Detailed Action
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Objection to the claims and rejection made under 35 U.S.C. 101 are withdrawn.
Applicant’s arguments with respect to claims 1-5, 7-13, and 15 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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On pages 11-17, Applicant argues,
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Examiner agrees that amended claim 1, as drafted, overcomes the previous 35 U.S.C. 101 rejection. The claim recites a particular medical imaging modality which is used to acquire data for a technological process. Namely, generating a single image visualization of coronary artery geometry and association perfusion and flow impediment measurements from a single spectral CT acquisition. Thus, these recited limitations reflect a practical application by way of a technical improvement of reducing the need for cross-modality/time-series alignment and therefore amount to significantly more than the judicial exception.
Drawings
Examiner acknowledges the corrections made to Figs. 3A and 7. However, the drawings remain objected to as failing to comply with 37 CFR 1.84(p)(4) because:
reference character “345” is still being used to designate both a flow deviation and reformatted data (see 345 of Figs. 2A and 3A and paragraphs 0036 and 0044).
Additionally, while the reference characters have been updated, the drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description:
reference character “355” of Fig. 3A. Note that the instances of “flow deviation 345” in paragraph 0036 should read “flow deviation 355”.
reference character “357” of Fig. 3A. Note that the instances of “reference value 347” in paragraph 0036 should read “reference value 357”.
reference characters “707”, “709”, and “710” of Fig. 7. Note that the instances of “713”, “715”, and “717” which correspond to the steps of fig. 7 in paragraphs 0054-0055 should read “707”, “709”, and “710”, respectively.
Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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 1-2, 4-5, 9-10, and 12-15 are rejected under 35 U.S.C. 103 as being unpatentable over Freiman et al. (EP 3378398 A1), (hereinafter Freiman) in view of Ishii et al. (US 20150262388 A1), (hereinafter, Ishii).
Regarding claim 1, Freiman teaches a computer-implemented method for visualization, comprising:
Obtaining first data of a first perfusion measure of myocardial tissues of a patient; obtaining second data of a geometry of a coronary artery of the patient (Freiman, “In a first aspect, embodiments of the present invention relate to an image processing device that comprises a data input for receiving spectral computed tomography volumetric image data organized in voxels. This volumetric image data comprises a contrast-enhanced volumetric image of a cardiac region in a subject’s body and a baseline volumetric image of that cardiac region. The contrast-enhanced volumetric image conveys anatomical information regarding coronary artery anatomy of the subject… The image processing device furthermore comprises a perfusion synthesis unit for generating at least one perfusion image, e.g. at least one virtual perfusion image, representative of a blood distribution in tissue, at least one instant in time, taking at least the baseline volumetric image and the coronary flow simulation into account.”, pg. 6, paragraph 0050, “The image processing device 10 also comprises a flow simulator 12 for generating or receiving, as input, a three-dimensional coronary tree model based on the volumetric image data and for simulating a coronary flow, e.g. generating a coronary flow simulation, based on the three-dimensional coronary tree model, e.g. by taking the contrast enhanced volumetric image into account, e.g. based on the contrast-enhanced volumetric image.”, pg. 7, paragraph 0062, ”The device may also comprise a perfusion map generator for computing quantitative perfusion maps from a sequence, e.g. a time series, of perfusion images generated by the perfusion synthesis unit 13. Such perfusion map generator may apply a method for calculating a quantitative perfusion map based on conventional dynamic cardiac perfusion CT images as known in the art, e.g. a prior-art method for processing physically acquired dynamic cardiac perfusion CT images.”, pg. 9, paragraph 0084, lines 1-5, A spectral CT volume is processed to obtain a coronary artery model, of which quantitative perfusion maps for myocardial tissue can be obtained based on simulated coronary flow. These maps represent an inferred perfusion measurement obtained for myocardial tissue in each scanned patient.);
obtaining third data of a second perfusion measure of the coronary artery; (Freiman, “The flow simulator 12 may be adapted for simulating the coronary flow by taking a boundary condition model into account. This boundary condition model may model an interface between the three-dimensional coronary tree model and non-imaged vasculature.”, pg. 7, paragraph 0065, Note perfusion measure of the coronary artery is being interpreted as corresponding to a measure of blood flow through the artery.)
wherein the first data, the second data, and the third data are all derived from a single spectral coronary computed tomography angiography (CCTA) acquisition (Freiman, “The spectral CT volumetric image data may for example comprise, or consist of, computed tomography cardiac angiography data, e.g. in accordance with a standard spectral CT acquisition protocol as known in the art for cardiac angiography.”, pg. 7, paragraph 0057, “In accordance with embodiments of the present invention, the data input 11 may be adapted for receiving the volumetric image data comprising the baseline volumetric image in the form of a virtual non-contrast-enhanced volumetric image of the cardiac region. Thus, the contrast-enhanced volumetric image and the virtual non-contrast-enhanced volumetric image may be based on a same spectral cardiac CT dataset obtained in a single spectral CT volumetric acquisition.”, pg. 7, paragraph 0060); and
visualizing, on a single image, the first perfusion measure of the myocardial tissues (Freiman, “The perfusion synthesis unit 13 may be adapted for synthesizing the perfusion image by iteratively minimizing a combination…”, pg. 9, paragraph 0081, lines 1-2).
Freiman does not teach obtaining fourth data of a flow impediment measure along the coronary artery based on the third data of the second perfusion measure of the coronary artery; visualizing, on a single image, the first perfusion measure of the myocardial tissues and the coronary artery, the coronary artery being overlaid with the first perfusion measure on the single image, the visualized coronary artery representing the geometry of the coronary artery and the flow impediment measure along the coronary artery.
However, Ishii teaches obtaining fourth data of a flow impediment measure along the coronary artery based on the third data of the second perfusion measure of the coronary artery; visualizing, on a single image, the first perfusion measure of the myocardial tissues and the coronary artery, the coronary artery being overlaid with the first perfusion measure on the single image, the visualized coronary artery representing the geometry of the coronary artery and the flow impediment measure along the coronary artery (Ishii, “A color scale bar regarding the FFR value is displayed in accordance with an LUT used for conversion from an FFR distribution map into a color map, and represents the magnitude of the FFR value by color. A color scale bar regarding the blood flow rate is applied to the color display of myocardial perfusion image, and represents the blood flow rate by color.”, pg. 5, paragraph 0069, 13-19, see Fig. 5, “In the local display mode, only an area of users interest (angiostenosis position, blood vessel branch position, and range of a blood vessel having a predetermined width or more) is displayed in a color corresponding to the magnitude of the FFR value. To the contrary, an area of no interest excluding the area of interest is not displayed in color, and a morphological image is displayed directly. Hence, the user can interpret a temporal change of the FFR result regarding the area of interest of the coronary artery.”, pg. 3, paragraph 0032, lines 1-14, A color map is determined corresponding to FFR values of the blood flow along the coronary artery. Fig. 5 shows a visualization of this color map being overlayed on a perfusion image. This color map can be further adjusted, based on user input, to visualize stenosis positions (e.g., flow impediment regions along the coronary artery) by considering vessel width and the corresponding FFR values, for the entirety of the artery. This localization of stenosis positions serves as a measurement of regions where blood flow is functionally impaired, allowing users to interpret these regions of the artery more accurately.).
Freiman teaches processing a single spectral CT acquisition to obtain a coronary artery model and to estimate coronary blood flow (i.e., perfusion of the coronary artery) for generating perfusion images representing perfusion in myocardial tissue (Freiman, pg. 6, paragraph 0050, pg. 7, paragraph 0062-0065). Freiman does not teach obtaining flow impediment measurements based on the measured coronary blood flow or jointly visualizing myocardial perfusion measurement with coronary artery flow measurements. Ishii teaches measuring coronary blood flow, including measurements indicative of flow impediment or stenosis, and visualizing these measurements by overlaying color mapped coronary artery flow data on perfusion images (see above). Ishii further teaches allowing users to adjust the color mapped coronary artery to identify regions of reduced blood flow or stenosis (Ishii, pg. 3, paragraph 0032, lines 1-14). Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Freiman to include the user-directed joint visualization of myocardial perfusion measurements and coronary artery flow impediment measurements as taught by Ishii. The motivation for doing so would have been to improve diagnostic interpretation by allowing the user to evaluate myocardial perfusion with respect to coronary blood flow (as suggested by Ishii, “The user can interpret a temporal change of the FFR value of the coronary artery and a state change of the cardiac muscle together. This can improve the image interpretation efficiency and diagnosis accuracy by the user.”, pg. 5, paragraph 0069, lines 22-26). Further, one skilled in the art could have combined the elements as described above by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine the teachings of Freiman with Ishii to obtain the invention as specified in claim 1.
Regarding claim 2, Freiman in view of Ishii teaches the method of claim 1, wherein the obtaining of the data of the flow impediment measure along the coronary artery includes:
determining a flow deviation of the second perfusion measure from a reference value along the coronary artery (Ishii, “The angiostenosis position can be specified according to, for example, the change amount of the inside diameter value of an extracted blood vessel area. This is because the inside diameter value of a blood vessel does not greatly vary in a range other than a branch position and the end of a blood vessel in a coronary artery, and a range having a large change amount of the inside diameter value is highly likely to be a stenosis range.”, pg. 3, paragraph 0032, lines 13-20, A diameter of the coronary artery is analyzed to identify regions of narrowing (e.g. stenosis) by detecting deviations from expected or normal vessel widths. These deviations indicate where blood flow may be impaired (e.g., stenosis positions) along the coronary artery, allowing users to adjust the viewable range of the color map for user interpretation.) and
processing a stenosis assessment along the coronary artery based on the determined flow deviation to obtain the data of the flow impediment measure (Ishii, “For example, when the display range setting circuitry 18 sets a color display range based on the FFR value, the user can set an FFR value range by inputting at least one of the upper and lower limit values of an FFR value to be displayed. For example, the user sets an FFR value of 0.8 or less, and can set a color display range where it can be estimated that angiostenosis is severe.”, pgs. 2 and 3, paragraph 0030, lines 4-10, “The display range setting circuitry 18 sets, as the color display range, a range obtained by adding a predetermined margin in each of four directions from the angiostenosis position (step S38).”, pg. 4, paragraph 0064, lines 5-8, Once the stenosis positions are identified, a “stenosis range” can be set for the color map to visualize these localized regions. To generate this display, a margin is applied around each identified stenosis position. This range-setting process serves as an initial stenosis assessment step to delineate stenosis regions that can be jointly displayed with myocardial perfusion.).
Regarding claim 4, Freiman in view of Ishii teaches the method of claim 1, wherein the visualizing includes simultaneously visualizing on the single image the first perfusion measure of the myocardial tissues and the coronary artery that represents the geometry of the coronary artery and that represents the flow impediment measure along the coronary artery (Ishii, “In steps S17, S27, and S44, the display 20 may display Superposed images obtained by position matching and phase matching of a plurality of morphological images and a plurality of color maps with respect to a plurality of myocardial perfusion images. Similarly, in steps S17, S27. and S44, the display 20 may display Superposed images obtained by position matching and phase matching of a plurality of morphological images and a plurality of color maps with respect to a plurality of polar maps.”, pg. 5, paragraph 0068, lines 1-9, see Figs. 5 and 6, For visualization, the geometry of the coronary artery is superimposed onto a myocardial perfusion image, as shown in Fig. 5. This superposition includes coronary blood flow color map, allowing specific stenosis positions to be jointly displayed with myocardial perfusion.).
Regarding claim 5, Freiman in view of Ishii teaches the method of claim 1, wherein the visualizing includes visualizing the first perfusion measure and the flow impediment measure by at least one of color, thickness, or size (Ishii, see Fig. 5, The joint myocardial perfusion image superimposed with the coronary artery model can be visualized in Fig. 5. In order to construct this visualization, color (e.g., color maps), thickness (e.g., artery diameter), and size (e.g., artery model and set display range) must be taken into consideration.).
Claim 9 corresponds to claim 1, additionally reciting a visualization system comprising a memory that stores a plurality of instructions and processor circuitry that couples to the memory to perform the method according to claim 1. Freiman in view of Ishii teaches the addition of a visualization system comprising a memory that stores a plurality of instructions and processor circuitry that couples to the memory (Freiman, “The image processing device 10 comprises a data input 11 for receiving spectral computed tomography (CT) volumetric image data organized in voxels. Particularly, the data input may comprise a digital communication circuit, such as a computer network interface, a wireless transmission interface or a digital data bus interface, for receiving the data from an external source, such as a spectral CT scanner or a reconstructor for reconstructing CT images provided by a spectral CT scanner. The data input may comprise a virtual interface for receiving the data from another software component implemented on a shared hardware platform, e.g. from another software component executing on the same computer, such as a software component for reconstructing spectral CT image data.”, pg. 6, paragraph 0053, lines 1-7). As indicated in the analysis of claim 1, Freiman in view of Ishii teaches all the limitation according to claim 1. Therefore, claim 9 is rejected for the same reason as claim 1.
Claim 10 corresponds to claim 2, additionally reciting a visualization system comprising a memory that stores a plurality of instructions and processor circuitry that couples to the memory to perform the method according to claim 2. Freiman in view of Ishii teaches the addition of a visualization system comprising a memory that stores a plurality of instructions and processor circuitry that couples to the memory (see analysis of claim 9). As indicated in the analysis of claim 2, Freiman in view of Ishii teaches all the limitation according to claim 2. Therefore, claim 10 is rejected for the same reason as claim 2.
Claim 12 corresponds to claim 4, additionally reciting a visualization system comprising a memory that stores a plurality of instructions and processor circuitry that couples to the memory to perform the method according to claim 4. Freiman in view of Ishii teaches the addition of a visualization system comprising a memory that stores a plurality of instructions and processor circuitry that couples to the memory (see analysis of claim 9). As indicated in the analysis of claim 4, Freiman in view of Ishii teaches all the limitation according to claim 4. Therefore, claim 12 is rejected for the same reason as claim 4.
Claim 13 corresponds to claim 5, additionally reciting a visualization system comprising a memory that stores a plurality of instructions and processor circuitry that couples to the memory to perform the method according to claim 5. Freiman in view of Ishii teaches the addition of a visualization system comprising a memory that stores a plurality of instructions and processor circuitry that couples to the memory (see analysis of claim 9). As indicated in the analysis of claim 5, Freiman in view of Ishii teaches all the limitation according to claim 5. Therefore, claim 13 is rejected for the same reason as claim 5.
Claim 14 corresponds to claim 6, additionally reciting a visualization system comprising a memory that stores a plurality of instructions and processor circuitry that couples to the memory to perform the method according to claim 6. Freiman in view of Ishii teaches the addition of a visualization system comprising a memory that stores a plurality of instructions and processor circuitry that couples to the memory (see analysis of claim 9). As indicated in the analysis of claim 6, Freiman in view of Ishii teaches all the limitation according to claim 6. Therefore, claim 14 is rejected for the same reason as claim 6.
Claim 15 corresponds to claim 1, additionally reciting a non-transitory computer-readable medium to perform the method according to claim 1. Freiman in view of Ishii teaches the addition of a non-transitory computer-readable medium (Freiman, “The computing system may comprise a computer readable storage medium 126, e.g. a non-transitory memory such as a physical digital memory”, pg. 10, paragraph 0093, lines 7-8). As indicated in the analysis of claim 1, Freiman in view of Ishii teaches all the limitation according to claim 1. Therefore, claim 15 is rejected for the same reason as claim 1.
Claims 7-8 is rejected under 35 U.S.C. 103 as being unpatentable over Freiman et al. (EP 3378398 A1) in view of Ishii et al. (US 20150262388 A1) and further in view of Breeuwer et al. (US 8537159 B2), (hereinafter, Breeuwer).
Regarding claim 7, Freiman in view of Ishii teaches the method of claim 1, further comprising:
segmenting image data of the patient in accordance with a segment model of the coronary artery to provide segmented data of the coronary artery, wherein the obtaining of the data of the geometry of the coronary artery of the patient and the obtaining of the data the flow impediment measure along the coronary artery are based on the segmented data of the coronary artery (Freiman, “The flow simulator 12 may comprise a coronary tree segmentation unit 14 for generating the three-dimensional coronary tree model based on the volumetric image data, e.g. by taking the contrast-enhanced volumetric image into account, e.g. based on the contrast-enhanced volumetric image. The segmentation unit may for example be adapted for coronary lumen segmentation, for extracting a vessel centerline and/or building a tree model from such branching centerline structures.”, pg. 7, paragraph 0064, The coronary artery is segmented from the spectral CT data. This segmentation provides the spatial information for the diameter measurement and localization of stenosis regions.);
reformatting the data of the first perfusion measure of the myocardial tissues, the data of the geometry of the coronary artery, and the data of the flow impediment measure along the coronary artery, to fit a reference shape (Ishii, “As shown in FIG. 6, a Superposed image obtained by Superposing a morphological image and a color map on a polar map is displayed. A color scale bar regarding the FFR value is displayed in accordance with an LUT used for conversion from an FFR distribution map into a color map, and represents the magnitude of the FFR value by color.”, pg. 5, paragraph 0070, lines 7-13, see Fig. 6, The superposition process can be applied to polar maps, which requires reformatting of the myocardial perfusion images and extracted coronary artery to align with the polar map layout.).
Freiman in view of Ishii does not teach segmenting image data of the patient in accordance with a segment model of a myocardium wall to provide segmented data of the myocardium wall, wherein the obtaining of the data of the first perfusion measure of the myocardial tissues is based on the segmented data of the myocardium wall and wherein the reference shape is defined by at least an inner reference surface and an outer reference surface.
However, Breeuwer teaches segmenting image data of the patient in accordance with a segment model of a myocardium wall to provide segmented data of the myocardium wall, wherein the obtaining of the data of the first perfusion measure of the myocardial tissues is based on the segmented data of the myocardium wall and wherein the reference shape is defined by at least an inner reference surface and an outer reference surface (Breeuwer, “The voxel data is segmented in accordance with a segment model. The segmentation may be performed automatically, semi-automatically or even manually. The segmentation may manually be done by identifying the voxels of interest. For example, to identify the voxels that constitutes the myocardium of the left ventricle. The segmented voxel data is fitted to a reference shape. In connection with the left ventricle, a truncated ellipsoid may be applied. FIG. 2 illustrates an example of a reference shape in the form of a truncated ellipsoid 20. In the reformation of the segmented voxel data, the true anatomical location of the myocardium data is fitted to match the reference shape. The segmentation results in the positioning the inner and outer reference surfaces The reference shape includes the long axis 21 of the left ventricle, the inner wall or endocardium 22 and the outer wall or epicardium 23. Each cross-section, as defined by a contour 24 of the reference shape, represents a reformatted or fitted MRI slice onto the reference shape. The segmentation and reformatting of the voxel data onto a reference shape is known in the art.”, columns 6 and 7, lines 58-67 and 1-11, respectively, “Finally, the target shape of the property value is visualized, typically on a computer screen of a user. FIG. 3 shows an example of a visualized target shape 30, where visualization of the target shape is obtained by a volume rendering of the target shape. The target shape is hereafter also referred to as the volumetric bull's eye plot (VBEP).”, column 7, lines 48-53, See Fig. 2, The myocardial walls are segmented and reformatted to a bull’s eye plot which is defined by an inner and outer surface).
Freiman in view of Ishii teaches superposing myocardial perfusion images with extracted coronary arteries containing color maps, to localize stenosis positions (Ishii, “For example, the user sets an FFR value of 0.8 or less, and can set a color display range where it can be estimated that angiostenosis is severe.”, pg. 3, paragraph 0030, lines 8-10, see Fig. 5). Freiman in view of Ishii further teaches that this superposition process may be applied to a polar map (Ishii, “As shown in FIG. 6, a Superposed image obtained by Superposing a morphological image and a color map on a polar map is displayed..”, pg. 5, paragraph 0070, lines 7-10, see Fig. 6, Note that the term polar map is synonymous with bull’s eye plot1), but does not specify how the myocardial perfusion images are reformatted for display in the polar map format. Breeuwer teaches segmenting myocardial voxels and reformatting the data to fit a reference shape defined by myocardial wall surfaces (see above). The reformatted data is then mapped to a target shape, such as a bull’s eye plot, for visualization (Breeuwer, column 7, lines 12-36). Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Freiman in view of Ishii by including the myocardial segmentation and reformatting technique, as taught by Breeuwer (Breeuwer, columns 6 and 7, lines 58-67 and 1-11, respectively, See Fig. 2). The motivation for doing so would have been to map localized reference structures onto a target shape, thereby improving the correlation to the anatomy and the diagnostics capabilities of the polar map (as suggested by Breeuwer, “By mapping reference structures onto the target shape, an improved correlation to the anatomy may be provided, and moreover, structures which are related to a property value under investigation can directly be corrected to the distribution geometry of the property value. The presence of localized reference structures renders the target shape patient specific, which may be important in connection with the diagnosis.”, column 3, lines 34-41). The combination of Freiman in view of Ishii and further in view of Breeuwer would generate segmented myocardial perfusion images based on myocardial wall boundaries and map them into polar map form. The superposition process would be applied to include the adjustable color maps of the coronary artery geometry in the mapping. Further, one skilled in the art could have combined the elements as described above by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine the teachings of Freiman in view of Ishii with Breeuwer to obtain the invention as specified in claim 7.
Regarding claim 8, Freiman in view of Ishii in view of Breeuwer teaches the method of claim 7, further comprising:
mapping, to a target shape, the reformatted data of the myocardial tissues, the reformatted data of the geometry of the coronary artery, and the reformatted data of the flow impediment measure along the coronary artery, wherein the target shape is defined by at least a first target surface and a second target surface, wherein the mapping includes mapping from the inner reference surface to the first target surface and from the outer reference surface to the second target surface (Breeuwer, “In accordance with embodiments of the present invention, the reformatted voxel data is mapped to a target shape by a mapping of the property value from the inner reference surface to the first target surface, and from the outer reference surface to the second target surface. Here the classified LE data, i.e. a property value indicative of intensity of the contrast agent, is mapped from the set ofvoxel values to a target shape in the form of a cylinder.”, column 7, lines 12-19, The mapping to the reference shape is based an inner and outer surface to respective target surfaces.); and
based on the mapping, visualizing, on the single image, the first perfusion measure of the myocardial tissues and the coronary artery that represents the geometry of the coronary artery and that represents the flow impediment measure along the coronary artery (Ishii, “Further, the input circuitry 16 accepts display/non display user instructions regarding a myocardial perfusion image and polar map to the display 20”, pg. 3, paragraph 0031, lines 1-3, As indicated in the analysis of claim 7, the combination of Freiman in view of Ishii and further in view of Breeuwer would map each element, the myocardial perfusion image, the coronary artery and the corresponding color map, into a polar map format to form a final visualization.).
Allowable Subject Matter
Claims 3 and 11 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CONNOR LEVI HANSEN whose telephone number is (703)756-5533. The examiner can normally be reached Monday-Friday 9:00-5:00 (ET).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sumati Lefkowitz can be reached at (571) 272-3638. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CONNOR L HANSEN/Examiner, Art Unit 2672
/SUMATI LEFKOWITZ/Supervisory Patent Examiner, Art Unit 2672
“Magnetism.” Questions and Answers in MRI, mri-q.com/polar-plots.html#:~:text=How%20do%20you%20interpret%20those,denoted%20anterior%20and%20inferior%20respectively. Accessed 31 July 2025.
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