Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The following Office action in response to communications received July 22, 2026. Claims 1 and 14 have been amended. Therefore, claims 1-14 and 17-19 are pending and addressed below.
Applicant’s amendments to the claims are not sufficient to overcome the rejections set forth in the previous office action dated April 22, 2026.
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 1–14 and 17–19 is/are rejected under 35 U.S.C. 103 as being unpatentable over
Pub. No.: US 2007/0038061 A1 to Huennekens et al. in view of Pub. No.: US 2010/0284601 A1 to Rubner et al. further in view of Pub. No.: US 2014/0334709 A1 to Siewerdsen et al. further in view of Pub. No.: US 2021/0295544 A1 to Yan et al.
Claim 1 recites:
“A method for visual support in a medical intervention on a hollow organ of a patient, the method comprising: obtaining reference data that includes a pre-operative reference representation of the hollow organ, wherein the reference data includes items of planning information relating to a location of at least one characteristic feature of the hollow organ in the pre-operative reference representation; generating an X-ray projection image of the hollow organ; determining items of overlay information based on the reference data; displaying, by a display device, an overlay image that corresponds to the X-ray projection image overlaid with the items of overlay information; determining a reference volume in the pre-operative reference representation as a function of the items of planning information; generating a reconstruction of a volume of the patient corresponding to the reference volume using a tomosynthesis method; generating registration data, the generating of the registration data comprising registering the reference volume in relation to the reconstruction; transforming the X-ray projection image or the items of overlay information in accordance with the generated registration data; and overlaying the items of overlay information on the transformed X-ray projection image or overlaying the transformed items of overlay information on the X-ray projection image, wherein generating registration data comprises generating 3D/3D registration data, wherein the X-ray projection image is two-dimensional (2D), and wherein the transforming comprises transforming the 2D X-ray projection image in accordance with the generated 3D/3D registration data.”
Huennekens teaches:
“A method for visual support in a medical intervention on a hollow organ of a patient.” Huennekens teaches creating coordinated graphical images from angiography and IVUS data for use in diagnostic and treatment regimens, including balloon angioplasty and atherectomy performed on arteries, which are hollow organs, see paragraphs 0002–0003 and 0006–0007.
“Obtaining reference data that includes a pre-operative reference representation of the hollow organ, wherein the reference data includes items of planning information relating to a location of at least one characteristic feature of the hollow organ in the pre-operative reference representation.” Huennekens teaches initially creating an angiographic image of a vessel segment and acquiring an IVUS vessel-image data set distinct from the angiographic data. Huennekens further teaches creating a volumetric vessel-wall model including diseased and normal portions, in which features including stenotic area 20, area of vulnerability 75, necrotic core 80, and EEL 50 are identified and localized for planning and therapy guidance, see paragraphs 0030–0032.
“Generating an X-ray projection image of the hollow organ.” Huennekens teaches forming an angiographic image of a blood-vessel segment as a two-dimensional or three-dimensional X-ray representation and describes using two two-dimensional angiographic images to create a three-dimensional graphical representation of the vessel lumen, see paragraphs 0036 and 0056–0059.
“Determining items of overlay information based on the reference data.” Huennekens teaches processing IVUS frames using automatic border-detection algorithms to identify luminal boundary 125 and EEL 110 and performing tissue characterization of IVUS RF backscatter to classify and color-code plaque components and stent materials, with cross-sectional and longitudinal displays showing the distribution of these components throughout the vessel volume, see paragraphs 0031–0032.
“Displaying, by a display device, an overlay image that corresponds to the X-ray projection image overlaid with the items of overlay information.” Huennekens teaches co-registering IVUS information with angiographic images and overlaying a three-dimensional reconstruction 165, including a lumen border, plaque composition, necrotic cores, and EEL, onto live two-dimensional angiography images. Huennekens thereby displays a projection of the plaque volume on the X-ray lumen image for use during diagnosis and therapy, see paragraphs 0033–0037.
“Determining a reference volume in the pre-operative reference representation as a function of the items of planning information.” Huennekens teaches pulling back the imaging catheter over a desired vessel length, obtaining imaging information along that length, and creating, from circumferential cross-section images, a volumetric vessel-wall model including diseased and normal portions. Huennekens further teaches that diseased regions, including stenosis 60, area of vulnerability 75, and necrotic cores 80a–80c, define particular segments and regions of interest within the reconstructed vessel volume for planning stent placement, debulking, and targeted therapy, see paragraphs 0030–0032 and 0036–0037.
“Generating registration data, the generating of the registration data comprising registering the reference volume in relation to the reconstruction.” Huennekens teaches obtaining axial and circumferential co-registration between IVUS-derived volumetric vessel data and a three-dimensional angiographic image. Huennekens computes lumen area from both modalities along the vessel, applies a best-fit algorithm that minimizes the sum of squared differences between the respective sequences to determine axial alignment, and determines best-fit angular rotations of IVUS frames relative to angiographic projections for circumferential alignment, thereby producing registration parameters that register the volumetric IVUS representation to the three-dimensional angiographic reconstruction, see paragraphs 0041–0047 and 0048–0050.
“Overlaying the items of overlay information on the transformed X-ray projection image or overlaying the transformed items of overlay information on the X-ray projection image.” Huennekens teaches using the co-registration to overlay the three-dimensional reconstruction 165 and IVUS-derived vessel information, including plaque and EEL, on live angiographic images, such that plaque volume is displayed over the X-ray lumen image to guide catheter-based interventions, see paragraphs 0036–0037.
Huennekens fails to explicitly teach:
“Generating a reconstruction of a volume of the patient corresponding to the reference volume using a tomosynthesis method.”
“Transforming the X-ray projection image or the items of overlay information in accordance with the generated registration data” using explicit image-transformation and source-detector-geometry parameters.
“Wherein generating registration data comprises generating 3D/3D registration data” specifically between a pre-operative 3D reference volume and an intra-operative tomosynthesis-derived 3D volume.
“Wherein the transforming comprises transforming the 2D X-ray projection image in accordance with the generated 3D/3D registration data.”
Rubner teaches:
“Generating a reconstruction of a volume of the patient corresponding to the reference volume using a tomosynthesis method.” Rubner teaches disposing a three-dimensional target in a fixed position relative to the subject, obtaining a sequence of X-ray video images of a region of interest while a C-arm is moved around the subject, determining the pose of the C-arm for each image using the target, selecting images based on criteria including resolution, motion, and region-of-interest size, and using a reconstruction engine with the selected images and pose data to calculate a three-dimensional volumetric data set of the region of interest, see paragraphs 0019–0022, 0025–0031, and 0038–0045.
Rubner further teaches that the reconstruction engine generates a three-dimensional volumetric data set from selected two-dimensional images and associated poses and that images representing slices of the subject’s body in any desired view can be displayed. Rubner further identifies tomographic algorithms, including ART and SART, for reconstruction, see paragraphs 0045–0050.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to include the tomosynthesis-based volume-reconstruction features taught by Rubner within the angiography/IVUS-based visualization and guidance system taught by Huennekens. The motivation would have been to provide an intra-operative C-arm-derived three-dimensional CT-type or tomosynthesis volume corresponding to the same vessel reference region, thereby enabling volumetric imaging of the region of interest during the intervention using existing C-arm equipment, see paragraphs 0045–0050 of Rubner.
Huennekens and Rubner fail to explicitly teach:
“Transforming the X-ray projection image or the items of overlay information in accordance with the generated registration data” using image-transformation and source-detector-geometry parameters to register a three-dimensional volume to a two-dimensional X-ray image.
“Wherein generating registration data comprises generating 3D/3D registration data” comprising correspondence data between a sample 3D image and a reference 3D image.
“Wherein the transforming comprises transforming the 2D X-ray projection image in accordance with the generated 3D/3D registration data.”
Siewerdsen teaches:
“Transforming the X-ray projection image or the items of overlay information in accordance with the generated registration data.” Siewerdsen teaches acquiring a three-dimensional image, such as CT or cone-beam CT, and one or more fixed two-dimensional X-ray images; initializing image-transformation and source-detector-geometry parameters; generating digitally reconstructed radiographs from the three-dimensional image using those parameters; computing an image-similarity metric between the fixed two-dimensional image and the reconstructed image; and iteratively updating the transformation and geometry parameters until the similarity metric is maximized. Siewerdsen thereby teaches registration data defining the geometric relationship between the three-dimensional image and the fixed two-dimensional X-ray image, see paragraphs 0023–0030, 0035–0042, and 0058–0067.
“Overlaying the items of overlay information on the transformed X-ray projection image or overlaying the transformed items of overlay information on the X-ray projection image.” Siewerdsen teaches generating a visualization image by overlaying the fixed two-dimensional image and the reconstructed two-dimensional image. Siewerdsen further teaches that the three-dimensional image may include pre-operative planning structures and that the fixed two-dimensional image may include intra-operative or post-operative radiographs, thereby relating planning information to current radiographs and verifying object presence and location, see paragraphs 0023–0024 and 0068–0075.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date
of the claimed invention to include the 3D-2D registration and transformation framework taught by
Siewerdsen with the systems/methods taught by Huennekens and Rubner with the motivation of
generating 3D/3D registration data between a pre-operative vessel reference volume and an
intra-operative tomosynthesis volume and using the resulting geometry parameters to transform and
overlay planning-based vessel information and tomosynthesis-derived volume information on current
X-ray projection images, thereby improving visual support for the intervention, see paragraphs
[0068-0075] of Siewerdsen.
Huennekens, Rubner, and Siewerdsen fail to explicitly teach:
“Wherein generating registration data comprises generating 3D/3D registration data,” where the 3D/3D registration data includes correspondence data between a sample 3D image and a reference 3D image.
“Wherein the transforming comprises transforming the 2D X-ray projection image in accordance with the generated 3D/3D registration data,” to the extent the claim requires that the 3D/3D registration data itself provides the correspondence or transformation information used in the 2D-image transformation.
Yan teaches:
“Wherein generating registration data comprises generating 3D/3D registration data.” Yan teaches “acquiring a 3D-3D registration sample,” wherein “the 3D-3D registration sample includes a sample 3D image, a reference 3D image and 3D-3D registration data,” and “the 3D-3D registration data includes correspondence data between the sample 3D image and the reference 3D image,” see paragraphs 0005–0008 and 0055–0059.
“Wherein generating registration data comprises generating 3D/3D registration data.” Yan explains that the 3D/3D registration data can be “data representing a specific transformation method when the sample 3D image is transformed into the reference 3D image,” see paragraph 0059.
“Wherein generating registration data comprises generating 3D/3D registration data.” Yan teaches that the 3D/3D registration data may comprise “the relative position coordinates of a same positioning point or a homologous point,” “a transformation matrix between the sample 3D image and the reference 3D image,” or “a correspondence table between regions of homologous images in the sample 3D image and the reference 3D image,” see paragraph 0061.
“Wherein the X-ray projection image is two-dimensional (2D).” Yan teaches “generating at least one dual-2D-image based on the sample 3D image,” wherein each dual-2D image is “a combination of 2D projection images of the sample 3D image in two different directions,” see paragraphs 0006–0008 and 0062.
“Wherein the X-ray projection image is two-dimensional (2D).” Yan teaches that the two 2D projection images may have “a same image form as that of a computed tomography image, an X-ray fluoroscopy image, a nuclear magnetic resonance image, an ultrasonic image or a fluorescence fluoroscopy image,” see paragraphs 0015–0017 and 0063.
“Wherein the transforming comprises transforming the 2D X-ray projection image in accordance with the generated 3D/3D registration data.” Yan does not use this precise claim language. Yan instead teaches “generating 2D-3D registration data corresponding to each dual-2D-image based on the 3D-3D registration data,” wherein “each 2D-3D registration data includes the correspondence data between the dual-2D-image and the reference 3D image,” see paragraphs 0006–0008, 0055–0057, and 0064–0065.
Yan explains that the 2D/3D registration data may be “data representing a specific transformation method when the dual-2D-image is transformed into the reference 3D image,” see paragraph 0064.
Yan also teaches acquiring a reference 3D image and sample 2D images, reconstructing each set of sample 2D images into a sample 3D image, acquiring correspondence data between each sample 3D image and the reference 3D image through 3D/3D image registration, and generating 2D/3D registration data corresponding to each dual-2D image “based on 3D-3D registration data,” see paragraphs 0077–0085.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Yan’s 3D/3D registration-data framework into the systems and methods taught by Huennekens, Rubner, and Siewerdsen. The combination would use Yan’s expressly disclosed correspondence data, transformation matrix, positioning-point coordinates, or homologous-region correspondence data between a sample 3D image and a reference 3D image to provide the upstream 3D/3D registration data. Siewerdsen’s image-transformation and source-detector-geometry parameters would then be used to transform and register the 2D X-ray projection image in the resulting Huennekens/Rubner image-guidance system. This combination would predictably maintain spatial correspondence among the pre-operative reference volume, the intra-operative tomosynthesis-derived volume, and the current two-dimensional X-ray projection image, thereby improving visual support during the intervention. Yan identifies image-guided surgery and image-guided radiotherapy as scenarios requiring sufficiently accurate, rapid, and robust image registration, see paragraph 0053.
As per Claim 2:“The method of claim 1, wherein the reference volume is determined as a planar slice, and wherein the method further comprises determining a slice thickness of the planar slice and a location of the planar slice in the pre-operative reference representation for determining the reference volume.”
Huennekens teaches:
“The method of claim 1, wherein the reference volume is determined as a planar slice.” Huennekens teaches that the vessel image data set can be a set of IVUS frames corresponding to circumferential cross-section slices taken at various positions along the vessel segment and uses these slices to build a volumetric model, see paragraphs and [0030–0032].
“… determining a slice thickness of the planar slice and a location of the planar slice in the pre-operative reference representation for determining the reference volume.” Huennekens teaches that the imaging catheter is pulled back over a desired length of the vessel, obtaining imaging information along this length, and that longitudinal displays and lumen-area graphs are generated as a function of IVUS frame number and linear displacement along the imaged vessel, thereby defining the position of each cross-sectional slice along the vessel and the segment of vessel wall modeled from those slices, see paragraphs [0031–0032] and [0041–0044].
Huennekens fails to explicitly teach:
Expressly labeling the reference volume itself as a “planar slice” in those words.
Explicitly computing and naming a numerical “slice thickness” parameter for that planar slice.
Rubner teaches:
“Wherein the reference volume is determined as a planar slice, and wherein the method further comprises determining a slice thickness of the planar slice and a location of the planar slice in the pre-operative reference representation for determining the reference volume.” Rubner teaches generating a three-dimensional volumetric data set of a region of interest from C-arm projections and explains that images representing slices of the subject’s body in any desired view can be displayed from the volumetric data, implying selection of slice location and thickness when extracting planar reconstructed slices from the volume, see paragraphs [0019–0022] and [0045–0050].
Huennekens and Rubner fail to explicitly teach:
That the planar slice and its slice thickness/location are determined specifically from pre-operative planning information about characteristic vessel features (e.g., stenosis, vulnerable plaque) as in Huennekens.
Siewerdsen teaches:
“Wherein the reference volume is determined as a planar slice … determining a slice thickness of the planar slice and a location of the planar slice in the pre-operative reference representation for determining the reference volume.” Siewerdsen teaches that the three-dimensional image used in registration can be a CT or cone-beam CT volume containing surgical planning data and that DRRs are generated from the 3D volume along specific projection directions, implicit in which is defining planar slices at selected locations and thickness within the volume for target structures, see paragraphs [0023–0030] and [0035–0042].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
As per Claim 3:“The method of claim 2, further comprising determining a parameter set for carrying out the tomosynthesis method as a function of the reference volume, wherein the tomosynthesis method is carried out in accordance with the parameter set.”
Huennekens teaches:
“The method of claim 2, further comprising determining a parameter set … as a function of the reference volume.” Huennekens teaches selecting and using a reference vessel region defined by slice location and extent, and using co-registered IVUS and angiographic information, including lumen-area behavior and locations of stenotic and vulnerable regions, to plan treatment (stent placement, atherectomy, drug delivery) based on that region, see paragraphs [0030–0032] and [0036–0037].
Huennekens fails to explicitly teach:
Any tomosynthesis method or explicit tomosynthesis “parameter set” for C-arm CT-type acquisition or reconstruction.
Selecting tomosynthesis parameters as a function of the reference volume.
Rubner teaches:
“Determining a parameter set for carrying out the tomosynthesis method as a function of the reference volume, wherein the tomosynthesis method is carried out in accordance with the parameter set.” Rubner teaches that images used for reconstruction are selected and acquisition/reconstruction behavior is governed by factors including desired image resolution and accuracy, instantaneous speed of motion of the C-arm, deviation from the motion path, and overall dimensions of the region of interest, and explains that the number and spacing of selected images depend on resolution and region size, effectively defining a parameter set (selection criteria, angular spacing, acquisition speed) chosen in relation to the region of interest being reconstructed, see paragraphs [0019–0022] and [0025–0031] and [0038–0045].
Huennekens and Rubner fail to explicitly teach:
That the tomosynthesis parameter set is chosen specifically with reference to a pre-operative reference vessel slice or volume used for overlay planning, as opposed to a generic region of interest.
Siewerdsen teaches:
“Determining a parameter set for carrying out the tomosynthesis method as a function of the reference volume.” Siewerdsen teaches solving for image-transformation and source–detector geometry parameters (e.g., six degrees of freedom for image transformation and three degrees of freedom for source–detector geometry) in a 3D–2D registration process, optionally using coarse-to-fine and parallel optimization, which requires defining parameter sets that control how the 3D image relates to 2D projections and how similarity is optimized, see paragraphs [0035–0042] and [0058–0067].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
As per Claim 4:“The method of claim 3, wherein the parameter set includes a recording angle range, and the recording angle range is determined as a function of the slice thickness the parameter set includes a reference recording direction corresponding to a predefined reference angle of the recording angle range, and the reference recording direction is determined as a function of the location of the planar slice the parameter set includes an isocenter position, and the isocenter position is determined as a function of the location of the planar slice or any combination thereof.”
Huennekens teaches:
“The method of claim 3, wherein the parameter set includes … determined as a function of the slice thickness … location of the planar slice … isocenter position … location of the planar slice.” Huennekens teaches selecting and using a reference vessel region (defined by slice location and extent) for co-registered imaging and therapy planning, and representing the vessel path and centerline in three dimensions relative to angiographic projection planes, see paragraphs [0030–0033] and [0036–0039].
Huennekens fails to explicitly teach:
Any explicit recording angle range, reference recording direction, or isocenter position for a tomosynthesis acquisition.
Determining such geometry parameters as functions of slice thickness or slice location.
Rubner teaches:
“Wherein the parameter set includes a recording angle range … determined as a function of the slice thickness … reference recording direction … determined as a function of the location of the planar slice … isocenter position … determined as a function of the location of the planar slice.” Rubner teaches moving the C-arm around the subject along a motion path while acquiring a sequence of X-ray images of a region of interest, determining the C-arm pose for each image, and selecting images based on resolution requirements, C-arm speed, deviation from the motion path, and overall dimensions of the region of interest, which defines an effective angular acquisition range and central viewing directions for reconstruction of the selected region, see paragraphs [0019–0022] and [0025–0031] and [0038–0045].
Huennekens and Rubner fail to explicitly teach:
Using the term “isocenter position” or explicitly describing “recording angle range” and “reference recording direction” in those exact words.
Explicitly tying the isocenter and reference direction specifically to a planar vessel slice defined from pre-operative planning data.
Siewerdsen teaches:
“Wherein the parameter set includes a recording angle range … reference recording direction … isocenter position … determined as a function of the location of the planar slice.” Siewerdsen teaches solving for six degrees of freedom of the 3D image transformation and three degrees of freedom of the source–detector geometry in a 3D–2D registration problem, starting from an unknown source–detector geometry for a radiography or fluoroscopy X-ray system and iteratively recovering an effective imaging geometry that encompasses angular range, projection directions, and an effective isocenter relative to the 3D volume, see paragraphs [0023–0030] and [0035–0042] and [0058–0067].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
As per Claim 5:“The method of claim 4, wherein carrying out the tomosynthesis method comprises generating a sequence of further X-ray projection images, wherein each X-ray projection image of the sequence of further X-ray projection images at least partially represents the hollow organ according to another predefined projection direction, respectively, wherein the other predefined projection directions of the further X-ray projection images of the sequence are characterized by a respective angle within the recording angle range in a plane, wherein the reference recording direction lies in the plane, and wherein generating the reconstruction comprises generating the reconstruction based on the sequence of further X-ray projection images.”
Huennekens teaches:
“The method of claim 4 … wherein carrying out the tomosynthesis method comprises generating a sequence of further X-ray projection images … each X-ray projection image … represents the hollow organ according to another predefined projection direction … characterized by a respective angle within the recording angle range … reference recording direction lies in the plane … generating the reconstruction comprises generating the reconstruction based on the sequence of further X-ray projection images.” Huennekens teaches using multiple angiographic images (e.g., two different view planes) to reconstruct a three-dimensional vessel lumen and to co-register IVUS vessel information, see paragraphs [0033–0034].
Huennekens fails to explicitly teach:
Generating a sequence of further X-ray projection images of the hollow organ over a defined tomosynthesis recording angle range.
Using such a sequence as input to a tomosynthesis reconstruction of a volume corresponding to the reference volume.
Rubner teaches:
“wherein carrying out the tomosynthesis method comprises generating a sequence of further X-ray projection images … each X-ray projection image … represents the hollow organ according to another predefined projection direction … characterized by a respective angle within the recording angle range … reference recording direction lies in the plane … generating the reconstruction comprises generating the reconstruction based on the sequence of further X-ray projection images.” Rubner teaches obtaining a sequence of X-ray video images of a region of interest while a C-arm is moved around the subject along a motion path, with each frame representing the region from a different C-arm pose (different projection direction), selecting frames according to criteria such as resolution, motion, and region size, and supplying the selected frames and their poses to a reconstruction engine that generates a three-dimensional tomosynthesis volume, see paragraphs [0019–0022] and [0025–0031] and [0038–0045].
Huennekens and Rubner fail to explicitly teach:
That the recorded projections are defined relative to a specific reference recording direction and recording angle range selected as functions of a planar reference slice derived from pre-operative planning.
Siewerdsen teaches:
“wherein carrying out the tomosynthesis method comprises generating a sequence of further X-ray projection images … predefined projection direction … characterized by a respective angle within the recording angle range … reference recording direction lies in the plane … generating the reconstruction comprises generating the reconstruction based on the sequence of further X-ray projection images.” Siewerdsen teaches that 3D–2D registration operates between a three-dimensional image (e.g., CT or C-arm cone-beam CT) and one or more 2D radiographs, and that DRRs are computed by projecting the 3D image along specific projection directions corresponding to source–detector geometry, with the 3D–2D registration solving for the geometry parameters relating the 3D volume to the set of 2D views, see paragraphs [0023–0030] and [0035–0042] and [0058–0067].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
As per Claim 6:“The method of claim 4, wherein a maximum angle difference according to the recording angle range is less than 180°, is at most 90°, is at most 60°, or is at most 45°.”
Huennekens teaches:
“The method of claim 4 … maximum angle difference according to the recording angle range …” Huennekens teaches reconstructing a three-dimensional vessel lumen from multiple angiographic projections and co-registering IVUS data to that 3D angiographic image, but does not specify particular numerical acquisition angle ranges, see paragraphs [0033–0034].
Huennekens fails to explicitly teach:
Any explicit “maximum angle difference” or numerical bounds on a recording angle range for tomosynthesis acquisition (e.g., <180°, ≤90°, ≤60°, ≤45°).
Rubner teaches:
“wherein a maximum angle difference according to the recording angle range is less than 180°, is at most 90°, is at most 60°, or is at most 45°.” Rubner teaches that the C-arm is moved around the subject while continuous X-ray video is acquired and that images are selected along the motion path according to criteria including resolution needs, motion, and region-of-interest size, which implies using a finite angular sweep (short-scan) sufficient for CT-type reconstruction and shorter than a full 360° rotation, see paragraphs [0019–0022] and [0025–0031] and [0038–0045].
Huennekens and Rubner fail to explicitly teach:
The specific numerical upper bounds 90°, 60°, and 45° as explicit maxima.
Explicitly tying those angle limits to a vessel-slice-based reference volume derived from pre-operative planning data.
Siewerdsen teaches:
“wherein a maximum angle difference according to the recording angle range is less than 180°, is at most 90°, is at most 60°, or is at most 45°.” Siewerdsen teaches using mobile and fixed-room X-ray systems, including C-arm systems, for 3D–2D registration between 3D images and 2D radiographs and emphasizes reducing acquisition requirements and dose compared to full 3D imaging while achieving registration adequate for surgical guidance, see paragraphs [0023–0030] and [0058–0067].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
As per Claim 7:“The method of claim 1, wherein the hollow organ contains a vessel, and the at least one characteristic feature includes a line running centrally through the vessel.”
Huennekens teaches:
“The method of claim 1, wherein the hollow organ contains a vessel …” Huennekens expressly relates to imaging blood vessels and describes examples involving arteries with lumen 10, stenotic area 20, and vessel wall layers, which are hollow organs, see paragraphs [0002–0003].
“… and the at least one characteristic feature includes a line running centrally through the vessel.” Huennekens teaches generating a three-dimensional center line 385 of the vessel lumen from angiographic information using two angiography image planes and shows the lumen border 380 projected over this three-dimensional center line in a co-registered model used for guidance, see paragraphs [0048–0049].
Huennekens fails to explicitly teach:
Referring to the center line 385 specifically as an “item of planning information” in those words, although it is used for planning and guidance.
Rubner teaches:
“wherein the hollow organ contains a vessel … characteristic feature includes a line running centrally through the vessel.” Rubner teaches reconstructing a three-dimensional volumetric data set of a region of interest (e.g., anatomy visualized by C-arm CT-type imaging) from which arbitrary slice views and trajectories can be defined; such 3D volumetric data inherently support extracting a centerline along a vessel path, see paragraphs [0019–0022] and [0045–0050].
Siewerdsen teaches:
“the at least one characteristic feature includes a line running centrally through the vessel.” Siewerdsen teaches incorporating planning structures defined in 3D images, such as device trajectories and anatomical targets, into intra-operative radiographs by 3D–2D registration and transforming these structures from the 3D coordinate system into the radiograph coordinate system after registration, see paragraphs [0023–0030] and [0068–0075].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
As per Claim 8:“The method of claim 7, wherein the reference volume is determined so a center of the reference volume lies on the line running centrally through the vessel.”
Huennekens teaches:
“The method of claim 7, wherein the reference volume is determined so a center of the reference volume lies on the line running centrally through the vessel.” Huennekens teaches forming a three-dimensional lumen border 365 and a three-dimensional centerline 385 of the vessel from angiographic information and projecting IVUS-derived lumen border information over this centerline, implying that the reconstructed and co-registered vessel volume is organized around and follows the vessel centerline, see paragraphs [0048–0049].
Huennekens fails to explicitly teach:
Expressly stating that “the center of the reference volume lies on the line running centrally through the vessel” in those words.
Rubner teaches:
“wherein the reference volume is determined so a center of the reference volume lies on the line running centrally through the vessel.” Rubner’s three-dimensional volumetric data set of a region of interest supports defining a volume of interest centered along a vessel path or trajectory, which can be aligned with a vessel centerline derived from angiographic or reconstructed data, see paragraphs [0019–0022] and [0045–0050].
Siewerdsen teaches:
“wherein the reference volume is determined so a center of the reference volume lies on the line running centrally through the vessel.” Siewerdsen teaches representing planning trajectories and anatomical targets in a 3D image and solving for the geometry that aligns those trajectories with 2D radiographs; centering a reference volume on a trajectory or centerline is inherent in such planning representations, see paragraphs [0023–0030] and [0068–0075].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
Claim 9:“The method of claim 1, wherein the hollow organ contains a vessel, and the at least one characteristic feature includes a first vascular outlet on the vessel.”
Huennekens teaches:
“The method of claim 1, wherein the hollow organ contains a vessel …” Huennekens teaches creating composite images of blood vessels, explicitly illustrating a diseased artery 5 with lumen 10 and stenotic area 20 as the target of angiography and IVUS imaging and subsequent intervention, i.e., a hollow organ containing a vessel, see paragraphs [0030–0032].
“… and the at least one characteristic feature includes a first vascular outlet on the vessel.” Huennekens teaches that arteries have side branches which can be identified with imaging techniques such as IVUS and angiography and explains that these side branches are used as fiduciary points for axial, circumferential, and radial orientation of IVUS information with respect to an angiographic base image, see paragraphs [0030–0032].
Rubner teaches:
A three-dimensional CT-type reconstruction of a region of interest from C-arm video images, using a reconstruction engine that generates a volumetric data set from selected frames and associated poses, from which images representing slices of the subject’s body in any desired view can be displayed, see paragraphs [0008–0012] and [0037–0038].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
Claim 10:“The method of claim 9, wherein the at least one characteristic feature includes a second vascular outlet on the vessel, and the reference volume is determined so the reference volume respectively at least partially includes the first vascular outlet and the second vascular outlet.”
Huennekens teaches:
“The method of claim 9, wherein the at least one characteristic feature includes a second vascular outlet on the vessel …” Huennekens teaches that arteries have multiple side branches used as fiduciary points for orientation and co-registration of IVUS and angiography, implying at least two vascular outlets on the vessel that can be identified and used, see paragraph [0036–0037].
“… and the reference volume is determined so the reference volume respectively at least partially includes the first vascular outlet and the second vascular outlet.” Huennekens teaches constructing a three-dimensional reconstruction 165 of the vessel over a length of artery that includes stenosis 60, necrotic cores 80a–80c, and side branches used for alignment, which implies selecting a vessel segment (reference volume) that spans multiple outlets and lesions for planning and treatment, see paragraphs [0036–0037].
Rubner teaches:
Generating a three-dimensional volumetric set of imaging data of a region of interest from selected C-arm video images, where the region of interest may be defined to encompass multiple anatomical features, and from which slice views can be displayed, see paragraphs [0008–0012].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
Claim 11:“The method of claim 1, further comprising before carrying out the tomosynthesis method, carrying out a pre-registration of the reference representation in relation to the patient.”
Huennekens teaches:
“The method of claim 1, further comprising … carrying out a pre-registration of the reference representation in relation to the patient.” Huennekens teaches co-registration of IVUS information with a three-dimensional angiographic image of the vessel by aligning lumen area sequences and using fiduciary points and side branches, thereby registering the volumetric vessel representation (reference representation) to the patient’s angiographic imaging geometry, see paragraphs [0034–0037] and [0041–0047].
Rubner teaches:
A workflow in which a three-dimensional target fixed relative to the subject is imaged along with the subject while the C-arm moves, and the pose of the C-arm relative to the subject is determined by analyzing the target so that the position and orientation of the subject within each frame are known before reconstruction, see paragraphs [0008–0012] and [0028–0033].
Siewerdsen teaches:
A 3D–2D registration method in which a three-dimensional image (e.g., pre-operative CT) is registered to a fixed two-dimensional image by solving for image transformation and source–detector geometry parameters so that a DRR matches the fixed radiograph, thereby aligning the 3D reference image to the patient’s 2D imaging pose, see paragraphs [0013–0017] and [0068–0075].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
Claim 12:“The method of claim 11, wherein carrying out the pre-registration comprises: generating a first reference X-ray projection image of the hollow organ; and registering the reference representation in relation to the first reference X-ray projection image.”
Huennekens teaches:
“generating a first reference X-ray projection image of the hollow organ …” Huennekens teaches forming an angiographic image of the artery (vessel) as a two-dimensional X-ray image of the lumen and using that angiogram as a base image in the co-registration process, see paragraphs [0031–0033] and
“… and registering the reference representation in relation to the first reference X-ray projection image.” Huennekens teaches aligning IVUS-derived vessel information to the angiographic image by using lumen area graphs and fiduciary points and then overlaying a three-dimensional reconstruction of the vessel onto the live two-dimensional angiographic image, which constitutes registering the volumetric reference representation to the X-ray projection of the patient’s vessel, see paragraphs [0034–0037] and [0041–0047].
Siewerdsen teaches:
Generating a reconstructed two-dimensional image (DRR) from a three-dimensional image using current transformation and geometry parameters, and computing an image-similarity metric relative to a fixed X-ray projection image, updating the parameters until the DRR best matches the fixed projection, i.e., registering the 3D image to a first reference X-ray projection image, see paragraphs [0013–0017] and [0068–0075].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
Claim 13:“The method of claim 12, wherein carrying out the pre-registration further comprises: generating a second reference X-ray projection image of the hollow organ, wherein a projection direction for generating the first reference X-ray projection image and a projection direction for generating the second reference X-ray projection image are different from each other; and registering the reference representation in relation to the second reference X-ray projection image.”
Huennekens teaches:
“generating a second reference X-ray projection image of the hollow organ, wherein a projection direction for generating the first … and … second … are different from each other …” Huennekens teaches using a first two-dimensional angiographic image 150 taken in a first view plane and a second two-dimensional angiographic image 155 taken in a second, different view plane to reconstruct a three-dimensional angiographic image 160 of the vessel lumen, see paragraphs [0033–0034].
“… and registering the reference representation in relation to the second reference X-ray projection image.” Huennekens further teaches using two angiography planes 370, 375 in circumferential registration, by projecting IVUS frames against each plane and comparing them to the corresponding angiographic projections to determine angular alignment, thereby using multiple projections for registration of the volumetric vessel representation, see paragraphs [0048–0049].
Siewerdsen teaches:
A 3D–2D registration framework in which a 3D image is registered to one or more 2D radiographs by computing DRRs and maximizing similarity, and notes that the imaging system may be a C-arm or other radiographic system where multiple projections can be used to constrain the registration, see paragraphs [0013–0017] and [0029–0031] and [0068–0075].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
Claim 14:“A system for visual support in a medical intervention on a hollow organ of a patient, the system comprising: an X-ray imaging modality that is configured to generate an X-ray projection image of the hollow organ; and at least one computing unit that is configured to: obtain reference data that includes a reference representation of the hollow organ, wherein the reference data includes items of planning information relating to a location of at least one characteristic feature of the hollow organ in the reference representation; determine items of overlay information based on the reference data; generate an overlay image that corresponds to the X-ray projection image overlaid with the items of overlay information; determine a reference volume in the reference representation as a function of the items of planning information; actuate the X-ray imaging modality for carrying out a tomosynthesis method; generate a reconstruction of a volume of the patient corresponding to the reference volume based on a result of the tomosynthesis method; generate registration data; register the reference volume in relation to the reconstruction; transform the X-ray projection image or the items of overlay information in accordance with the generated registration data; and overlay the items of overlay information on the transformed X-ray projection image or overlay the transformed items of overlay information on the X-ray projection image, wherein the generation of the registration data comprises generation of 3D/3D registration data.”
Huennekens teaches:
“A system for visual support in a medical intervention on a hollow organ of a patient, the system comprising: an X-ray imaging modality that is configured to generate an X-ray projection image of the hollow organ; and at least one computing unit …” Huennekens describes an imaging system including angiographic X-ray equipment producing 2D and 3D angiograms, an imaging catheter providing IVUS data, and an image processing/display system that executes algorithms to create volumetric vessel reconstructions and composite graphical displays on a monitor, see paragraphs [0031–0033] and [0035–0037].
“obtain reference data that includes a reference representation of the hollow organ … items of planning information relating to a location of at least one characteristic feature … determine items of overlay information based on the reference data; generate an overlay image that corresponds to the X-ray projection image overlaid with the items of overlay information; determine a reference volume … register the reference volume in relation to the reconstruction; transform the X-ray projection image or the items of overlay information … overlay the items of overlay information on the transformed X-ray projection image or overlay the transformed items …” These functions are collectively taught by Huennekens’s acquisition of angiographic and IVUS data, creation of a volumetric vessel model including stenosis, necrotic cores, and side branches, co-registration of IVUS and angiography via axial and circumferential algorithms, and overlay of the reconstructed vessel volume and lesion information onto live angiographic images for guidance, see paragraphs [0030–0032] and [0034–0037] and [0041–0049].
Huennekens fails to explicitly teach:
“actuate the X-ray imaging modality for carrying out a tomosynthesis method; generate a reconstruction of a volume of the patient corresponding to the reference volume based on a result of the tomosynthesis method … wherein the generation of the registration data comprises generation of 3D/3D registration data” using C-arm tomosynthesis and explicit 3D/3D registration parameters between pre-operative and intra-operative volumes.
Rubner teaches:
“actuate the X-ray imaging modality for carrying out a tomosynthesis method; generate a reconstruction of a volume of the patient corresponding to the reference volume based on a result of the tomosynthesis method.” Rubner teaches a system in which an existing C-arm fluoroscopy unit is used to obtain a sequence of video images of a region of interest while the C-arm is moved, the C-arm pose is determined from a 3D target plate, and a reconstruction engine uses selected frames and poses to generate a three-dimensional volumetric CT-type data set of the region of interest, see paragraphs [0008–0012] and [0028–0033] and [0037–0038].
Siewerdsen teaches:
“generate registration data … wherein the generation of the registration data comprises generation of 3D/3D registration data; transform the X-ray projection image or the items of overlay information … overlay the items of overlay information on the transformed X-ray projection image or overlay the transformed items …” Siewerdsen teaches computing image transformation and source–detector geometry parameters that register a 3D image to a fixed 2D X-ray image by optimizing a similarity metric between a DRR and the fixed image, and generating a visualization image by overlaying the fixed radiograph with the reconstructed projection, with 3D planning data aligned to the radiograph, see paragraphs [0013–0017] and [0031–0033] and [0068–0075].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
Claim 17:“The method of claim 1, wherein the items of overlay information comprise a two-dimensional representation of the hollow organ or another organ of the patient obtained from the pre-operative reference representation, two-dimensional representations of the characteristic features, or the two-dimensional representation of the hollow organ or the other organ of the patient obtained from the pre-operative reference representation and the two-dimensional representations of the characteristic features.”
Huennekens teaches:
“wherein the items of overlay information comprise a two-dimensional representation of the hollow organ … obtained from the pre-operative reference representation …” Huennekens teaches generating two-dimensional angiographic images of the artery and two-dimensional graphical projections of the reconstructed three-dimensional vessel volume (e.g., vessel lumen trace and overlays) used in composite displays, see paragraphs [0031–0033] and [0036–0037] and [0055–0057].
“two-dimensional representations of the characteristic features …” Huennekens teaches two-dimensional views and overlays that show locations of stenosis 60, necrotic cores 80a–80c, plaque thickness profiles, and side branches relative to a lumen trace, which are 2D representations of characteristic vessel features derived from the volumetric model, see paragraphs [0036–0037] and [0055–0057].
Rubner teaches:
Slice and projection images derived from a 3D CT-type volume that can be displayed in arbitrary views, implying 2D representations of both the hollow organ and its internal features from the reconstructed volume, see paragraphs [0008–0012] and [0037–0038].
Siewerdsen teaches:
Representing 3D planning structures and anatomical regions in a pre-operative image and overlaying them as 2D projections on mobile radiographs after registration, i.e., generating 2D representations of characteristic features and overlying them with 2D anatomy, see paragraphs [0013–0017] and [0033–0035] and [0068–0075].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
Claim 18:“The method of claim 17, wherein the hollow organ is a vessel, wherein the items of overlay information comprise the two-dimensional representations of the characteristic features, and wherein the characteristic features include a central line through one of the vessels.”
Huennekens teaches:
“wherein the hollow organ is a vessel … the items of overlay information comprise the two-dimensional representations of the characteristic features … wherein the characteristic features include a central line through one of the vessels.” Huennekens teaches that the hollow organ is a diseased artery and that the reconstruction includes a three-dimensional lumen border 365 and a three-dimensional center line 385 of the vessel, with graphical displays that show projections of the centerline and plaque features, providing 2D representations of these characteristic features for overlay, see paragraphs [0048–0049] and [0055–0057].
Rubner teaches:
3D CT-type volumes of vascular regions from which centerline paths and projections of those paths (2D representations of a central line through a vessel) can be derived and displayed as part of the imaging information, see paragraphs [0008–0012] and [0037–0038].
Siewerdsen teaches:
Planning trajectories and structures defined in 3D (such as device paths) which, when registered to radiographs, are displayed as projected 2D lines over the anatomy for visualization and verification, providing 2D representations of central or planned lines through structures, see paragraphs [0033–0035] and [0068–0075].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
Claim 19:“The method of claim 1, wherein the x-ray projection image is two-dimensional (2D), and wherein the transforming comprises transforming the 2D X-ray projection image in accordance with the generated 3D/3D registration data.”
Huennekens teaches:
“wherein the x-ray projection image is two-dimensional (2D) …” Huennekens teaches forming angiographic images of the vessel as two-dimensional X-ray projection images and using these 2D angiograms as the base images in composite displays and co-registration, see paragraphs [0031–0033].
“… and wherein the transforming comprises transforming the 2D X-ray projection image in accordance with the generated 3D/3D registration data.” Huennekens teaches aligning and co-registering IVUS information and angiographic images via axial and circumferential registration algorithms and then displaying the reconstructed vessel over a live 2D angiographic image, but the registration is described in terms of aligning 1D/2D/3D vessel information rather than explicitly as 3D/3D registration that yields a transform applied directly to the 2D projection image, see paragraphs [0041–0047] and [0048–0049].
Huennekens thus implies using registration results to adjust the relationship between reconstructed 3D vessel data and the 2D angiogram but does not explicitly frame this as transforming the 2D X-ray projection image itself in accordance with 3D/3D registration data between volumes.
Rubner teaches:
A tomosynthesis/CT-type reconstruction pipeline in which a 3D volumetric data set of the region of interest is generated from selected C-arm video images and their poses, producing 3D imaging data that can be used alongside other 3D data sets (e.g., pre-operative images) for further processing and comparison, see paragraphs [0008–0012] and [0037–0038].
Siewerdsen teaches:
A 3D–2D registration method that solves for both image-transformation and source–detector geometry parameters so that a reconstructed 2D projection (DRR) from a 3D image best matches a fixed 2D X-ray image, and then generates a visualization image by overlaying the fixed 2D image and the reconstructed DRR; this framework inherently uses 3D registration results to define how the 2D X-ray projection is related to the 3D data and can be viewed as transforming the 2D image geometry according to the computed 3D/3D/3D–2D parameters, see paragraphs [0013–0017] and [0031–0033] and [0068–0075].
The obviousness of combining the teachings of Huennekens, Rubner, Siewerdsen and Yan are discussed in the rejection of claim 1, and incorporated herein.
Response to Arguments
Applicant's arguments, filed on July 22, 2026 with respect to argument (1) in the remarks, have been considered but are moot in view of the new ground(s) of rejection necessitated by the new limitations added to Claims 1 and 14.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
WO 2006119426 A2: A device and methods for performing a simulated CT biopsy on a region of interest on a patient. The device comprises a gantry (22) configured to mount an x-ray emitter (24) and CT detector (26) on opposing sides of the gantry, a motor (28) rotatably coupled to the gantry such that the gantry rotates horizontally about the region of interest, and a high-resolution x-ray detector (172) positioned adjacent the CT detector in between the CT detector and the x-ray emitter.
US 20110080990 A1: A medical system includes a treatment radiation source configured to deliver treatment radiation during a treatment session, an imaging system configured to obtain image data during the treatment session, and a processor configured to determine a beam break, and automatically operate the imaging system to obtain the image data during the beam break. A medical system includes a treatment radiation source, an imaging system configured to automatically obtain image data in a beam break that occurs during a treatment session, and a processor configured to automatically operate the treatment radiation source to deliver treatment radiation during the treatment session after the beam break ends.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/E.B.W/ Examiner, Art Unit 3683
/ROBERT W MORGAN/ Supervisory Patent Examiner, Art Unit 3683
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