1320, cardiovascular flow dynamics can be calculated based on the analyzed data (e.g. the OCT data and/or Non-OCT data collected and/or analyzed)", the modified Petroff explicitly teaches using geometry from both OCT and extravascular imaging for flow reserve calculations, including in regions beyond the primary OCT pullback; [0194]: "System 10 can use the 3D coordinates of the centerline...to calculate cross-sectional images and/or reconstruct the vessel geometry in 3D space...", while this passage discusses centerline use for vessel reconstruction, the modified Petroff does not explicitly state that this is applied to extravascular images; however, a person of ordinary skill in the art would understand that all vessel geometry analyses, including in extravascular images, necessarily use a centerline as a reference, and such centerline-to-boundary distances are standard in VFR computation). A person of ordinary skill in the art would recognize that Petroff’s method involves using extravascular imaging to determine vessel geometry, including the distance from centerline to boundary, in second regions (i.e., regions proximal or distal to the primary pullback), and that these values are required inputs for VFR calculation. All such steps are performed by system 10’s processor.
Regarding claim 5, the modified Petroff teaches that the second region of the vessel includes at least one of a distal epicardial region and a proximal epicardial region of the vessel (Petroff, [0232]: "If the tissue at the end portions is diseased, angiography data can be analyzed to determine the extent of stenosis proximal and distal to the clear portion of the pullback", the modified Petroff confirms that after imaging and correlating a primary region, the system analyzes regions beyond (proximal and distal) to the main pullback zone using extravascular imaging; [0184]: "system 10 can comprise a digital model of the expected branching of one or more of the major vessels of the heart, for example the LCx, RCA, and/or LAD arteries", demonstrating that both OCT and angiography data are registered with respect to a digital model of the major epicardial arteries, thereby encompassing analysis of both distal and proximal epicardial regions).
Regarding claim 6, the modified Petroff teaches that determining the size of a second region of the vessel includes determining a length of the distal epicardial region and a length of the proximal epicardial region (Petroff, [0232]: "If the tissue at the end portions is diseased, angiography data can be analyzed to determine the extent of stenosis proximal and distal to the clear portion of the pullback", the modified Petroff explicitly discusses analysis of regions proximal and distal to the main imaging area, including determination of disease extent (where a person of ordinary skill in the art would understand this to include the length of affected vessel, not merely severity at a single point) in these epicardial segments, thus encompassing determination of both distal and proximal region lengths; and [0184] demonstrates the region of interest to be epicardial arteries).
Regarding claim 7, the modified Petroff does not fully teach correlating the apparent length of the first region of the vessel represented in the plurality of extravascular images with the defined pullback length includes scaling a lumen size represented in at least one of the plurality of extravascular images. Rather, the modified Petroff determines a known pullback length and maps that length onto the vessel geometry represented in the extravascular images (Petroff, [0240]: "The distance traversed between the radiopaque marker at sequence (ii) and (iv) is the pullback distance (e.g. a distance of 50 mm). System 10 can map this known pullback distance along the artery shape, such as in a linear fashion. If landmarks are detected in the OCT image at time tlm, system 10 can add further corrections, where the distance moved is tlm, times the pullback speed"; [0189]: "In some embodiments, the data is shown in an overlay arrangement... Calculated vessel sizes are displayed along with the OCT images and/or non-OCT images"). Thus, the modified Petroff provides a known physical length and associates that length with the vessel representation in the extravascular images. However, it does not explicitly teach scaling a lumen size in the extravascular images based on a calibration relationship between apparent image dimensions and the defined pullback length.
Cohen teaches that calibration factors are determined by relating image-based representations to known physical dimensions and that such calibration relationships are used to determine dimensions of portions of the lumen (Cohen, ¶[0093]: "determine... calibration factors... based upon a known physical distance between two or more of the identified features"; ¶[0092]: "based upon a known physical dimension associated with one or more of the identified features"; ¶[0044]: "determine... local calibration factors associated with respective portions of the roadmap image"; ¶[0070]: "determine a length of a portion of the lumen that corresponds to a portion of the stack"). Such calibration includes scaling image-based lumen size to correspond to actual physical dimensions, and is performed as part of correlating apparent image length with actual physical length as set forth in claim 1. the modified Petroff provides the pullback-derived physical length and spatial mapping to the extravascular image, while Cohen teaches using known physical dimensions to scale image-based representations of the lumen as part of that correlation.
It would have been prima facie obvious before the effective filing date of the claimed invention to have further modified the modified Petroff in view of Cohen to scale a lumen size represented in the extravascular images as part of the correlation between apparent image length and a defined pullback length because Petroff already provides a known physical length and image mapping framework, and Cohen teaches using known physical dimensions to calibrate and scale image-based representations as part of that correlation. Such a modification would have been feasible because both references operate on co-registered intravascular and extravascular imaging data and rely on spatial relationships within the same imaging environment. The motivation for combining is to improve the dimensional accuracy of lumen size measurements and to correct projection-related distortion in extravascular images, thereby enabling more accurate assessment of vessel dimensions.
Regarding claim 8, the modified Petroff teaches that the plurality of extravascular images are taken from a plurality of locations relative to the vessel (Petroff, [0127]: "Second imaging device 15 can comprise an imaging device such as one or more imaging devices selected from the group consisting of: an X-ray; a fluoroscope such as a single plane or biplane fluoroscope; a CT Scanner; an MRI; a PET Scanner; an ultrasound imager; and combinations of one or more of these. In some embodiments, second imaging device 15 comprises a device configured to perform rotational angiography", the modified Petroff expressly discloses that extravascular images may be acquired using one or more different imaging modalities, including rotational acquisition for multiple spatial perspectives).
Regarding claim 9, the modified Petroff teaches that the system analyzes the plurality of extravascular images so as to identify a three-dimensional orientation of one or more objects relative to the vessel (Petroff, [0127]: "Second imaging device 15 can comprise an imaging device such as one or more imaging devices... and combinations of one or more of these. In some embodiments, second imaging device 15 comprises a device configured to perform rotational angiography", the modified Petroff expressly discloses that multiple extravascular imaging modalities, including rotational angiography, provide images from varying perspectives, implicitly supporting the identification of 3D orientation; [0191]: "System 10 can be configured to calculate the flow dynamics... using a full 3D Navier-Stokes simulation... numerous geometric and other features of the imaged area", the modified Petroff confirms that images from different locations are used to reconstruct and determine 3D relationships of anatomical features and objects in the vessel; [0184]: "the data can be registered using the location, size, and shape of one or more side branches of the selected artery," the modified Petroff teaches that the system identifies the three-dimensional position and orientation of vessel branches (objects) relative to the vessel, based on multiple extravascular images and registration).
Regarding claim 10, the modified Petroff teaches that the one or more objects comprises a branch from the vessel and wherein the three-dimensional orientation of the branch includes a position and takeoff angle of the branch relative to the vessel (Petroff, [0180]: "System 10 can be configured to calculate (e.g. via algorithm 51) the branch angle of a side branch from the imaged artery. In some embodiments, the branch angle is used by algorithm 51 to calculate the side branch vessel diameter. System 10 can be configured to reconstruct at least a portion of the side branch from the OCT data (e.g. from the image slices of the OCT data), and/or from non-OCT data (e.g. from angiography data). In some embodiments, system 10 is configured to calculate the relationship between the side branch angle and the diameter of the size of the side branch (e.g. the size of the side branch relative to the size of the imaged artery)," the modified Petroff expressly demonstrates that the system identifies both the position and takeoff angle (branch angle) of vessel branches relative to the main vessel, based on analysis of OCT and/or extravascular (angiography) images; [0184]: "the data can be registered using the location, size, and shape of one or more side branches of the selected artery," the modified Petroff further confirms that the three-dimensional position and orientation of side branches (objects) relative to the vessel are determined through data registration).
Regarding claim 11, the modified Petroff implicitly, inherently, or obviously teaches that the one or more processors are further configured to compute a virtual flow reserve (VFR) of the vessel based on the identified position and takeoff angle of the branch (Petroff, [0180]: "...the branch angle is used by algorithm 51 to calculate the side branch vessel diameter... System 10 is configured to calculate the relationship between the side branch angle and the diameter...," the modified Petroff shows the system analyzes position and angle of vessel branches and incorporates these values in anatomical modeling for flow calculation; [0184]: "...the data can be registered using the location, size, and shape of one or more side branches of the selected artery," the modified Petroff confirms that branch features are included in the integrated model; [0191]: "System 10 can be configured to calculate the flow dynamics... using a full 3D Navier-Stokes simulation... numerous geometric and other features of the imaged area," the modified Petroff shows that VFR/FFR computation is based on comprehensive 3D geometry, which includes branch position and angle). Although the modified Petroff does not expressly state that VFR is computed solely from branch position and angle, the reference clearly teaches that anatomical features such as branch location and takeoff angle are measured and incorporated into the 3D anatomical vessel model, which is then used by the system’s processors to perform comprehensive flow reserve analysis using computational fluid dynamics (CFD). Because accurate CFD-based VFR/FFR calculations depend on complete vessel geometry, including the spatial relationships of all branches, one of ordinary skill in the art would understand that the contribution of branch position and angle is implicitly included in the flow reserve computation. This integration ensures that physiological models realistically represent the dynamics of blood flow in complex vascular networks, resulting in clinically meaningful and reliable VFR assessments.
Regarding claim 12, Petroff teaches that the system for identifying attributes of a vessel comprises: one or more memories for storing images of the vessel (Petroff, [0108]: "Imaging system 10 can further comprise multiple imaging devices, second imaging device 15 shown" Petroff shows that the system includes hardware for capturing and storing vessel images; [0123]: "Processor 52 can include one or more memory storage components, such as one or more memory circuits which store software routines, algorithms (e.g. algorithm 51), and other operating instructions of system 10, as well as data acquired by imaging probe 100, second imaging device 15, and/or another component of system 10", Petroff expressly states that the system includes one or more memory circuits for storing and processing images) and one or more processors (Petroff, [0125]: "Console 50 can further comprise a processing assembly, processor 52, configured to execute algorithm 51, and/or perform any type of data processing, such as digital signal processing", Petroff confirms that one or more processors are present for controlling, analyzing, and processing imaging data) configured to: capture a plurality of extravascular images of the vessel during a pullback of an intravascular imaging probe having a defined pullback length along a first region of the vessel (Petroff, [0127]: "Second imaging device 15 can comprise an imaging device such as one or more imaging devices selected from the group consisting of: an X-ray; a fluoroscope such as a single plane or biplane fluoroscope; a CT Scanner; an MRI; a PET Scanner; an ultrasound imager; and combinations of one or more of these", Petroff describes at least one extravascular imaging device used for capturing images; [0253]: "System 10 can provide high resolution morphological images and other high-resolution morphological information... based on OCT data and non-OCT data (e.g. at least angiography data)", Petroff confirms the simultaneous use of intravascular and extravascular imaging; [0240]: "System 10 can add lengths, by turning the time-points of each snap-shot into distances... the radiopaque marker of probe 100 can be identified at the start of pullback and at the end of the pullback... The distance traversed between the radiopaque marker at sequence (ii) and (iv) is the pullback distance (e.g. a distance of 50 mm). System 10 can map this known pullback distance along the artery shape, such as in a linear fashion", Petroff teaches capturing both extravascular images (angiography) and intravascular images (OCT) during a defined pullback length); and detect locations of one or more markers in the plurality of extravascular images (Petroff, [0113]: "Imaging probe 100 can comprise one or more visualizable markers along its length (e.g. along shaft 120), markers 131 a-b shown (marker 131 herein). Marker 131 can comprise markers selected from the group consisting of: radiopaque markers; ultrasonically reflective markers; magnetic markers; ferrous material; and combinations of one or more of these", [0115]: "In some embodiments, tip 119 can comprise a radiopaque marker configured to increase the visibility of imaging probe 100 under an X-ray or fluoroscope", [0240]: "...the radiopaque marker of probe 100 can be identified at the start of pullback and at the end of the pullback, and an angiography image (frame) closest in time to the respective trigger...", [0184]: "In some embodiments, the data can be registered using the location, size, and shape of one or more side branches of the selected artery", showing that Petroff uses both physical markers visible in extravascular images (e.g., radiopaque markers on the probe in angiography) and anatomical landmarks (side branches) seen in extravascular imaging as registration points for detection and localization; where [0123] and [0125] discusses the processor used in the system).
Also regarding claim 12, Petroff does not fully teach correlating an apparent length of the first region of the vessel represented in the plurality of extravascular images with the defined pullback length based on the location of the one or more markers in the plurality of extravascular images. Rather, Petroff determines a known pullback length and explicitly maps that known pullback length onto the vessel geometry represented in the extravascular images (Petroff, [0240]: "The distance traversed... is the pullback distance... System 10 can map this known pullback distance along the artery shape"; [0184]: "OCT data and Non-OCT data (e.g. angiography data) can be registered (e.g. correlated)"). Thus, Petroff correlates a physically defined pullback length with the vessel as represented in the extravascular images using marker-based localization in combination with pullback-derived distance calculations based on speed and time, mapping a known physical length onto the image representation in a one-directional manner from physical space to image space, without establishing a bidirectional calibration relationship between the apparent image length and the physical length. In Petroff, the locations of the radiopaque markers anchor the pullback-derived length within the extravascular image, such that any correlation between physical length and image representation is based on the locations of the one or more markers in the plurality of extravascular images (Petroff, [0240]: "a radiopaque marker of probe 100 can be identified at the start of pullback and at the end of the pullback... The distance traversed... is the pullback distance"; [0113]: "Imaging probe 100 can comprise one or more visualizable markers along its length..."). However, Petroff does not derive a relationship between the apparent image length (i.e., a length as represented in the extravascular image) and the defined pullback length, and therefore does not explicitly teach correlating an apparent length in the extravascular image with the defined pullback length to derive a calibration relationship between image representation and physical length.
Cohen teaches that calibration factors are determined by relating image-based representations to known physical dimensions (Cohen, ¶[0093]: "determine... calibration factors... based upon a known physical distance between two or more of the identified features"; ¶[0092]: "based upon a known physical dimension associated with one or more of the identified features"; ¶[0090]: "based upon a known speed at which the endoluminal device is moved through the lumen"), thereby establishing a relationship between apparent image dimensions and actual physical dimensions (¶[0044]: "determine... local calibration factors associated with respective portions of the roadmap image"), where the identified features include visible markers or anatomical landmarks whose locations are used to derive the calibration relationship.
Petroff provides a known pullback length and extravascular image representation, while Cohen teaches using known physical lengths, including motion-derived distances, to calibrate image representations and thereby correlate apparent image dimensions with actual physical dimensions.
It would have been prima facie obvious before the effective filing date of the claimed invention to have modified Petroff in view of Cohen to correlate an apparent length of a vessel in an extravascular image with a defined pullback length using calibration techniques, because Petroff already provides the known pullback length and image framework, and Cohen teaches using known physical distances to calibrate image representations. Such a modification would have been feasible because both references operate on co-registered intravascular and extravascular imaging data and rely on spatial relationships within the same imaging environment. The motivation for combining is to improve dimensional accuracy and correct projection-related distortions in extravascular imaging, thereby enabling more accurate vessel measurements.
Also regarding claim 12, the modified Petroff does not fully teach determining a size of a second region of the vessel represented in the plurality of extravascular images based on the correlation of the apparent length of the first region of the vessel represented in the plurality of extravascular images with the defined pullback length. Rather, the modified Petroff determines characteristics of regions outside the pullback using angiography (Petroff, [0232]: "angiography data can be analyzed to determine the extent of stenosis proximal and distal to the clear portion of the pullback"; [0185]-[0187]: "cardiovascular flow dynamics can be calculated... estimate microvascular resistance distal to the selected artery"). Thus, the modified Petroff determines parameters of second regions based on extravascular image data that is spatially related to the pullback-derived geometry of the vessel, which provides the spatial framework upon which the calibration relationship described above can be applied. However, it does not explicitly teach that the determination of the size of the second region is based on a correlation between apparent image length and pullback length, nor does it teach using a calibration relationship between image-based length and physical length when determining the size of the second region.
Cohen teaches that once calibration factors relating apparent image dimensions to actual physical dimensions are determined, those calibration relationships are used to derive measurements of portions of the lumen, including lengths (Cohen, ¶[0070]: "determine a length of a portion of the lumen that corresponds to a portion of the stack"; ¶[0067]-¶[0069]: "determine a parameter... including length... based upon the co-registering of the endoluminal data points").
Petroff provides determination of characteristics of regions outside the primary region using extravascular images, while Cohen teaches that calibrated relationships between image and physical dimensions are used to determine lengths of vessel portions. Thus, Petroff as modified by Cohen teaches determining a size of a second region based on the correlation, using the calibration relationship described above between apparent image length and actual physical length.
It would have been prima facie obvious before the effective filing date of the claimed invention to have further modified the modified Petroff in view of Cohen to determine a size of a second region of the vessel based on a correlation between apparent image length and pullback length because once calibration between image and physical dimensions is established, applying that calibration to measure additional regions is a predictable use of known techniques. This modification would have been feasible because Petroff already analyzes regions outside the pullback using a pullback-derived spatial framework and Cohen provides the calibration framework needed to convert apparent image-based representations into actual physical measurements based on that framework. The motivation for combining is to improve the accuracy and reliability of measurements of vessel regions beyond the primary imaging area, thereby enhancing diagnostic and analytical capabilities.
Regarding claim 13, the modified Petroff teaches that the size of the second region of the vessel includes at least one of a length of the second region, a cross-section diameter within the second region, and a cross-sectional area within the second region (Petroff, [0232]: "angiography data can be analyzed to determine the extent of stenosis proximal and distal to the clear portion of the pullback. Subsequently, Rd is calculated for these areas outside of the delineated pullback" showing that the system determines the extent or length of disease in a second region (the modified Petroff uses “extent of stenosis” in reference to vessel regions, and a person of ordinary skill in the art would understand this to include the length of affected vessel, not merely severity at a single point), as well as the resistance (Rd, [0217]) which uses a diameter (cross-section diameter) and by extension, cross-sectional area, in a region outside of the primary pullback zone).
Regarding claim 14, the modified Petroff implicitly, inherently, or obviously teaches that the system is configured to compute a virtual flow reserve (VFR) of the vessel based on a plurality of images captured by the intravascular imaging probe and based on the determined size of the second region of the vessel (Petroff, [0185]: "In Step 1320, cardiovascular flow dynamics can be calculated based on the analyzed data (e.g. the OCT data and/or Non-OCT data collected and/or analyzed). In some embodiments, system 10 is configured to estimate microvascular resistance distal to the selected artery" showing that system 10 (which operates via one or more processors, [0123] and [0125]) calculates flow reserve using as inputs the analyzed data, including measurements of size and attributes of additional vessel regions (the 'second region'), so that the calculation is performed based on the determined size of the second region; [0249]: "For example, system 10 can be configured to produce pre and post-treatment FFR data. In some embodiments, system 10 compares information produced based on image data (e.g. OCT data and/or non-OCT data) gathered prior to treatment, to information produced based on image data (e.g. OCT Data and/or non-OCT data) gathered after a treatment has been performed" the modified Petroff discloses that the system’s processors generate FFR (VFR) by using analyzed image data from before and after an intervention, and this process is dependent on the characteristics, including size, of the second region, thereby satisfying the requirement that VFR is computed based on the determined size of the second region; [0253]: "In some embodiments, the high-resolution information produced by system 10 is based on OCT data and non-OCT data (e.g. at least angiography data)" the modified Petroff confirms that the virtual flow reserve calculation performed by the processors utilizes both intra- and extravascular images, and incorporates the measured vessel characteristics of the second region as part of the computation). Although the modified Petroff does not use the phrasing “based on the determined size of the second region,” a person of ordinary skill in the art would understand that computation of virtual flow reserve (FFR/VFR) necessarily requires the measured size (diameter, area, length) of the relevant vessel region as an input, since these attributes are fundamental to any hemodynamic calculation.
Regarding claim 15, the modified Petroff implicitly, inherently, or obviously teaches that the system is configured to compute the VFR of the vessel based on a distance between a vessel centerline and a boundary of the vessel within the second region of the vessel identified in at least one of the plurality of extravascular images (Petroff, [0232]: "If the tissue at the end portions is diseased, angiography data can be analyzed to determine the extent of stenosis proximal and distal to the clear portion of the pullback" the modified Petroff demonstrates that a “second region”, meaning any area proximal or distal to the intravascular pullback zone, is identified and analyzed using extravascular imaging, with boundaries determined for VFR calculation; [0183]: "In some embodiments, non-OCT data is analyzed to identify one or more of the following: vessel geometries (e.g. curves, tapers, and/or trajectories)... vessel diameters..." the modified Petroff teaches that extravascular images are analyzed to determine vessel boundaries and diameters, which, when paired with a vessel centerline, provide the data necessary for centerline-to-boundary measurements in the second region; (Petroff, [0185]: "In Step 1320, cardiovascular flow dynamics can be calculated based on the analyzed data (e.g. the OCT data and/or Non-OCT data collected and/or analyzed)" the modified Petroff explicitly teaches using geometry from both OCT and extravascular imaging for flow reserve calculations, including in regions beyond the primary OCT pullback; (Petroff, [0194]: "System 10 can use the 3D coordinates of the centerline...to calculate cross-sectional images and/or reconstruct the vessel geometry in 3D space..." While this passage discusses centerline use for vessel reconstruction, the modified Petroff does not explicitly state that this is applied to extravascular images; however, a person of ordinary skill in the art would understand that all vessel geometry analyses, including in extravascular images, necessarily use a centerline as a reference, and such centerline-to-boundary distances are standard in VFR computation). A person of ordinary skill in the art would recognize that Petroff’s system involves using extravascular imaging to determine vessel geometry, including the distance from centerline to boundary, in second regions (i.e., regions proximal or distal to the primary pullback), and that these values are required inputs for VFR calculation. All such steps are performed by system 10’s processor.
Regarding claim 16, the modified Petroff teaches that the second region of the vessel includes at least one of a distal epicardial region and a proximal epicardial region of the vessel (Petroff, [0232]: "If the tissue at the end portions is diseased, angiography data can be analyzed to determine the extent of stenosis proximal and distal to the clear portion of the pullback" the modified Petroff confirms that after imaging and correlating a primary region, the system analyzes regions beyond (proximal and distal) to the main pullback zone using extravascular imaging; [0184]: "system 10 can comprise a digital model of the expected branching of one or more of the major vessels of the heart, for example the LCx, RCA, and/or LAD arteries" demonstrating that both OCT and angiography data are registered with respect to a digital model of the major epicardial arteries, thereby encompassing analysis of both distal and proximal epicardial regions).
Regarding claim 17, the modified Petroff does not fully teach correlating the apparent length of the first region of the vessel represented in the plurality of extravascular images with the defined pullback length includes scaling a lumen size represented in at least one of the plurality of extravascular images. Rather, the modified Petroff determines a known pullback length and maps that length onto the vessel geometry represented in the extravascular images (Petroff, [0240]: "The distance traversed between the radiopaque marker at sequence (ii) and (iv) is the pullback distance (e.g. a distance of 50 mm). System 10 can map this known pullback distance along the artery shape, such as in a linear fashion. If landmarks are detected in the OCT image at time tlm, system 10 can add further corrections, where the distance moved is tlm times the pullback speed"; [0189]: "In some embodiments, the data is shown in an overlay arrangement... Calculated vessel sizes are displayed along with the OCT images and/or non-OCT images"). Thus, the modified Petroff provides a known physical length and associates that length with the vessel representation in the extravascular images. However, it does not explicitly teach scaling a lumen size in the extravascular images based on a calibration relationship between apparent image dimensions and the defined pullback length.
Cohen teaches that calibration factors are determined by relating image-based representations to known physical dimensions and that such calibration relationships are used to determine dimensions of portions of the lumen (Cohen, ¶[0093]: "determine... calibration factors... based upon a known physical distance between two or more of the identified features"; ¶[0092]: "based upon a known physical dimension associated with one or more of the identified features"; ¶[0044]: "determine... local calibration factors associated with respective portions of the roadmap image"; ¶[0070]: "determine a length of a portion of the lumen that corresponds to a portion of the stack"). Such calibration includes scaling image-based lumen size to correspond to actual physical dimensions, and is performed as part of correlating apparent image length with actual physical length as set forth in claim 1. Petroff provides the pullback-derived physical length and spatial mapping to the extravascular image, while Cohen teaches using known physical dimensions to scale image-based representations of the lumen as part of that correlation.
It would have been prima facie obvious before the effective filing date of the claimed invention to have further modified the modified Petroff in view of Cohen to scale a lumen size represented in the extravascular images as part of the correlation between apparent image length and a defined pullback length because Petroff already provides a known physical length and image mapping framework, and Cohen teaches using known physical dimensions to calibrate and scale image-based representations as part of that correlation. Such a modification would have been feasible because both references operate on co-registered intravascular and extravascular imaging data and rely on spatial relationships within the same imaging environment. The motivation for combining is to improve the dimensional accuracy of lumen size measurements and to correct projection-related distortion in extravascular images, thereby enabling more accurate assessment of vessel dimensions.
Regarding claim 18, the modified Petroff teaches that the one or more objects comprises a branch from the vessel and wherein the three-dimensional orientation of the branch includes a position and takeoff angle of the branch relative to the vessel (Petroff, [0180]: "System 10 can be configured to calculate (e.g. via algorithm 51) the branch angle of a side branch from the imaged artery. In some embodiments, the branch angle is used by algorithm 51 to calculate the side branch vessel diameter. System 10 can be configured to reconstruct at least a portion of the side branch from the OCT data (e.g. from the image slices of the OCT data), and/or from non-OCT data (e.g. from angiography data). In some embodiments, system 10 is configured to calculate the relationship between the side branch angle and the diameter of the size of the side branch (e.g. the size of the side branch relative to the size of the imaged artery)," the modified Petroff expressly demonstrates that the system identifies both the position and takeoff angle (branch angle) of vessel branches relative to the main vessel, based on analysis of OCT and/or extravascular (angiography) images [0184]: "the data can be registered using the location, size, and shape of one or more side branches of the selected artery," the modified Petroff further confirms that the three-dimensional position and orientation of side branches (objects) relative to the vessel are determined through data registration).
Regarding claim 19, the modified Petroff implicitly, inherently, or obviously teaches that the one or more processors are further configured to compute a virtual flow reserve (VFR) of the vessel based on the identified position and takeoff angle of the branch (Petroff, [0180]: "...the branch angle is used by algorithm 51 to calculate the side branch vessel diameter... System 10 is configured to calculate the relationship between the side branch angle and the diameter...," the modified Petroff shows the system analyzes position and angle of vessel branches and incorporates these values in anatomical modeling for flow calculation; [0184]: "...the data can be registered using the location, size, and shape of one or more side branches of the selected artery," the modified Petroff confirms that branch features are included in the integrated model; [0191]: "System 10 can be configured to calculate the flow dynamics... using a full 3D Navier-Stokes simulation... numerous geometric and other features of the imaged area," the modified Petroff shows that VFR/FFR computation is based on comprehensive 3D geometry, which includes branch position and angle). Although the modified Petroff does not expressly state that VFR is computed solely from branch position and angle, the reference clearly teaches that anatomical features such as branch location and takeoff angle are measured and incorporated into the 3D anatomical vessel model, which is then used by the system’s processors to perform comprehensive flow reserve analysis using computational fluid dynamics (CFD). Because accurate CFD-based VFR/FFR calculations depend on complete vessel geometry, including the spatial relationships of all branches, one of ordinary skill in the art would understand that the contribution of branch position and angle is implicitly included in the flow reserve computation. This integration ensures that physiological models realistically represent the dynamics of blood flow in complex vascular networks, resulting in clinically meaningful and reliable VFR assessments.
Response to Arguments
35 U.S.C. §102/103
Applicant's arguments filed 2/13/2026, pages 6-8, regarding the previous 102/103 Rejections of claims 1-22 have been fully considered but are either moot (because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument; that is, there are new grounds of rejection) or are not persuasive as shown below.
Applicant’s Argument: Applicant contends that Petroff does not disclose or suggest correlating an apparent length of a vessel in an extravascular image with a defined pullback length, and further argues that Petroff merely performs registration or alignment between imaging modalities without establishing a relationship between projected image length and actual physical length.
Examiner’s Response: The arguments have been fully considered but are not persuasive. Petroff does not explicitly disclose deriving a calibration relationship between an apparent image length and a physical pullback length. The rejection does not rely on Petroff alone for this teaching. Rather, Petroff is relied upon for teaching a system that determines a defined pullback length and maps that known physical length onto an extravascular image of the vessel, thereby establishing a spatial framework in which physical distances are associated with image representations (Petroff, ¶[0240]; ¶[0184]). Petroff further teaches that marker locations are used to anchor the pullback-derived length within the image, thereby providing correspondence between physical locations and image features. Thus, Petroff determines and uses a defined pullback length, where the pullback length is explicitly calculated and known for mapping to the vessel geometry, and uses marker locations as the basis for anchoring that length within the image.
Applicant’s argument that Petroff merely performs registration is not persuasive because Petroff goes beyond simple alignment and explicitly converts pullback motion into a known physical length and maps that length along the vessel geometry. This constitutes associating physical dimensions with image-based representations, but Petroff does not explicitly derive a relationship between the apparent length in the image and the actual physical length.
Further, the rejection relies on Cohen for this missing teaching. Cohen expressly teaches determining calibration factors that relate image-based dimensions to known physical dimensions, including distances derived from device motion and feature spacing (Cohen, ¶[0090], ¶[0092], ¶[0093], ¶[0044]). These calibration factors establish a relationship between apparent image length and actual physical length, which directly addresses the limitation identified by Applicant. Because Petroff uses marker locations to anchor physical length within the image and Cohen determines calibration relationships based on identified features whose locations are used for calibration, the combined teachings establish a correlation between apparent length and physical length that is based on the location of the one or more markers. Cohen further teaches that such calibration relationships are used to determine lengths of vessel portions (¶[0070]; ¶[0067]-¶[0069]).
Accordingly, it would have been prima facie obvious before the effective filing date of the claimed invention to modify Petroff in view of Cohen to incorporate calibration of the extravascular image using the known pullback length, because Petroff already provides the known physical length and image mapping framework, and Cohen teaches using such known physical lengths to calibrate image representations. One of ordinary skill in the art would have recognized that applying Cohen’s calibration techniques to Petroff would improve the dimensional accuracy of measurements derived from extravascular images by accounting for projection-related distortion, which is a known issue in angiographic imaging.
Applicant’s Argument: Applicant contends that Petroff does not use a correlation between apparent image length and pullback length to determine the size of a second region of the vessel.
Examiner’s Response: The argument is not persuasive. Petroff teaches analyzing regions proximal and distal to the imaged pullback segment using extravascular imaging data (Petroff, ¶[0232]; ¶[0185]-¶[0187]). While Petroff does not explicitly state that such determinations are based on a calibrated relationship between apparent and actual length, Cohen teaches that once calibration factors are established, those relationships are used to determine lengths of vessel segments. Thus, when Petroff is modified in view of Cohen, the calibrated relationship between apparent image length and actual physical length is used as the basis for determining the size of the second region.
Applicant’s arguments do not address the combined teachings of Petroff and Cohen. When considered together, the references teach or render obvious all limitations of the claim. Therefore, the rejection is maintained.
Conclusion
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/AARON MERRIAM/Examiner, Art Unit 3791
/MATTHEW KREMER/Primary Examiner, Art Unit 3791
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