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 .
Status of Claims
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
Claims 1, 3, 4, 6, 7, 11, 14, and 17 have been amended.
Claims 1-20 are pending.
Claim Objections
Claim 1 is objected to because of the following informalities:
Claim 1 recites “receive an indication of a distal end of the catheter in the second MRI image data set; and update a relative position of a distal end of the catheter and the target in the 3D model.” Based on the prior use of “a distal end,” claim 1 should read “update a relative position of [[a]] the distal end of the catheter.”
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite or similarly recite:
[a] generating an MRI image data set;
[b] generating a three-dimensional (3D) model from the MRI image data set;
[c] generating a pathway through the 3D model to a target;
[d] determining a location of a sensor [or distal portion of a catheter] within the patient [or 3D model];
[e] updating a displayed location of the portion of the catheter;
[f] generate a second MRI image data set;
[i] updating a relative position of a distal end of the catheter and the target in the 3D model.
Claim limitation [a] and [f], as drafted and under their broadest reasonable interpretation, recite a mathematical concept. (MPEP 2106.04(a)(2)(I) (see, e.g., Digitech Image Techs., LLC v. Electronics for Imaging, Inc., 758 F.3d 1344, 1350, 111 USPQ2d 1717, 1721 (Fed. Cir. 2014) (although the claims did not recite a particular mathematical formula, the court held “[w]ithout additional limitations, a process that employs mathematical algorithms to manipulate existing information to generate additional information is not patent eligible.”)). For example, generating MRI images involves acquiring k-space and reconstructing images by applying an inverse Fourier transform and linear systems. (see also, e.g., Burnett v. Panasonic Corp., 741 Fed. Appx. 777, 780 (Fed. Cir. 2018) (non-precedential) (claims reciting a formula to convert geospatial coordinates into natural numbers are patent ineligible).
Claim limitation [b], as drafted and under its broadest reasonable interpretation, recites a mathematical concept. (MPEP 2106.04(a)(2)(I) (see, e.g., Digitech Image Techs., LLC v. Electronics for Imaging, Inc., 758 F.3d 1344, 1350, 111 USPQ2d 1717, 1721 (Fed. Cir. 2014) (although the claims did not recite a particular mathematical formula, the court held “[w]ithout additional limitations, a process that employs mathematical algorithms to manipulate existing information to generate additional information is not patent eligible.”)). For example, generating a 3D model involves segmenting a volume and extracting isosurfaces using various formulas and often smoothing/registration.
Claim limitation [c], as drafted and under its broadest reasonable interpretation, recites a mathematical concept. (MPEP 2106.04(a)(2)(I) (see, e.g., Digitech Image Techs., LLC v. Electronics for Imaging, Inc., 758 F.3d 1344, 1350, 111 USPQ2d 1717, 1721 (Fed. Cir. 2014) (although the claims did not recite a particular mathematical formula, the court held “[w]ithout additional limitations, a process that employs mathematical algorithms to manipulate existing information to generate additional information is not patent eligible.”)). For example, generating a pathway requires building centerlines and calculating shortest-path searches that avoid collisions.
Claim limitations [d], [e], and [i], as drafted and under their broadest reasonable interpretation, recite a mathematical concept. (MPEP 2106.04(a)(2)(I) (see, e.g., Digitech Image Techs., LLC v. Electronics for Imaging, Inc., 758 F.3d 1344, 1350, 111 USPQ2d 1717, 1721 (Fed. Cir. 2014) (although the claims did not recite a particular mathematical formula, the court held “[w]ithout additional limitations, a process that employs mathematical algorithms to manipulate existing information to generate additional information is not patent eligible.”)). For example, determining a location of an object within a space (and then updating that location) involves estimating poses of the object in six degrees of freedom (DOF) using tracking data, which involves various complex formulas, and then mapping the poses to the space with a rigid transform.
The next question is to consider whether the claims integrate the judicial exception into a practical application. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception. (MPEP 2106.04(d)). In this case, some additional elements/steps to consider include (1) a catheter configured for navigation within the luminal network; (2) a sensor for tracking the catheter; (3) a computing device including a processor and computer readable memory with instructions; (4) receiving magnetic resonance signals from a magnetic resonance image (MRI) scanner; (5) causing display of a location of a portion of a catheter in the 3D model based on the determined position of the sensor; and (6) receiving second magnetic resonance signals; (7) receiving signals from a sensor incorporated in the catheter; (8) receiving an indication of a distal end of the catheter in the second MRI image data set.
Here, the judicial exception is not integrated into a practical application. The catheter limitation (1) does no more than generally link the judicial exception to a particular technological environment (i.e., surgical navigation). (MPEP 2106.04(d)(I), which also refers to MPEP 2106.05(h)). Claims limitations (2), (7), and (8) to the sensor and receiving sensor signals are merely reciting words equivalent to “apply it” with the judicial exceptions. (MPEP 2106.04(d)(I), which also refers to MPEP 2106.05(f)). Claim limitation (3) recite a processor and a memory that merely include instructions to implement the abstract idea on a computer and/or merely use a computer as a tool to perform an abstract idea. (MPEP 2106.04(d)(I), which also refers to MPEP 2106.05(f)). The claim limitations (4), (6), (7), (8) to receiving signals/data recite insignificant extra-solution activity (i.e., pre-solution activity) that does not impose meaningfully limits on the claim. (MPEP 2106.04(d)(I), which also refers to MPEP 2106.05(g)). The claim limitation (5) to displaying information (e.g., graphical representation over image) recite insignificant extra-solution activity (i.e., post-solution activity) that does not impose meaningfully limits on the claim. (MPEP 2106.04(d)(I), which also refers to MPEP 2106.05(g)).
The claims do not include additional elements/steps that are sufficient to amount to significantly more than the judicial exception. A shared quality of the additional elements and/or steps is that they do not recite any meaningful limitation that transforms the judicial exception into a patent-eligible application. (MPEP 2106.05(II)). As explained above, claim limitation (1) only generally links the judicial exception to a particular technological environment; claim limitations (2), (7), and (8) merely recite words equivalent to “apply it”; claim limitation (3) recites generic elements for computing; and claim limitations (4), (6), (7), (8) recite insignificant extra-solution activity. Moreover, many of the claim limitations are well-understood, routine, conventional activities/elements that are previously known to the industry and specified at a high level of generality such that they do not meaningfully limit the claims. (MPEP 2106.05(A)). (see, e.g., Section 103 rejections below).
Accordingly, claims 1, 11, and 17 do not include patent-eligible subject matter.
Dependent claims 2-10, 12-16, and 18-20 also fail to recite patent-eligible subject matter.
Claims 2 and 11 recite displaying an updated relative position of an object. These are similar to claim limitations [d], [e], and [i] discussed above and recite a mathematical concept. (MPEP 2106.04(a)(2)(I).
Claims 3 and 13 recite receiving signals to generate another image. These are similar to claim limitations [a] and [f] and recites a mathematical concept. (MPEP 2106.04(a)(2)(I) and similar to additional elements (4), (6), (7), (8) (i.e., receive data) that recites insignificant pre-solution activity. (MPEP 2106.04(d)(I), which also refers to MPEP 2106.05(g)).
Claim 4 recites determining whether more targets exist in the 3D model. The claim limitation is merely determining whether another target exists in order to repeat the recited operations of the processor. This merely recites insignificant extra-solution activity, which could be considered post-solution or pre-solution. (MPEP 2106.04(d)(I), which also refers to MPEP 2106.05(g)). In any case, it does not recite any meaningful limitation that transforms the judicial exception into a patent-eligible application.
Claim 5 recites displaying a 3D model and a pathway to a second target. This is similar to the additional element (5). Displaying information (e.g., graphical representation over image) is an insignificant extra-solution activity (i.e., post-solution activity) that does not impose meaningfully limits on the claim. (MPEP 2106.04(d)(I), which also refers to MPEP 2106.05(g)).
Claim 6 recites a magnetic resonance scanner generating the magnetic resonance signals. However, this does no more than generally link the judicial exception to a particular technological environment (i.e., surgical navigation). (MPEP 2106.04(d)(I), which also refers to MPEP 2106.05(h)).
Claims 7 and 14 recite that the sensor is an EM sensor and that an EM field is generated and (in claim 14) determining a location of the sensor. These limitations do no more than generally link the judicial exception to a particular technological environment (i.e., surgical navigation). (MPEP 2106.04(d)(I), which also refers to MPEP 2106.05(h)).
Claims 8, 9, 15, and 16 recite limitations that specify what is generating the EM field (e.g., mat or MRI scanner). However, these are standard elements often used to generate EM fields for tracking and do not impose a meaningful limitation on the judicial exception. They also recite well-understood, routine, and conventional activities/elements. (MPEP 2106.05(A)). (see discussion of COVIDIEN and ROTH in Section 103 rejection of claims 8, 9, 15, and 16 below).
Claims 10 and 18 recite that the sensor is an inertial measurement unit. Again, this is a standard element used for tracking that does not impose a meaningful limitation on the judicial exception. (MPEP 2106.04(d)). They also recite well-understood, routine, conventional activities/elements that are previously known to the industry and specified at a high level of generality such that they do not meaningfully limit the claims. (MPEP 2106.05(A)). (see discussion of KREUCKER in Section 103 rejection of claims 10 and 18 below).
Claim 19 recites that the updated displayed position of the distal portion of the catheter is employed to eliminate drift of the IMU. This recitation relates to the intended purpose of an action and does not impose a meaningful limitation on the judicial exception. (MPEP 2106.04(d)).
Claim 20 repeats many of the steps/operations discussed above but are “focused to the area proximate the sensor.” This recitation is a well-understood, routine, conventional activity that is previously known to the industry such that it does not meaningfully limit the claim. (MPEP 2106.05(A)). (see, e.g., discussion of GUTTMAN in Section 103 rejections below).
Accordingly, none of the claims recite patent-eligible subject matter.
RESPONSE TO APPLICANT’S ARGUMENTS:
Applicant argues on pages 6 and 7 of the Response dated 1/23/2026 that Examiner failed to consider the claim “as a whole.” In particular, Applicant argues that navigating a catheter using MRI data and updating the displayed location is a practical application. Applicant also argues that multiple references to the catheter support the notion that the catheter more than generally links the judicial exception to a technological environment.
Examiner disagrees. The claims essentially recite multiple steps of collecting data, analyzing data, and generating a display based on the data analysis. These claims are often held to be abstract ideas, especially when the claim limitations are recited at a high level of generality. (see, e.g., Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016) and AI Visualize, Inc. v. Nuance Communications, Inc., 97 F. 4th 1371 (2024), which stated: “We have explained that the steps of obtaining, manipulating, and displaying data, particularly when claimed at a high level of generality, are abstract concepts.”). The catheter is the one physical object that links this navigation to surgical navigation. However, the catheter and the process that is carried out by the computing device are recited at a high level of generality.
Applicant also argues that a further practical application results from using non-ionizing MR signals throughout the process. Examiner disagrees. “A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception.” (MPEP 2106.04(d)). As explained above, the various claim limitations do not meaningfully limit the judicial exception. The catheter only generally links the judicial exception to a particular technological environment. The other claim limitations recite words equivalent to “apply it,” generic computing elements, or insignificant extra-solution activity. Lastly, many of the claim limitations are well-understood, routine, conventional activities/elements that are previously known to the industry. As such, the claims do not impose a meaningful limit on the judicial exception.
Accordingly, the claims do not recite patent-eligible subject matter.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-6, 11-13, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over International Publ. No. WO 2010/144419 A2 (hereinafter “GUTTMAN”) and U.S. Patent Appl. Publ. No. 2018/0055582 A1 (hereinafter “KRIMSKY”).
With respect claim 1 (and in light of the Section 112(b) rejection), GUTTMAN teaches a system for luminal navigation (“MRI guided cardiac interventional systems….,” Abstract, but GUTTMAN also describes embodiments being applicable for “the tracheobronchopulmonary structure (structures including the lungs and the tracheobronchial tree),” ([0196])), the system includes a catheter ([0063]: “flexible intrabody medical device 80,” also called “catheter 80” elsewhere in GUTTMAN) configured for navigation within a luminal network of a patient ([0196] describes embodiments being used for procedures involving a heart, a tracheobronchopulmonary structure among others), the catheter including a sensor ([0063] “tracking members 82 can comprise miniature tracking coils, passive markers and/or a receive antenna.”); and a computing device including a processor and computer readable memory (Figure 36, [0178]: “data processing system [includes a] “processor 410” that communicates with “memory 414”), the memory storing thereon instructions ([0170]: “Computer program code for carrying out…”) that when executed by the processor perform operations discussed below.
GUTTMAN also teaches that the computing device is configured to receive magnetic resonance signals from a magnetic resonance image (MRI) scanner and to generate an MRI image data set ([0007]: “obtain MR image data and generate a series of near real time (RT) MRI images of target anatomy of a patient during a surgical procedure…”); generate a three-dimensional (3D) model from the MRI image data set (see [0007]: “render near RT interactive visualizations of the at least one flexible medical device in the 3-D [MRI] image space with at least one near RT [MRI] image of target patient anatomical structure and a registered pre-acquired volumetric model of the target anatomical structure of the patient.” (emphasis added)). GUTTMAN also teaches that the computing device is configured to determine a location of the sensor within the patient (block 204 in Figure 34, see also [0159]: “X, Y, Z coordinate locations are electronically identified in 3-D MRI image space for each of the tracking coils using the tracking signals (block 204).”; cause display of a location of a portion of the catheter in the 3D model (block 210 in Figure 34, see also [0159]: “Near real time (RT) visualizations of the medical device are generated showing: (a) the model of the patient's anatomy; (b) a physical representation of at least a distal end portion of the medical device using the identified locations of the tracking coils....”(emphasis added)); and update the displayed location of the portion of the catheter; receive second magnetic resonance signals and generate a second MRI image data set; receive an indication of a distal end of the catheter in the second MRI image data set; and update a relative position of a distal end of the catheter and the target in the 3D model. (Id., see also [0138]: “The MRI Scanner 10S (Figures 1-3) can be operated substantially continuously to provide image data that can be used to generate updated maps 100M in the visualizations upon request or automatically. This operation can be ‘in the background’, e.g., transparent to the user so as not to slow down the procedure while providing updated image and tracking data during the course of the procedure.”).
GUTTMAN does not explicitly teach a computing device that is configured to generate a pathway through the 3D model to a target. However, GUTTMAN does describe that “[e]mbodiments of the present invention can be configured to guide and/or place flexible intrabody diagnostic and/or interventional devices in an MRI environment (e.g., interventional medical suite) to any desired internal region of interest of a subject, typically via a natural lumen and/or tortuous path…”. (emphasis added) ([0069]). Moreover, GUTTMAN describes presenting “with additional visual indicators and a ‘target’ navigational indicia (e.g., mark) for visual help in navigation to the site.” ([0131], Figure 23).
In the same field of endeavor, KRIMSKY teaches “methods for planning a procedure for treatment of lung tissue. An exemplary method includes generating a three-dimensional (3D) model of the luminal network, displaying the 3D model of the luminal network…, determining an access path between the target location and the identified point in the luminal network,…and displaying the access path and the calculated risk of injury for the access path on the 3D model.” (Abstract). The image data used to make the model and determine the access path includes magnetic resonance imaging (MRI) image data. ([0050]). KRIMSKY determines one or more access paths to the target location and displays the access paths along with a calculated risk of injury for each path. ([0066]).
It would have been obvious to one having ordinary skill in the art to modify/program the GUTTMAN system such that the computing device generates a pathway through the 3D model to a target. One having ordinary skill in the art would be motivated to modify the system to reduce the risk of injury during the operation. GUTTMAN suggests providing pathways to the user for guidance to a target, and KRIMSKY teaches how to generate multiple paths along with calculated risks for the user to consider before proceeding. There would be a reasonable expectation of success as KRIMSKY teaches that pathways can be generated using MRI data.
RESPONSE TO APPLICANT’S ARGUMENTS:
Applicant argues on page 8 of the Response that GUTTMAN does not teach “generating a three-dimensional (3D) model from the MRI image data set.”
The office action alleges that Guttman teaches “generat[ion of] a three-dimensional (3D) model from the MRI image data set,” however, this is incorrect. Specifically, the office action relies on ¶ [0007], but the cited passage does not teach generation of a 3D model. Instead, this passage teaches “render[ing] near RT interactive visualizations of the at least one flexible medical device in the 3D image space with at least one near RT image of target patient anatomical structure and a registered pre-acquired volumetric model of the target anatomical structure of the patient.” (¶ [0007], emphasis added.) Rather than generating a 3D model, the passage is merely describing the space as a “3D image space” in which the MR images are captured. As noted immediately prior to the passage of Guttman relied upon in the Office Action the method being described in ¶ [0007] starts with “obtain[ing] MR image data and generat[ing] a series of near real time (RT) MRI images of target anatomy of a patient during a surgical procedure using relevant anatomical scan planes associated with a 3-D MRI image space having a coordinate system.” Accordingly, when read in context, the relied upon passage is merely defining the space in which the MR images are captured and not the generation of a 3D model. This understanding is further supported by the portion of T [0007] omitted in the office action, that clarifies that also rendered is “a registered pre-acquired volumetric model of the target anatomical structure of the patient.” If, as alleged in the office action the MR images are used to generate a 3D model, there would be no need to render this “pre-acquired volumetric model. Accordingly, contrary to the assertion in the office action, Guttman does not teach generation of a 3D model.
Examiner disagrees that GUTTMAN does not teach a “generating a 3D model from the MRI image data set.” During patent examination, the pending claims must be given their broadest reasonable interpretation consistent with the specification. (MPEP 2111). “Under a broadest reasonable interpretation (BRI), words of the claim must be given their plain meaning, unless such meaning is inconsistent with the specification.” (MPEP 2111.01).
The only requirement in the claims for the “3D model” is that it is generated “from the MRI image data set.” Applicant’s disclosure does not define “3D model.” In fact, Applicant’s disclosure does not provide a single example of a 3D model in the drawings. Similar to the claim language, Applicant’s use of “3D model” does not limit its interpretation other than requiring that the 3D model is somehow based on image data. (see, e.g., [0031] and [0038]). The 3D model can be derived from one type or more than one type of image data. “Image data 1014 may include the MRI data scans and 3D models derived from the MRI data scans and/or any other image data (e.g., from CT, fluoroscopy, or ultrasound) acquired of the patient either pre-procedurally or intra-procedurally (e.g., with a fluoroscope not shown).” ([0020]). The 3D model can also be derived from more than MRI image data sets, including one that is more focused than another. ([0011], [0057]). Notably, the disclosure does not describe how the image data is transformed into a 3D model.
Applicant’s disclosure also does not limit “3D model” to volumetric image data. When listing data that can be stored by the computing device, Applicant not only considers 3D model as separate from the image data of which it is derived but also considers it separate from volumetric reconstructions: “Computing device 122 may further include a database configured to store patient data, image data sets including CT image data sets (if any), MRI image data sets, fluoroscopic image data sets including 3D models derived from the image data sets, volumetric reconstructions, navigation plans, and any other such data.” ([0031]).
Thus, Applicant’s disclosure does not limit the meaning of 3D model other than the 3D model is somehow based on image data. However, the claims do specify that the image data is MRI image data. With this in mind, GUTTMAN clearly teaches a 3D model at [0007] and elsewhere within the scope of the broadest reasonable interpretation of claim 1. More specifically, GUTTMAN teaches generating a “series of near real time (RT) MRI images” and then rendering “near RT interactive visualizations” that include at least one near RT image and a registered pre-acquired volumetric model. ([0007]). Thus, GUTTMAN’s 3D model is displayed as a visualization and includes (a) at least one near RT image and (b) a registered pre-acquired volumetric model of the target anatomical structure of the patient.
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Figures 5A and 5B are shown below and illustrate what is described in [0007] of GUTTMAN. Figures 5A and 5B include a “visualization 100V” that includes “a volumetric model 100M” of a target anatomical structure, “near real-time MRI images 100MRI,” and a “physical representation 80R” of a device. ([0089]).
Examiner is not certain, but it appears that Applicant is arguing that two-dimensional scan planes or slices that are displayed with a registered pre-acquired volumetric model in a “3D image space” could not be a 3D model. Figures 5A and 5B above show one example of what is described in [0007] and elsewhere of GUTTMAN. Figures 5A and 5B clearly illustrate a 3D model. First, the pre-acquired volumetric model is a 3D model on its own. The pre-acquired volumetric model can be derived from MRI and can be acquired “immediately prior to” the procedure ([0016]). Second, even if the volumetric model was not based on MRI image data, the scan planes identified as 41, 42, and 43 in Figure 5A and include MRI image data. (see, e.g., [0075]: “…one or more of at least four different data sets in either the rendered model 100M or in near RT MRI images 100MRI of relevant scan planes during a procedure.”). The three scan planes are mutually perpendicular to one another forming a 3D space and are positioned relative to the volumetric model 100M. Accordingly, GUTTMAN teaches a processor that causes the computing device to “generate a three-dimensional (3D) model from the MRI image data set” as recited in claim 1.
With respect to claim 2, GUTTMAN teaches that the instructions when executed by the processor cause the display of the updated relative position of the distal end of the catheter and the target in the 3D model. “[T]he visualizations can be electronically rotated based on user input and electronically selectively altering a view of the displayed visualization based on user input so that the visualization includes the at least one flexible device with (a) only a near RT image of the target anatomy, (b) both the near RT image of the anatomy and the registered model of the anatomical structure, or (c) only the registered model of the anatomical structure (block 214).” (emphasis added) ([0161]). As explained above, the near real-time images “RT MR images” are updated throughout the procedures, thereby providing an “updated relative position” of the distal end of the catheter. (see, e.g., Figure 34, [0159], and [0138])
With respect to claim 3 (depending from claim 2), GUTTMAN teaches that the instructions when executed by the processor receive third magnetic resonance signals to form a third MRI image to confirm placement of the catheter, a biopsy tool, or a therapy tool in the target. As explained above, the near real-time images “RT MR images” are updated throughout the procedures, thereby providing an “third magnetic resonance signals to form a third MRI image” of the distal end of the catheter. (see, e.g., Figure 34, [0159], and [0138]). Moreover, GUTTMAN teaches that catheter can be another device, such as a biopsy tool. “To be clear, while detailed drawings of exemplary flexible devices 80 are shown for tracking coils for transseptal needles (septal puncture kit components)and mapping and/or ablation catheters for cardiac use, embodiments of the invention are not intended to be limited to these devices nor to cardiac use… For example, the device can be implemented as injection catheters or diagnostic biopsy needles and the like for any target anatomical location in the body” (emphasis added) ([0072).
With respect to claim 4 (depending from claim 3), GUTTMAN teaches that the instructions when executed by the processor determine whether more targets exist in the 3D model. GUTTMAN teaches that the map can show “locations of target and actual ablation sites (in different colors).” ([0137]). As such, the system determines whether more targets exist after biopsy/therapy of the prior target. (see also [0165]: “Optionally, the tissue characterization map can be displayed with the (planned) indicated target ablation locations in a first color, intensity and/or opacity along with an updated tissue characterization map with MR image data showing actual ablated tissue locations in a different color (side by side or one over the other) (block 332).”).
With respect to claim 5 (depending from claim 4), GUTTMAN does not explicitly teach the limitations of claim 5. However, KRIMSKY teaches that the instructions when executed by the processor cause the display of the 3D model and a pathway to a second target. “[T]he method proceeds to step S446 where a determination is made if there are additional target locations for which access paths have to be determined. If there are additional target locations, the method returns to step S410.” ([0069]). Upon returning to step 410, the method proceeds to display another pathway to the next target. (Figure 4B, S438, [0066]).
It would have been obvious to one having ordinary skill in the art to modify/program the GUTTMAN system such that the computing device generates another pathway through the 3D model to a target and displays that pathway. One having ordinary skill in the art would modify the system to reduce the risk of injury during the operation. GUTTMAN suggests providing pathways to the user for guidance to a target, and KRIMSKY teaches how to generate multiple paths along with calculated risks for the user to consider before proceeding. There would be a reasonable expectation of success as KRIMSKY teaches that pathways can be generated using MRI data.
With respect to claim 6, GUTTMAN teaches that the system further comprises a magnetic resonance scanner generating the magnetic resonance signals. (“MRI Scanner 10” in Figure 29 and described at [0082]).
With respect claim 11, GUTTMAN teaches a method of navigating a catheter to a target within a patient (“MRI guided cardiac interventional systems….,” Abstract, but GUTTMAN also describes embodiments being applicable for “the tracheobronchopulmonary structure (structures including the lungs and the tracheobronchial tree),” GUTTMAN also teaches that the method includes receiving magnetic resonance signals from a magnetic resonance image (MRI) scanner and generating an MRI image data set ([0007]: “obtain MR image data and generate a series of near real time (RT) MRI images of target anatomy of a patient during a surgical procedure…”); generating a three-dimensional (3D) model from the MRI image data set (see [0007]: “render near RT interactive visualizations of the at least one flexible medical device in the 3-D [MRI] image space with at least one near RT [MRI] image of target patient anatomical structure and a registered pre-acquired volumetric model of the target anatomical structure of the patient.” GUTTMAN also teaches that the method includes determining a location of a sensor within the patient (block 204 in Figure 34, see also [0159]: “X, Y, Z coordinate locations are electronically identified in 3-D MRI image space for each of the tracking coils using the tracking signals (block 204).”; ([0063]: “tracking members 82 can comprise miniature tracking coils, passive markers and/or a receive antenna.”); causing display of a location of a portion of a catheter in the 3D model based on the determined position of the sensor (block 210 in Figure 34, see also [0159]: “Near real time (RT) visualizations of the medical device are generated showing: (a) the model of the patient's anatomy; (b) a physical representation of at least a distal end portion of the medical device using the identified locations of the tracking coils....”); and updating a displayed location of the portion of the catheter; receiving second magnetic resonance signals and generate a second MRI image data set; receiving an indication of a distal end of the catheter in the second MRI image data set; and updating a relative position of a distal end of the catheter and the target in the 3D model. (Id., see also [0138]: “The MRI Scanner 10S (Figures 1-3) can be operated substantially continuously to provide image data that can be used to generate updated maps 100M in the visualizations upon request or automatically. This operation can be ‘in the background’, e.g., transparent to the user so as not to slow down the procedure while providing updated image and tracking data during the course of the procedure.”).
GUTTMAN does not explicitly teach a method that includes generating a pathway through the 3D model to a target. However, GUTTMAN does describe that “[e]mbodiments of the present invention can be configured to guide and/or place flexible intrabody diagnostic and/or interventional devices in an MRI environment (e.g., interventional medical suite) to any desired internal region of interest of a subject, typically via a natural lumen and/or tortuous path…”. (emphasis added) ([0069]). Moreover, GUTTMAN describes presenting “with additional visual indicators and a ‘target’ navigational indicia (e.g., mark) for visual help in navigation to the site.” ([0131], Figure 23).
In the same field of endeavor, KRIMSKY teaches “methods for planning a procedure for treatment of lung tissue. An exemplary method includes generating a three-dimensional (3D) model of the luminal network, displaying the 3D model of the luminal network…, determining an access path between the target location and the identified point in the luminal network,…and displaying the access path and the calculated risk of injury for the access path on the 3D model.” (Abstract). The image data used to make the model and determine the access path includes magnetic resonance imaging (MRI) image data. ([0050]). KRIMSKY determines one or more access paths to the target location and displays the access paths along with a calculated risk of injury for each path. ([0066]).
It would have been obvious to one having ordinary skill in the art to modify/program the GUTTMAN method generates a pathway through the 3D model to a target. One having ordinary skill in the art would modify the system to reduce the risk of injury during the operation. GUTTMAN suggests providing pathways to the user for guidance to a target, and KRIMSKY teaches how to generate multiple paths along with calculated risks for the user to consider before proceeding. There would be a reasonable expectation of success as KRIMSKY teaches that pathways can be generated using MRI data.
With respect to claim 12, GUTTMAN teaches that the method includes causing display of the updated relative position of the distal end of the catheter and the target in the 3D model. “[T]he visualizations can be electronically rotated based on user input and electronically selectively altering a view of the displayed visualization based on user input so that the visualization includes the at least one flexible device with (a) only a near RT image of the target anatomy, (b) both the near RT image of the anatomy and the registered model of the anatomical structure, or (c) only the registered model of the anatomical structure (block 214).” (emphasis added) ([0161]). As explained above, the near real-time images “RT MR images” are updated throughout the procedures, thereby providing an “updated relative position” of the distal end of the catheter. (see, e.g., Figure 34, [0159], and [0138]).
With respect to claim 13 (depending from claim 12), GUTTMAN teaches that the method includes receiving third magnetic resonance signals to form a third MRI image to confirm placement of the catheter, a biopsy tool, or a therapy tool in the target. As explained above, the near real-time images “RT MR images” are updated throughout the procedures, thereby providing an “third magnetic resonance signals to form a third MRI image” of the distal end of the catheter. (see, e.g., Figure 34, [0159], and [0138]). Moreover, GUTTMAN teaches that catheter can be another device, such as a biopsy tool. “To be clear, while detailed drawings of exemplary flexible devices 80 are shown for tracking coils for transseptal needles (septal puncture kit components)and mapping and/or ablation catheters for cardiac use, embodiments of the invention are not intended to be limited to these devices nor to cardiac use… For example, the device can be implemented as injection catheters or diagnostic biopsy needles and the like for any target anatomical location in the body” (emphasis added) ([0072).
With respect claim 17, GUTTMAN teaches a method of navigating a catheter to a target within a patient (“MRI guided cardiac interventional systems….,” Abstract, but GUTTMAN also describes embodiments being applicable for “the tracheobronchopulmonary structure (structures including the lungs and the tracheobronchial tree),” GUTTMAN also teaches that the method includes receiving magnetic resonance signals from a magnetic resonance image (MRI) scanner and generating an MRI image data set ([0007]: “obtain MR image data and generate a series of near real time (RT) MRI images of target anatomy of a patient during a surgical procedure…”); generating a three-dimensional (3D) model from the MRI image data set (see [0007]: “render near RT interactive visualizations of the at least one flexible medical device in the 3-D [MRI] image space with at least one near RT [MRI] image of target patient anatomical structure and a registered pre-acquired volumetric model of the target anatomical structure of the patient.” GUTTMAN also teaches that the method includes determining a location of a distal portion of a catheter within the 3D model (204 in Figure 34, see also [0159]: “X, Y, Z coordinate locations are electronically identified in 3-D MRI image space for each of the tracking coils using the tracking signals (block 204).”; ([0063] “tracking members 82 can comprise miniature tracking coils, passive markers and/or a receive antenna.”); causing display of the location of at least the distal portion of a catheter in the 3D model (210 in Figure 34, see also [0159]: “Near real time (RT) visualizations of the medical device are generated showing: (a) the model of the patient's anatomy; (b) a physical representation of at least a distal end portion of the medical device using the identified locations of the tracking coils....”); receiving signals from a sensor incorporated in the catheter (204 in Figure 34, see also [0159]: “X, Y, Z coordinate locations are electronically identified in 3-D MRI image space for each of the tracking coils using the tracking signals (block 204).”; updating a displayed location of at least a portion of the catheter based on the received signals; receiving second magnetic resonance signals and generate a second MRI image data set, and updating a displayed position of the distal portion of the catheter in the 3D model based on the second MRI image data set. (Id., see also [0138]: “The MRI Scanner 10S (Figures 1-3) can be operated substantially continuously to provide image data that can be used to generate updated maps 100M in the visualizations upon request or automatically. This operation can be ‘in the background’, e.g., transparent to the user so as not to slow down the procedure while providing updated image and tracking data during the course of the procedure.”).
GUTTMAN also teaches that the method includes wherein the second MRI image data set is focused to an area proximate the sensor. In the same field of endeavor, GUTTMAN teaches “During the procedure, as the distal end of the device 80 (e.g., ablation catheter) approaches a location that corresponds to a target treatment (e.g., ablation) site 55t, the circuit 60c (e.g., MR Scanner 10S) can automatically select scan planes that “snap to” the tip and/or distal end portion location using a scan plane defined “on the fly” based on the calculated location of the distal end portion of the device (typically selected so that the slice includes a region offset from and/or projected forward a distance beyond the device such as between about 0-4 mm, typically about 1-2 mm) and/or using one or more of the preset scan planes associated with that location to obtain real-time MR image data of the associated tissue.” (emphasis added) ([0124])
GUTTMAN does not explicitly teach a method that includes generating a pathway through the 3D model to a target. However, GUTTMAN does describe that “[e]mbodiments of the present invention can be configured to guide and/or place flexible intrabody diagnostic and/or interventional devices in an MRI environment (e.g., interventional medical suite) to any desired internal region of interest of a subject, typically via a natural lumen and/or tortuous path…”. (emphasis added) ([0069]). Moreover, GUTTMAN describes presenting “with additional visual indicators and a ‘target’ navigational indicia (e.g., mark) for visual help in navigation to the site.” ([0131], Figure 23).
In the same field of endeavor, KRIMSKY teaches “methods for planning a procedure for treatment of lung tissue. An exemplary method includes generating a three-dimensional (3D) model of the luminal network, displaying the 3D model of the luminal network…, determining an access path between the target location and the identified point in the luminal network,…and displaying the access path and the calculated risk of injury for the access path on the 3D model.” (Abstract). The image data used to make the model and determine the access path includes magnetic resonance imaging (MRI) image data. ([0050]). KRIMSKY determines one or more access paths to the target location and displays the access paths along with a calculated risk of injury for each path. ([0066]).
It would have been obvious to one having ordinary skill in the art to modify/program the GUTTMAN method generates a pathway through the 3D model to a target. One having ordinary skill in the art would modify the system to reduce the risk of injury during the operation. GUTTMAN suggests providing pathways to the user for guidance to a target, and KRIMSKY teaches how to generate multiple paths along with calculated risks for the user to consider before proceeding. There would be a reasonable expectation of success as KRIMSKY teaches that pathways can be generated using MRI data.
Claims 7, 8, 14, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over International Publ. No. WO 2010/144419 A2 (hereinafter “GUTTMAN”) and U.S. Patent Appl. Publ. No. 2018/0055582 A1 (hereinafter “KRIMSKY”) as applied to claim 1 above, and further in view of U.S. Patent Appl. Publ. No. 2018/0049693 A1 (hereinafter “COVIDIEN”).
With respect to claims 7 and 8 (depending from claim 7), GUTTMAN does not explicitly teach the limitations of claims 7 and 8. However, COVIDIEN teaches that the sensor is an electromagnetic sensor and a transmitter mat can cause the generation of an electromagnetic field.
In the same field of endeavor, COVIDIEN teaches a “[s]ystem 10 [that] generally includes an operating table 40 configured to support a patient “P”, a bronchoscope 50 configured for insertion through the patient's mount into the patient's airways, monitoring equipment 60 coupled to the bronchoscope 50 for displaying video images received from bronchoscope 50, a tracking system 70 including a tracking module 72, a plurality of reference sensors 74, and a transmitter mat 76.” (emphasis added) ([0070]). “[A] sensor 100 d (FIGS. 2A, 3A, and 4A) that, in conjunction with tracking system 70 (FIG. 1)….” ([0059]). “A transmitter mat 76 is positioned beneath the patient “P” and is a transmitter of electromagnetic radiation. Transmitter mat 76 includes a stack of three substantially planar rectangular loop antennas (not shown) configured to be connected to drive circuitry (not shown).” ([0076]).
It would have been obvious to one having ordinary skill in the art to either replace the sensor in GUTTMAN or incorporate the EM sensor from COVIDIEN and to generate an electromagnetic field using the transmitter mat. One would have been motivated to use the EM sensor as it can be used with MRI and offer redundancy for other tracking systems. There would have been a reasonable expectation of success as COVIDIEN teaches they can be used with surgical navigation.
With respect to claims 14 and 15 (depending from claim 14), GUTTMAN does not explicitly teach the limitations of claims 14 and 15. However, COVIDIEN teaches generating an electromagnetic field and determining a location of the sensor in the electromagnetic field or a transmitter mat causing the generation of an electromagnetic field.
In the same field of endeavor, COVIDIEN teaches a “[s]ystem 10 [that] generally includes an operating table 40 configured to support a patient “P”, a bronchoscope 50 configured for insertion through the patient's mount into the patient's airways, monitoring equipment 60 coupled to the bronchoscope 50 for displaying video images received from bronchoscope 50, a tracking system 70 including a tracking module 72, a plurality of reference sensors 74, and a transmitter mat 76.” (emphasis added) ([0070]). “[A] sensor 100 d (FIGS. 2A, 3A, and 4A) that, in conjunction with tracking system 70 (FIG. 1)….” ([0059]). “A transmitter mat 76 is positioned beneath the patient “P” and is a transmitter of electromagnetic radiation. Transmitter mat 76 includes a stack of three substantially planar rectangular loop antennas (not shown) configured to be connected to drive circuitry (not shown).” (emphasis added) ([0076]).
It would have been obvious to one having ordinary skill in the art to either replace the sensor (e.g., tracking coils) in GUTTMAN with or add the EM sensor from COVIDIEN and to generate an electromagnetic field using the transmitter mat. One would have been motivated to use the EM sensor and mat system as it can be used with MRI and offer redundancy for other tracking systems. There would have been a reasonable expectation of success as COVIDIEN teaches they can be used with surgical navigation.
Claims 1-6, 11-13, and 17
Claims 7, 8, 14, and 15
Claims 7, 9, 14 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over International Publ. No. WO 2010/144419 A2 (hereinafter “GUTTMAN”) and U.S. Patent Appl. Publ. No. 2018/0055582 A1 (hereinafter “KRIMSKY”) as applied to claim 1 above, and further in view of U.S. Patent Appl. Publ. No. 2010/0280353 A1 (hereinafter “ROTH”).
With respect to claims 7 and 9 (depending from claim 7), GUTTMAN does not explicitly teach to cause the generation of an electromagnetic field and the sensor is an electromagnetic sensor or explicitly teach wherein a magnetic coil of the MRI scanner generates the electromagnetic field.
However, ROTH teaches a method of “[t]racking based on the gradient fields of magnetic resonance imaging (MRI) scanners based on passive operation of the tracking system without any change of the scanner's hardware or mode of operation.” (Abstract). To this end, ROTH uses a sensor having three orthogonal coils. (see, e.g., “sensor 20” in Figure 4). ROTH notes that the “invention has significant advantages over existing methodologies. Compared with stereotaxis, either the frame or frameless techniques, the new methodology enables the use of devices like catheters or surgical instrumentation without the need for direct line of sight with the device and under realtime MRI.” ([0030]).
ROTH’s invention provides “a technique to create a custom MRI pulse sequence is disclosed. Through this technique any standard pulse sequence of the scanner can be modified to include gradient activations specifically designated for tracking.” (Abstract). Furthermore, it has broad applicability within “Interventional MRI: The sensor can be used with various devices, like miniature tools for minimally invasive surgery, catheters inside blood vessels, rigid and flexible endoscopes, biopsy and aspiration needles.” ([0094]). “Another potential application is to use the information of the location and orientation of the device in order to enable display of the MRI images in reference to the device local coordinate system, as if the operator is looking through the device and in the direction of the tip, similar to the use of optical endoscopes.” (Id).
It would have been obvious to one having ordinary skill in the art to incorporate the ROTH sensor and technique with the GUTTMAN system such that the sensor is an electromagnetic sensor and a magnetic coil of the MRI scanner generates the electromagnetic field. One would be motivated to use the ROTH sensor and technique because it eliminates one component (e.g., the separate EM field generator) while offering redundancy to the tracking coils of GUTTMAN and also enabling the “display of the MRI images in reference to the device local coordinate system, as if the operator is looking through the device and in the direction of the tip” as taught in ROTH. ([0094]). There would be a reasonable expectation of success as ROTH teaches that the invention can be incorporated into MRI scanners and used for surgical navigation.
With respect to claims 14 and 16 (depending from claim 14), GUTTMAN does not explicitly teach generating an electromagnetic field and determining a location of the sensor in the electromagnetic field (claim 14), wherein the sensor is an electromagnetic sensor and a magnetic coil of the MRI scanner generates the electromagnetic field (claim 16).
However, ROTH teaches a method of “[t]racking based on the gradient fields of magnetic resonance imaging (MRI) scanners based on passive operation of the tracking system without any change of the scanner's hardware or mode of operation.” (Abstract). To this end, ROTH uses a sensor having three orthogonal coils. (see, e.g., “sensor 20” in Figure 4) the location of which can be determined in the electromagnetic field. ([0048]). ROTH notes that the “invention has significant advantages over existing methodologies. Compared with stereotaxis, either the frame or frameless techniques, the new methodology enables the use of devices like catheters or surgical instrumentation without the need for direct line of sight with the device and under realtime MRI.” ([0030]).
ROTH’s invention provides “a technique to create a custom MRI pulse sequence is disclosed. Through this technique any standard pulse sequence of the scanner can be modified to include gradient activations specifically designated for tracking.” (Abstract). Furthermore, it has broad applicability within “Interventional MRI: The sensor can be used with various devices, like miniature tools for minimally invasive surgery, catheters inside blood vessels, rigid and flexible endoscopes, biopsy and aspiration needles.” ([0094]). “Another potential application is to use the information of the location and orientation of the device in order to enable display of the MRI images in reference to the device local coordinate system, as if the operator is looking through the device and in the direction of the tip, similar to the use of optical endoscopes.” (Id).
It would have been obvious to one having ordinary skill in the art to incorporate the ROTH sensor and technique with the GUTTMAN system such that the sensor is an electromagnetic sensor and a magnetic coil of the MRI scanner generates the electromagnetic field. One would be motivated to use the ROTH sensor and technique because it eliminates one component (e.g., the separate EM field generator) while offering redundancy to the tracking coils of GUTTMAN and also enabling the “display of the MRI images in reference to the device local coordinate system, as if the operator is looking through the device and in the direction of the tip” as taught in ROTH. ([0094]). There would be a reasonable expectation of success as ROTH teaches that the invention can be incorporated into MRI scanners and used for surgical navigation.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over International Publ. No. WO 2010/144419 A2 (hereinafter “GUTTMAN”) and U.S. Patent Appl. Publ. No. 2018/0055582 A1 (hereinafter “KRIMSKY”) as applied to claim 1 above, and further in view of U.S. Patent Appl. Publ. No. 2019/0142374 A1 (hereinafter “KRUECKER”).
With respect to claim 10, GUTTMAN does not explicitly teach wherein the sensor is an inertial measurement unit.
KRUECKER teaches medical navigation systems in which the system “employs inertial-based tracking methods and selectively employs image-based tracking methods to track medical imaging devices.” ([0001]). KRUECKER describes alternative tracking systems that use various technologies but also explains that those can be expensive and suggests motion-based tracking as an option. However, “motion-based inertial tracking devices experience bias which can lead to tracking inaccuracies.” ([0002]). “When using motion-based inertial tracking system for medical device tracking, the pose of the medical device may not always be tracked accurately over extended periods of time.” ([0003]). To address this concern, “[e]mbodiments of the present system may provide a system and method for acquiring image-based information and employing this image-based information to correct bias errors in inertial-based sensors of imaging devices for position tracking.” ([0005]). Embodiments “may reduce the need for highly-complex and expensive inertial or non-inertial sensors (such as electro-magnetic tracking sensors) and may allow the implementation of simple, low-cost inertial sensors.”
In KRUECKER, “[t]he system 100 may include one or more of a medical imaging device (MID)… an inertial measurement unit (IMU) 111, and a tracking corrector 106 communicatively coupled to each other via any suitable wired and/or wireless methods.” ([0032]). KRUECKER’s system employs periodic bias correction using image data. ([0005]).
It would have been obvious to one having ordinary skill in the art to use an inertial measurement unit (IMU) as the sensor in the GUTTMAN system. One would be motivated to use an IMU with KRUECKER’s technique because electro-magnetic tracking sensors can be expensive whereas KRUECKER’s method permits low-cost IMUs. There would have been a reasonable expectation of success as KRUECKER teaches that the IMU can be incorporated into tracking systems for surgical navigation.
Claims 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over International Publ. No. WO 2010/144419 A2 (hereinafter “GUTTMAN”) and U.S. Patent Appl. Publ. No. 2018/0055582 A1 (hereinafter “KRIMSKY”) as applied to claim 17 above, and further in view of U.S. Patent Appl. Publ. No. 2019/0142374 A1 (hereinafter “KRUECKER”).
With respect to claim 18, GUTTMAN does not explicitly teach wherein the sensor is an inertial measurement unit.
KRUECKER teaches medical navigation systems in which the system “employs inertial-based tracking methods and selectively employs image-based tracking methods to track medical imaging devices.” ([0001]). KRUECKER describes alternative tracking systems that use various technologies but also explains that those can be expensive and suggests motion-based tracking as an option. However, “motion-based inertial tracking devices experience bias which can lead to tracking inaccuracies.” ([0002]). “When using motion-based inertial tracking system for medical device tracking, the pose of the medical device may not always be tracked accurately over extended periods of time.” ([0003]). To address this concern, “[e]mbodiments of the present system may provide a system and method for acquiring image-based information and employing this image-based information to correct bias errors in inertial-based sensors of imaging devices for position tracking.” ([0005]). Embodiments “may reduce the need for highly-complex and expensive inertial or non-inertial sensors (such as electro-magnetic tracking sensors) and may allow the implementation of simple, low-cost inertial sensors.”
In KRUECKER, “[t]he system 100 may include one or more of a medical imaging device (MID)… an inertial measurement unit (IMU) 111, and a tracking corrector 106 communicatively coupled to each other via any suitable wired and/or wireless methods.” ([0032]). KRUECKER’s system employs periodic bias correction using image data. ([0005]).
It would have been obvious to one having ordinary skill in the art to use an inertial measurement unit (IMU) as the sensor in the GUTTMAN system. One would be motivated to use an IMU with KRUECKER’s technique because electro-magnetic tracking sensors can be expensive whereas KRUECKER’s method permits low-cost IMUs. There would have been a reasonable expectation of success as KRUECKER teaches that the IMU can be incorporated into tracking systems for surgical navigation.
With respect to claim 19, GUTTMAN does not explicitly teach wherein the updated displayed position of the distal portion of the catheter is employed to eliminate drift of the IMU.
KRUECKER’s primary concern is correcting for bias (i.e., drift). “However, any small error, bias or drift in acceleration and angular velocity may be accumulative over time and, thus, in the pose estimate, leading to deteriorating pose estimates over time.” ([0046]). Accordingly, KRUECKER teaches that “the sensors 112 are positioned as close to the image plane (i.e., as close to the tip of the probe 102) as possible, in order to minimize any errors introduced by extrapolating the motion/rotation (which was measured at the sensor position) to the image plane position.” ([0036]).
It would have been obvious to one having ordinary skill in the art to use the imaging (i.e, that shows the updated displayed position of the distal portion of the catheter) to eliminate drift of the IMU. One would be motivated to use an IMU with KRUECKER’s technique because electro-magnetic tracking sensors can be expensive whereas KRUECKER’s method permits low-cost IMUs and drift-correction for the tip of the tool, which can be the most important to follow. There would have been a reasonable expectation of success as KRUECKER teaches that the IMU can be incorporated into tracking systems for surgical navigation.
With respect to claim 20, GUTTMAN teaches further comprising receiving subsequent magnetic resonance signals and generating additional MRI image data sets, wherein the additional MRI image data sets are focused to the area proximate the sensor; and updating the displayed position of the distal portion of the catheter in the 3D model based on the second MRI image data set. ([0138]: “The MRI Scanner 10S (Figures 1-3) can be operated substantially continuously to provide image data that can be used to generate updated maps 100M in the visualizations upon request or automatically. This operation can be ‘in the background’, e.g., transparent to the user so as not to slow down the procedure while providing updated image and tracking data during the course of the procedure.”).
GUTTMAN also teaches wherein the second MRI image data set is focused to an area proximate the sensor. “During the procedure, as the distal end of the device 80 (e.g., ablation catheter) approaches a location that corresponds to a target treatment (e.g., ablation) site 55t, the circuit 60c (e.g., MR Scanner 10S) can automatically select scan planes that “snap to” the tip and/or distal end portion location using a scan plane defined “on the fly” based on the calculated location of the distal end portion of the device (typically selected so that the slice includes a region offset from and/or projected forward a distance beyond the device such as between about 0-4 mm, typically about 1-2 mm) and/or using one or more of the preset scan planes associated with that location to obtain real-time MR image data of the associated tissue.” ([0124]).
Prior Art of Record
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2019/0374130 A1 teaches a system that determines a plurality of paths for selection by a user who may select one of these paths as a reference path. The system may be used during bronchoscopic procedures.
US 2022/0156925 A1 teaches a process that includes determining, during an interventional procedure (e.g., bronchoscopic procedure), whether a current position of a tracked device is outside of the pathways in a three-dimensional model.
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.
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/JASON P GROSS/Examiner, Art Unit 3797 /SERKAN AKAR/Primary Examiner, Art Unit 3797