WO2025122431A1

WO2025122431A1 - Systems and methods for updating surgical images using nuclear magnetic resonance (nmr) measurements

Info

Publication number: WO2025122431A1
Application number: PCT/US2024/058104
Authority: WO
Inventors: Dominic M. Graziani; Ma Luo
Original assignee: Medtronic Navigation Inc
Current assignee: Medtronic Navigation Inc
Priority date: 2023-12-06
Filing date: 2024-12-02
Publication date: 2025-06-12
Anticipated expiration: 2026-06-06

Abstract

A method according to at least one embodiment of the present disclosure includes: receiving scan data associated with a Nuclear Magnetic Resonance (NMR) profilometer scan of an anatomical structure; determining, based on the scan data and tracking of the NMR profilometer, a location of the anatomical structure; determining a difference between the determined location of the anatomical structure and a depicted location of the anatomical structure in a multi-dimensional model; comparing the difference to a threshold value; and updating, when the difference meets or exceeds the threshold value, the multi-dimensional model to reduce the difference.

Description

SYSTEMS AND METHODS FOR UPDATING SURGICAL IMAGES USING NUCLEAR MAGNETIC RESONANCE (NMR) MEASUREMENTS

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] The present application claims the benefit of and priority to U.S. Provisional Application No. 63/607,039 filed on December 6, 2023, entitled “SYSTEMS AND METHODS FOR UPDATING SURGICAL IMAGES USING NUCLEAR MAGNETIC RESONANCE (NMR) MEASUREMENTS”, the entirety of which is hereby incorporated herein by reference.

FIELD OF INVENTION

[0002] The present disclosure is generally directed to updating surgical images, and relates more particularly to using Nuclear Magnetic Resonance (NMR) data to update surgical images.

BACKGROUND

[0003] Surgical robots may assist a surgeon or other medical provider in carrying out a surgical procedure, or may complete one or more surgical procedures autonomously. Imaging may be used by a medical provider for diagnostic and/or therapeutic purposes. Patient anatomy can change over time, particularly following placement of a medical implant in the patient anatomy.

BRIEF SUMMARY

[0004] Human brain deformation may occur during cranial procedures, leading to reduced surgical navigation accuracy. NMR may be beneficial in detecting and accounting for such deformation, but NMR machines are bulky and expensive, requiring additional resources to set up and implement. Accordingly to embodiments of the present disclosure, a navigated handheld single-sided NMR profilometer provides a non-invasive method for determining brain shift by enabling ID depth profile generation that can be used to detect, determine, and adjust for brain deformation. Such an approach beneficially reduces surgical costs while increasing the likelihood of positive surgical outcomes.

[0005] Example aspects of the present disclosure include:

[0006] A method according to at least one embodiment of the present disclosure comprises: receiving scan data associated with a Nuclear Magnetic Resonance (NMR) profilometer scan of an anatomical structure; determining, based on the scan data and tracking of the NMR profilometer, a location of the anatomical structure; determining a difference between the determined location of the anatomical structure and a depicted location of the anatomical structure in a multi-dimensional model; comparing the difference to a threshold value; and updating, when the difference meets or exceeds the threshold value, the multi-dimensional model to reduce the difference.

[0007] Any of the aspects herein, wherein the scan data comprises one-dimensional (ID) depth data.

[0008] Any of the aspects herein, wherein the multi-dimensional model is based on at least one of a preoperative image of the anatomical structure and an intraoperative image of the anatomical structure.

[0009] Any of the aspects herein, further comprising: rendering, to a display, at least one of the updated multi-dimensional model and the scan data.

[0010] Any of the aspects herein, wherein the updating of the multi-dimensional model is performed by an Artificial Intelligence (Al) model.

[0011] Any of the aspects herein, wherein the NMR profilometer comprises a plurality of navigation markers.

[0012] Any of the aspects herein, wherein the NMR profilometer comprises a magnet and a tunable radiofrequency (RF) coil.

[0013] Any of the aspects herein, wherein a navigation system navigates a surgical tool based on the updated multi-dimensional model.

[0014] A system according to at least one embodiment of the present disclosure comprises: a processor; and a memory storing data thereon that, when processed by the processor, enable the processor to: receive scan data associated with a Nuclear Magnetic Resonance (NMR) profilometer scan of an anatomical structure; determine, based on the scan data and tracking of the NMR profilometer, a location of the anatomical structure; determine a difference between the determined location of the anatomical structure and a depicted location of the anatomical structure in a multi-dimensional model; compare the difference to a threshold value; and update, when the difference meets or exceeds the threshold value, the multi-dimensional model to reduce a value of the difference.

[0015] Any of the aspects herein, wherein the scan data comprises one-dimensional (ID) depth data.

[0016] Any of the aspects herein, wherein the multi-dimensional model is based on at least one of a preoperative image of the anatomical structure and an intraoperative image of the anatomical structure.

[0017] Any of the aspects herein, wherein the data, when processed by the processor, further enable the processor to: render, to a display, at least one of the updated multi- dimensional model and the scan data.

[0018] Any of the aspects herein, wherein the updating of the multi-dimensional model is performed by an Artificial Intelligence (Al) model.

[0019] Any of the aspects herein, wherein the NMR profilometer comprises a plurality of navigation markers.

[0020] Any of the aspects herein, wherein the NMR profilometer comprises a magnet and a tunable radiofrequency (RF) coil.

[0021] Any of the aspects herein, wherein a navigation system navigates a surgical tool based on the updated multi-dimensional model.

[0022] A system according to at least one embodiment of the present disclosure comprises: a Nuclear Magnetic Resonance (NMR) profilometer; a processor; and a memory storing data thereon that, when processed by the processor, enable the processor to: receive scan data associated with a scan performed by the NMR profilometer of an anatomical structure; determine, based on the scan data and tracking of the NMR profilometer, a location of the anatomical structure; compare the determined location of the anatomical structure with a depicted location of the anatomical structure in a multidimensional model to generate a value indicative of a difference between the determined location and the depicted location; compare the value indicative of the difference to a threshold value; and update, when the value indicative of the difference meets or exceeds the threshold value, the multi-dimensional model to reduce the value of the difference.

[0023] Any of the aspects herein, wherein the scan data comprises one-dimensional (ID) depth data.

[0024] Any of the aspects herein, wherein the data, when processed by the processor, further enable the processor to: render, to a display, at least one of the updated multidimensional model and the scan data.

[0025] Any of the aspects herein, wherein the updating of the multi-dimensional model is performed by an Artificial Intelligence (Al) model.

[0026] Any aspect in combination with any one or more other aspects.

[0027] Any one or more of the features disclosed herein.

[0028] Any one or more of the features as substantially disclosed herein.

[0029] Any one or more of the features as substantially disclosed herein in combination with any one or more other features as substantially disclosed herein.

[0030] Any one of the aspects/features/embodiments in combination with any one or more other aspects/features/embodiments. [0031] Use of any one or more of the aspects or features as disclosed herein.

[0032] It is to be appreciated that any feature described herein can be claimed in combination with any other feature(s) as described herein, regardless of whether the features come from the same described embodiment.

[0033] The details of one or more aspects of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the techniques described in this disclosure will be apparent from the description and drawings, and from the claims.

[0034] The phrases “at least one”, “one or more”, and “and/or” are open-ended expressions that are both conjunctive and disjunctive in operation. For example, each of the expressions “at least one of A, B and C”, “at least one of A, B, or C”, “one or more of A, B, and C”, “one or more of A, B, or C” and “A, B, and/or C” means A alone, B alone, C alone, A and B together, A and C together, B and C together, or A, B and C together. When each one of A, B, and C in the above expressions refers to an element, such as X, Y, and Z, or class of elements, such as Xl-Xn, Yl-Ym, and Zl-Zo, the phrase is intended to refer to a single element selected from X, Y, and Z, a combination of elements selected from the same class (e.g., XI and X2) as well as a combination of elements selected from two or more classes (e.g., Y1 and Zo).

[0035] The term “a” or “an” entity refers to one or more of that entity. As such, the terms “a” (or “an”), “one or more” and “at least one” can be used interchangeably herein. It is also to be noted that the terms “comprising”, “including”, and “having” can be used interchangeably.

[0036] The preceding is a simplified summary of the disclosure to provide an understanding of some aspects of the disclosure. This summary is neither an extensive nor exhaustive overview of the disclosure and its various aspects, embodiments, and configurations. It is intended neither to identify key or critical elements of the disclosure nor to delineate the scope of the disclosure but to present selected concepts of the disclosure in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other aspects, embodiments, and configurations of the disclosure are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.

[0037] Numerous additional features and advantages of the present disclosure will become apparent to those skilled in the art upon consideration of the embodiment descriptions provided hereinbelow. BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS [0038] The accompanying drawings are incorporated into and form a part of the specification to illustrate several examples of the present disclosure. These drawings, together with the description, explain the principles of the disclosure. The drawings simply illustrate preferred and alternative examples of how the disclosure can be made and used and are not to be construed as limiting the disclosure to only the illustrated and described examples. Further features and advantages will become apparent from the following, more detailed, description of the various aspects, embodiments, and configurations of the disclosure, as illustrated by the drawings referenced below.

[0039] Fig. l is a block diagram of a system according to at least one embodiment of the present disclosure;

[0040] Fig. 2 shows an NMR profilometer interacting with a patient according to at least one embodiment of the present disclosure;

[0041] Fig. 3 A shows an ideal depth profile before a craniotomy according to at least one embodiment of the present disclosure;

[0042] Fig. 3B shows an ideal depth profile after a craniotomy according to at least one embodiment of the present disclosure; and

[0043] Fig. 4 is a flowchart according to at least one embodiment of the present disclosure.

DETAILED DESCRIPTION

[0044] It should be understood that various aspects disclosed herein may be combined in different combinations than the combinations specifically presented in the description and accompanying drawings. It should also be understood that, depending on the example or embodiment, certain acts or events of any of the processes or methods described herein may be performed in a different sequence, and/or may be added, merged, or left out altogether (e.g., all described acts or events may not be necessary to carry out the disclosed techniques according to different embodiments of the present disclosure). In addition, while certain aspects of this disclosure are described as being performed by a single module or unit for purposes of clarity, it should be understood that the techniques of this disclosure may be performed by a combination of units or modules associated with, for example, a computing device and/or a medical device.

[0045] In one or more examples, the described methods, processes, and techniques may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Alternatively or additionally, functions may be implemented using machine learning (ML) models, neural networks, artificial neural networks, or combinations thereof (alone or in combination with instructions). Computer-readable media may include non-transitory computer-readable media, which corresponds to a tangible medium such as data storage media (e.g., RAM, ROM, EEPROM, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer).

[0046] Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors (e.g., Intel Core i3, i5, i7, or i9 processors; Intel Celeron processors; Intel Xeon processors; Intel Pentium processors; AMD Ryzen processors; AMD Athlon processors; AMD Phenom processors; Apple A10 or 10X Fusion processors; Apple Al l, A12, A12X, A12Z, or A13 Bionic processors; or any other general purpose microprocessors), graphics processing units (e.g., Nvidia GeForce RTX 2000-series processors, Nvidia GeForce RTX 3000-series processors, AMD Radeon RX 5000-series processors, AMD Radeon RX 6000-series processors, or any other graphics processing units), application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor” as used herein may refer to any of the foregoing structure or any other physical structure suitable for implementation of the described techniques. Also, the techniques could be fully implemented in one or more circuits or logic elements.

[0047] Before any embodiments of the disclosure are explained in detail, it is to be understood that the disclosure is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the drawings. The disclosure is capable of other embodiments and of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of “including,” “comprising,” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. Further, the present disclosure may use examples to illustrate one or more aspects thereof. Unless explicitly stated otherwise, the use or listing of one or more examples (which may be denoted by “for example,” “by way of example,” “e.g.,” “such as,” or similar language) is not intended to and does not limit the scope of the present disclosure.

[0048] Accurate surgical navigation relies on the assumption that the anatomy is rigid and unchanged during a surgery or surgical procedure. In cranial procedures, the brain may deform due to fluid loss, gravity, tissue resection, osmotic conditions driven by intraoperative drugs/osmotic agents administered to the patient, tissue response (e.g., swelling), combinations thereof, etc. Such deformation may result in the preoperative Magnetic Resonance Imaging (MRI) or Computed Tomography (CT) images on a navigation system no longer representing the patient’s anatomy. This brain shift phenomenon can introduce error in navigated cranial procedures. Surgeons might have to rely on visual cues (if any) and/or intuition to compensate for the inaccuracy. It is desirable to have a means of measuring how the brain has shifted so the surgeon can compensate for the shift and/or the navigation system can non-rigidly transform the preoperative image to the true shape of the brain.

[0049] According to embodiments of the present disclosure, a navigated handheld single-sided nuclear magnetic resonance (NMR) profilometer may be provided. The profilometer implements the same physics as an MRI machine, but instead of producing a three-dimensional (3D) image of the brain, the profilometer produces a one-dimensional (ID) depth profile of the anatomical tissues under the profilometer. The different relaxation properties of the tissue would allow for identification of the boundary between the skin, skull, dura, cerebrospinal fluid (CSF), and the surface of the brain. Additionally, any air gaps that develop due to the brain shift would be recognizable as signal voids. Such signal voids may allow a user or system to non-invasively probe at different locations around the skull to locate the surface of the brain. The profilometer may be tracked by a navigation system, such that local measurements of the brain shift could be displayed to a user via a display.

[0050] The profilometer comprises a magnet that produces a static magnetic field, and a tunable RF coil for exciting the sample and receiving the NMR signal. The magnetic resonance frequency of the sample is proportional to the magnetic field strength. If the field decays from the surface of the device, the frequency of the RF coil can be tuned to excite the sample at different depths. By sweeping the RF coil frequency across a range of frequencies, a ID depth profile can be generated. For example, the ID depth profile may change after a craniotomy. The CSF may be drained, resulting in the brain pulling away from the skull, leaving an air gap (which may appear in the ID depth profile). The distance from the skin to the surface of the brain can be measured and overlayed on the navigation system.

[0051] According to embodiments of the present disclosure, the NMR profilometer may provide a non-invasive method for determining brain-shift in navigated cranial procedures. The profilometer may be less expensive, less bulky, and more portable than an intraoperative MRI machine. Instead of acquiring full depth profiles at every location, acquisition time can be significantly improved by locking on the signal at the interface of air and brain and making small adjustments to the probing depths as the device moves around the head of the patient. Such an approach provides a non-invasive method for measuring brain shift, possibly improving navigation accuracy and providing better patient outcomes.

[0052] Embodiments of the present disclosure provide technical solutions to one or more of the problems of (1) inaccurate navigation in cranial surgeries or surgical procedures and (2) reduced time and cost of cranial surgeries or surgical procedures. [0053] Turning first to Fig. 1, a block diagram of a system 100 according to at least one embodiment of the present disclosure is shown. The system 100 may be used to update depictions of anatomical structures based on NMR scan data; control, pose, and/or otherwise manipulate a surgical mount system, a surgical arm, and/or surgical tools attached thereto; and/or carry out one or more other aspects of the method disclosed herein. The system 100 comprises a computing device 102, one or more imaging devices 112, a robot 114, a navigation system 118, a database 130, a cloud or other network 134, a display 136, and/or an NMR profilometer 140. Systems according to other embodiments of the present disclosure may comprise more or fewer components than the system 100. For example, the system 100 may not include the imaging device 112, the robot 114, one or more components of the computing device 102, the database 130, and/or the cloud 134. [0054] The computing device 102 comprises a processor 104, a memory 106, a communication interface 108, and a user interface 110. Computing devices according to other embodiments of the present disclosure may comprise more or fewer components than the computing device 102.

[0055] The processor 104 of the computing device 102 may be any processor described herein or any similar processor. The processor 104 may be configured to execute instructions stored in the memory 106, which instructions may cause the processor 104 to carry out one or more computing steps utilizing or based on data received from the imaging device 112, the robot 114, the navigation system 118, the database 130, the cloud 134, and/or the NMR profilometer 140. The processor 104 may be or comprise one or more digital signal processors (DSPs), general purpose microprocessors (e.g., Intel Core i3, i5, i7, or i9 processors; Intel Celeron processors; Intel Xeon processors; Intel Pentium processors; AMD Ryzen processors; AMD Athlon processors; AMD Phenom processors; Apple A10 or 10X Fusion processors; Apple Al l, A12, A12X, A12Z, or A13 Bionic processors; or any other general purpose microprocessors), graphics processing units (e.g., Nvidia GeForce RTX 2000-series processors, Nvidia GeForce RTX 3000-series processors, AMD Radeon RX 5000-series processors, AMD Radeon RX 6000-series processors, or any other graphics processing units), application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry.

[0056] The memory 106 may be or comprise RAM, DRAM, SDRAM, other solid-state memory, any memory described herein, or any other tangible, non-transitory memory for storing computer-readable data and/or instructions. The memory 106 may store information or data useful for completing, for example, any step of the method 400 described herein, or of any other methods. The memory 106 may store, for example, instructions and/or machine learning models that support one or more functions of the robot 114. For instance, the memory 106 may store content (e.g., instructions and/or machine learning models) that, when executed by the processor 104, enable image processing 120, segmentation 122, transformation 124, and/or registration 128. Such content, if provided as in instruction, may, in some embodiments, be organized into one or more applications, modules, packages, layers, or engines. Alternatively or additionally, the memory 106 may store other types of content or data (e.g., machine learning models, artificial neural networks, deep neural networks, etc.) that can be processed by the processor 104 to carry out the various method and features described herein. Thus, although various contents of memory 106 may be described as instructions, it should be appreciated that functionality described herein can be achieved through use of instructions, algorithms, and/or machine learning models. The data, algorithms, and/or instructions may cause the processor 104 to manipulate data stored in the memory 106 and/or received from or via the imaging device 112, the robot 114, the database 130, the cloud 134, and/or the NMR profilometer 140.

[0057] The memory 106 may comprise one or more multi-dimensional data models 142. The multi-dimensional data model 142 may be or comprise a multi-dimensional (e.g., 2D, 3D, etc.) depiction of one or more portions of the patient. For example, the multidimensional data model 142 may be or comprise a model of the patient’s head, including the brain. The multi-dimensional data model 142 may be generated using one or more artificial intelligence (Al) or machine learning (ML) models or methods. The Al or ML data models may be or comprise Convolutional Neural Networks (CNNs), Deep Neural Networks (DNNs), classification models, Support Vector Machines (SVMs), etc. that take the preoperative image 144 and/or the intraoperative image 148 as an input and output the multi-dimensional data model 142. In some embodiments, the data models may be trained on historical data sets of similar anatomical elements or structures and/or similar surgeries or surgical procedures to generate the multi-dimensional data model 142. The intraoperative image 148 may be rendered to the display 136 during a portion of or for the duration of the surgery or surgical procedure (e.g., a craniotomy). In some embodiments, the generation may be semiautomatic, with the user capable of modifying the multidimensional data model 142 manually. In other words, the data model may generate the multi-dimensional data model 142, and the user may be able to adjust the position or structure of one or more features depicted in the multi-dimensional data model 142 manually via input in the user interface 110. As discussed below, the multi-dimensional data model 142 may be updated based on scan data generated by the NMR profilometer 140, such as when the computing device 102 determines that the anatomical structure depicted in the multi-dimensional data model 142 has shifted or moved, or that the multidimensional data model 142 is otherwise no longer accurate with respect to the position and/or orientation of the anatomical structure.

[0058] The communication interface 108 may be used for receiving image data or other information from an external source (such as the imaging device 112, the robot 114, the navigation system 118, the database 130, the cloud 134, the NMR profilometer 140, and/or any other system or component not part of the system 100), and/or for transmitting instructions, images, or other information to an external system or device (e.g., another computing device 102, the imaging device 112, the robot 114, the navigation system 118, the database 130, the cloud 134, the NMR profilometer 140, and/or any other system or component not part of the system 100). The communication interface 108 may comprise one or more wired interfaces (e.g., a USB port, an Ethernet port, a Firewire port) and/or one or more wireless transceivers or interfaces (configured, for example, to transmit and/or receive information via one or more wireless communication protocols such as 802.11a/b/g/n, Bluetooth, NFC, ZigBee, and so forth). In some embodiments, the communication interface 108 may be useful for enabling the device 102 to communicate with one or more other processors 104 or computing devices 102, whether to reduce the time needed to accomplish a computing-intensive task or for any other reason. [0059] The computing device 102 may also comprise one or more user interfaces 110. The user interface 110 may be or comprise a keyboard, mouse, trackball, monitor, television, screen, touchscreen, and/or any other device for receiving information from a user and/or for providing information to a user. The user interface 110 may be used, for example, to receive a user selection or other user input regarding any step of any method described herein. Notwithstanding the foregoing, any required input for any step of any method described herein may be generated automatically by the system 100 (e.g., by the processor 104 or another component of the system 100) or received by the system 100 from a source external to the system 100. In some embodiments, the user interface 110 may be useful to allow a surgeon or other user to modify instructions to be executed by the processor 104 according to one or more embodiments of the present disclosure, and/or to modify or adjust a setting of other information displayed on the user interface 110 or corresponding thereto.

[0060] Although the user interface 110 is shown as part of the computing device 102, in some embodiments, the computing device 102 may utilize a user interface 110 that is housed separately from one or more remaining components of the computing device 102. In some embodiments, the user interface 110 may be located proximate one or more other components of the computing device 102, while in other embodiments, the user interface 110 may be located remotely from one or more other components of the computing device 102.

[0061] The imaging device 112 may be operable to image anatomical feature(s) (e.g., a bone, veins, tissue, etc.) and/or other aspects of patient anatomy to yield image data (e.g., image data depicting or corresponding to a bone, veins, tissue, etc.). “Image data” as used herein refers to the data generated or captured by an imaging device 112, including in a machine-readable form, a graphical/visual form, and in any other form. In various examples, the image data may comprise data corresponding to an anatomical feature of a patient, or to a portion thereof. The image data may be or comprise one or more preoperative images 144, one or more intraoperative images 148, one or more postoperative images, or one or more images taken independently of any surgical procedure. In some embodiments, a first imaging device 112 may be used to obtain first image data (e.g., a first image) at a first time, and a second imaging device 112 may be used to obtain second image data (e.g., a second image) at a second time after the first time. The imaging device 112 may be capable of taking a two-dimensional (2D) image or a 3D image to yield the image data. The imaging device 112 may be or comprise, for example, an ultrasound scanner (which may comprise, for example, a physically separate transducer and receiver, or a single ultrasound transceiver), an O-arm, a C-arm, a G-arm, or any other device utilizing X-ray-based imaging (e.g., a fluoroscope, a CT scanner, or other X-ray machine), a magnetic resonance imaging (MRI) scanner, an optical coherence tomography (OCT) scanner, an endoscope, a microscope, an optical camera, a thermographic camera (e.g., an infrared camera), a radar system (which may comprise, for example, a transmitter, a receiver, a processor, and one or more antennae), or any other imaging device 112 suitable for obtaining images of an anatomical feature of a patient. The imaging device 112 may be contained entirely within a single housing, or may comprise a transmitter/emitter and a receiver/ detector that are in separate housings or are otherwise physically separated.

[0062] In some embodiments, the imaging device 112 may comprise more than one imaging device 112. For example, a first imaging device may provide first image data and/or a first image, and a second imaging device may provide second image data and/or a second image. In still other embodiments, the same imaging device may be used to provide both the first image data and the second image data, and/or any other image data described herein. The imaging device 112 may be operable to generate a stream of image data. For example, the imaging device 112 may be configured to operate with an open shutter, or with a shutter that continuously alternates between open and shut so as to capture successive images. For purposes of the present disclosure, unless specified otherwise, image data may be considered to be continuous and/or provided as an image data stream if the image data represents two or more frames per second.

[0063] The robot 114 may be any surgical robot or surgical robotic system. The robot 114 may be or comprise, for example, the Mazor X™ Stealth Edition robotic guidance system. The robot 114 may be configured to position the imaging device 112 at one or more precise position(s) and orientation(s), and/or to return the imaging device 112 to the same position(s) and orientation(s) at a later point in time. The robot 114 may additionally or alternatively be configured to manipulate a surgical tool (whether based on guidance from the navigation system 118 or not) to accomplish or to assist with a surgical task. In some embodiments, the robot 114 may be configured to hold and/or manipulate an anatomical element during or in connection with a surgical procedure. The robot 114 may comprise one or more robotic arms 116. In some embodiments, the robotic arm 116 may comprise a first robotic arm and a second robotic arm, though the robot 114 may comprise more than two robotic arms. In some embodiments, one or more of the robotic arms 116 may be used to hold and/or maneuver the imaging device 112. In embodiments where the imaging device 112 comprises two or more physically separate components (e.g., a transmitter and receiver), one robotic arm 116 may hold one such component, and another robotic arm 116 may hold another such component. Each robotic arm 116 may be positionable independently of the other robotic arm. The robotic arms 116 may be controlled in a single, shared coordinate space, or in separate coordinate spaces.

[0064] The robot 114, together with the robotic arm 116, may have, for example, one, two, three, four, five, six, seven, or more degrees of freedom. Further, the robotic arm 116 may be positioned or positionable in any pose, plane, and/or focal point. The pose includes a position and an orientation. As a result, an imaging device 112, surgical tool, or other object held by the robot 114 (or, more specifically, by the robotic arm 116) may be precisely positionable in one or more needed and specific positions and orientations. The robotic arm(s) 116 may comprise one or more sensors that enable the processor 104 (or a processor of the robot 114) to determine a precise pose in space of the robotic arm (as well as any object or element held by or secured to the robotic arm).

[0065] In some embodiments, reference markers (e.g., navigation markers) may be placed on the robot 114 (including, e.g., on the robotic arm 116), the imaging device 112, or any other object in the surgical space (e.g., on the NMR profilometer 140). The reference markers may be tracked by the navigation system 118, and the results of the tracking may be used by the robot 114 and/or by an operator of the system 100 or any component thereof. In some embodiments, the navigation system 118 can be used to track other components of the system (e.g., imaging device 112, the NMR profilometer 140) and the system can operate without the use of the robot 114 (e.g., with the surgeon manually manipulating the imaging device 112, the NMR profilometer 140, sand/or one or more surgical tools, based on information and/or instructions generated by the navigation system 118, for example).

[0066] The navigation system 118 may provide navigation for a surgeon and/or a surgical robot during an operation. The navigation system 118 may be any now-known or future-developed navigation system, including, for example, the Medtronic Stealth StationTM S8 surgical navigation system or any successor thereof. The navigation system 118 may include one or more cameras or other sensor(s) for tracking one or more reference markers, navigated trackers, or other objects within the operating room or other room in which some or all of the system 100 is located. The one or more cameras may be optical cameras, infrared cameras, or other cameras. In some embodiments, the navigation system 118 may comprise one or more electromagnetic sensors. In various embodiments, the navigation system 118 may be used to track a position and orientation (e.g., a pose) of the imaging device 112, the robot 114 and/or robotic arm 116, and/or one or more surgical tools (or, more particularly, to track a pose of a navigated tracker attached, directly or indirectly, in fixed relation to the one or more of the foregoing). The navigation system 118 may include a display for displaying one or more images from an external source (e.g., the computing device 102, imaging device 112, or other source) or for displaying an image and/or video stream from the one or more cameras or other sensors of the navigation system 118. The navigation system 118 may be configured to provide guidance to a surgeon or other user of the system 100 or a component thereof, to the robot 114, or to any other element of the system 100 regarding, for example, a pose of one or more anatomical elements, whether or not a tool is in the proper trajectory, and/or how to move a tool into the proper trajectory to carry out a surgical task according to a preoperative or other surgical plan.

[0067] The database 130 may store information that correlates one coordinate system to another (e.g., one or more robotic coordinate systems to a patient coordinate system and/or to a navigation coordinate system). The database 130 may additionally or alternatively store, for example, one or more surgical plans (including, for example, pose information about a target and/or image information about a patient’s anatomy at and/or proximate the surgical site, for use by the robot 114, the navigation system 118, and/or a user of the computing device 102 or of the system 100); one or more images useful in connection with a surgery to be completed by or with the assistance of one or more other components of the system 100 (e.g., the preoperative images 144, the intraoperative images 148, etc.); threshold value information (e.g., threshold values for use in comparison to a difference between the depicted location of an anatomical structure based on a multi-dimensional model and a determined location of the anatomical structure based on data generated by the NMR profilometer 140); and/or any other useful information. The database 130 may be configured to provide any such information to the computing device 102 or to any other device of the system 100 or external to the system 100, whether directly or via the cloud 134. In some embodiments, the database 130 may be or comprise part of a hospital image storage system, such as a picture archiving and communication system (PACS), a health information system (HIS), and/or another system for collecting, storing, managing, and/or transmitting electronic medical records including image data. [0068] The cloud 134 may be or represent the Internet or any other wide area network. The computing device 102, the robot 114, the navigation system 118, the database 130, the display 136, and/or the NMR profilometer 140 may be connected to the cloud 134 via the communication interface 108, using a wired connection, a wireless connection, or both. In some embodiments, the computing device 102 may communicate with the database 130, the display 136, the NMR profilometer 140 and/or an external device (e.g., a computing device) via the cloud 134.

[0069] The display 136 may be connected to or included in one or more components of the system 100. The display 136 is configured to display data such as various views of one or more images, surgical information, surgical plans, scan data generated by the NMR profilometer 140, multi-dimensional data model(s) 142, preoperative image(s) 144, intraoperative image(s) 148, combinations thereof, and/or the like from an external source (e.g., the computing device 102, the imaging device 112, or other source) or to display an image and/or video stream from one or more cameras or other sensors of the imaging device 112, the navigation system 118, and/or the like. In some embodiments, the display 136 may be similar to or the same as the user interface 110, and may communicate with one or more other components of the system 100 (e.g., via the communication interface 108, via the cloud 134, etc.). The display 136 may be configured to display additional data, such as a pose of one or more anatomical elements, whether or not a tool is in the proper trajectory, how to move a tool into the proper trajectory to carry out a surgical task according to a preoperative or other surgical plan, visual depictions of one or more objects in the surgical environment, combinations thereof, and/or the like.

[0070] The NMR profilometer 140 may be or comprise a device capable of delivering radiofrequency (RF) energy to a surgical site and detecting NMR responses of objects within the surgical site (e.g., anatomical tissues such as skin, brain tissue, CSF, etc.). The NMR profilometer 140 comprises a magnet and a tunable RF coil. The magnet may be a single-sided magnet (e.g., a magnet with magnetic poles emerging from the same side of the magnet) that generates a static magnetic field. Examples of the magnet include, but are in no way limited to, a permanent magnet, an electromagnet, a superconducting magnet, combinations thereof, and/or the like. The tunable RF coil may comprise one or more exciting coils that emit RF energy as well as one or more receiving coils that record excitation signals generated by objects within the surgical site in response to the delivered RF energy. The NMR profilometer 140 may be adjustable to generate RF energy at various frequencies (e.g., 1 Megahertz (MHz), 2 MHz, 3 MHz, etc.). The various frequencies may be used to account for the drop off of magnetic field strength over distance. In other words, the frequency of RF energy output by the NMR profilometer 140 may be changed to excite the anatomical tissues in the surgical site at different depths. In some embodiments, the various frequencies may be applied while the NMR profilometer 140 remains stationary, such that NMR response signals can be recorded to generate a depth profile (e.g., an amplitude of the response signal as a function of depth or distance away from the NMR profilometer 140).

[0071] In some embodiments, the NMR profilometer 140 may be used to generate ID depth data for the skull of a patient. The NMR profilometer 140 may be positioned proximate the patient’s head, and may emit RF energy that excites protons of anatomical tissues at various depths in the patient’s head. For example, the magnetic field generated by the NMR profilometer 140 may excite protons in the patient’s skin, brain, skull, CSF, etc., each of which may in turn generate response signals that are captured by the NMR profilometer 140. The frequency of the RF coil may be adjusted (e.g., increased or decreased) over a range of frequencies to generate the ID depth profile that depicts the response signal amplitude as a function of depth. In cases when the brain or other anatomical structures of the patient have shifted, such a shift may be depicted in the ID depth profile, enabling a user or the computing device 102 (e.g., using Al or ML models) to identify the shift and adjust the surgery or surgical procedure accordingly, as discussed in further detail below. The shifting of the brain or other anatomical structures in the patient may be caused by or due to one or more factors or conditions, for example due to the draining the CSF of the patient, due to gravity, due to osmotic conditions driven by intraoperative drugs/osmotic agents administered to the patient, due to tissue response (e.g., swelling), due to surgical resection, combinations thereof, and/or the like.

[0072] The system 100 or similar systems may be used, for example, to carry out one or more aspects of the method 400 described herein. The system 100 or similar systems may also be used for other purposes.

[0073] With reference to Fig. 2, aspects of the NMR profilometer 140 interacting with a patient 208 are shown in accordance with embodiments of the present disclosure. The NMR profilometer 140 may be positioned relative to the brain 212 of the patient 208, such that the NMR profilometer 140 can generate RF energy at a plurality of frequencies 216A- 216C. For example, the NMR profilometer 140 may generate RF energy at a first frequency 216A (e.g., a frequency at 3 MHz), a second frequency 216B (e.g., a frequency of 2 MHz), and a third frequency 216C (e.g., a frequency at 1 MHz). The NMR profilometer 140 may emit RF energy at additional or alternative frequencies. As previously noted, such frequencies may enable the NMR profilometer 140 to stimulate proton response at various depths below the NMR profilometer 140. For example, the outer skin of the patient 208 may be induced by the first frequency 216A and generate a response that is recorded by the NMR profilometer 140. Then, the NMR profilometer 140 may be adjusted to the second frequency 216B, which may induce a response from a deeper layer of anatomical tissue, such as the skull of the patient. The induced response of the protons in the skull may also be recorded by the NMR profilometer 140. Such a process of adjusting frequencies and recording induced responses may be repeated for a plurality of frequencies, such that the data collected by the NMR profilometer 140 can be converted into a depth profile that depicts the response amplitude of various anatomical tissues as a function of depth. The frequencies may be automatically adjusted by the processor 104 after the processor 104 receives the proton response (e.g., after receiving a response signal from the NMR profilometer 140 for the first frequency 216A, the processor 104 may automatically adjust the frequency of the NMR profilometer 140 to the second frequency 216B), or may be manually set by the user (e.g., a surgeon) based on inputs into the user interface 110. In some embodiments, the NMR profilometer 140 produces a uniform magnetic field. In other words, the NMR profilometer 140 generates a magnetic field at a fixed resonance frequency (e.g., at 3 MHz). The use of the uniform magnetic field may beneficially omit the need to generate additional RF frequencies to produce a ID depth profile. In such embodiments, the NMR profilometer 140 comprises an additional gradient coil that generates a time varying gradient field. The gradient field may modulate the uniform magnetic field in a predicable or known manner, such that the response frequency of the protons varies as a function of position, which in turn enables the NMR profilometer 140 to encode the spatial location of the protons for the purposes of generating a ID depth profile.

[0074] The NMR profilometer 140 may comprise a navigation tracker 204. The navigation tracker 204 may comprise fiducial markers (e.g., navigation markers) or other indicators that enable a navigation camera of the navigation system 118 to track the pose (e.g., position and orientation) of the NMR profilometer 140 as the NMR profilometer 140 moves relative to the patient 208. For example, the NMR profilometer 140 may be moved (e.g., using the robotic arm 116, manually by a user, etc.) around the brain 212 of the patient 208 to generate ID depth data associated with the excitation response of anatomical tissues disposed below the NMR profilometer 140. In one embodiment, the NMR profilometer 140 may be portable, handheld, or otherwise capable of being navigated by a user without the assistance of the robotic arm 116. In such an embodiment, the user may move the NMR profilometer 140 along various portions of the patient 208 to generate depth profiles at various points of the patient 208. As the user or robot 114 maneuvers the NMR profilometer 140, a navigation camera of the navigation system 118 may identify and track the navigation tracker 204, such that the navigation system 118 can determine a pose of the NMR profilometer 140 in a known coordinate system as the NMR profilometer 140 is moved relative to the patient 208. In some cases, the navigation system 118 may provide such information to the computing device 102, which may use the pose of the NMR profilometer 140 along with the depth profiles generated by the NMR profilometer 140 to determine the position of the brain 212.

[0075] With reference to Figs. 3 A-3B, ideal depth profiles generated based on the NMR profilometer 140 measurements are shown in accordance with embodiments of the present disclosure. The ideal depth profiles may be or comprise scan data that reflect the measured amplitude of the proton response signal to the NMR profilometer 140 as a function of depth. The ideal depth profile in Fig. 3 A may correspond to the ideal signal data before a craniotomy, while the ideal depth profile in Fig. 3B may correspond to the ideal signal data after a craniotomy. Each of the ideal depth profiles comprises data that reflect the presence of a plurality of layers in, for example, the head of the patient 208, with each layer corresponding to the a different material excited by the RF energy generated by the NMR profilometer 140. Each layer may be a different material with different relaxation properties (which is reflected in the different signal amplitudes). For example, one or more sections of the signal may correspond to air (as shown by section 304), skin (as shown by section 308), the patient’s skull (as shown by section 312), CSF (as shown by section 316), and brain tissue (as shown by section 320) at increasing depths.

[0076] After the CSF has been drained during, for example, a craniotomy, the signal data may indicate that there is an air gap between the patient’s skull and the brain tissue. As depicted in Fig. 3B, an air gap (as shown by section 324) may be measured between the section 312 (corresponding to the patient’s skull) and the section 320 (corresponding to brain tissue). The section 324 may be identifiable in the scan data, and may be used to identify a new location of the patient’s brain. For example, based on the width of the section 324 (e.g., ranging from about 15 mm to about 20 mm in depth), the computing device 102 may be able to determine relative movement of the brain. In some examples, the NMR profilometer 140 may be passed over the patient 208 in multiple locations, such that multiple depth profiles are generated. Based on the readings and the various presence or absence of air gaps at various depths, the computing device 102 may be able to determine (e.g., using Al or ML models, using transformation 124 in combination with data provided by the navigation system 118, etc.) the location of the brain. The location of the brain may then be compared with the depicting location of the brain (e.g., depicted in the multi-dimensional data model 142) and, in the event a difference between the two meets or exceeds a threshold value, the multi-dimensional data model 142 may be updated to more accurately depict the position of the brain, as discussed in further detail below. [0077] Fig. 4 depicts a method 400 that may be used, for example, to adjust an image or model depicting an anatomical structure (e.g., a patient’s brain) based on NMR profilometer measurements.

[0078] The method 400 (and/or one or more steps thereof) may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as or similar to the processor(s) 104 of the computing device 102 described above. The at least one processor may be part of a robot (such as a robot 114) or part of a navigation system (such as a navigation system 118). A processor other than any processor described herein may also be used to execute the method 400. The at least one processor may perform the method 400 by executing elements stored in a memory such as the memory 106. The elements stored in memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 400. One or more portions of a method 400 may be performed by the processor executing any of the contents of memory, such as an image processing 120, a segmentation 122, a transformation 124, and/or a registration 128.

[0079] The method 400 comprises receiving scan data associated with a Nuclear Magnetic Resonance (NMR) profilometer scan of an anatomical structure (step 404). The NMR profilometer may be similar to or the same as the NMR profilometer 140. The anatomical structure may comprise any one or more portions of patient anatomy, such as the brain of the patient. The scan data may be generated by the NMR profilometer 140 at a variety of frequencies, such that the scan data comprises ID depth data. In some embodiments, the NMR profilometer 140 may comprise the navigation tracker 204 such that, as the NMR profilometer 140 is moved (e.g., by a user, by the robotic arm 116, etc.), the pose of the robot 114 is tracked and known to the navigation system 118. In some embodiments, the scan data may comprise a plurality of ID depth profiles. In other words, the scan data may comprise a depth profile generated by the NMR profilometer 140 when the NMR profilometer 140 is in a first pose, a depth profile generated by the NMR profilometer 140 when the NMR profilometer 140 is in a second pose, etc. In some embodiments, the scan data may be generated (e.g., the NMR profilometer 140 may be used) at a plurality of different steps in the surgery or surgical procedure. For example, the scan data may comprise information generated by the NMR profilometer 140 both before and after a craniotomy. In this example, the NMR profilometer 140 may be positioned in similar or the same poses for generating the NMR response data both before and after the craniotomy. The scan data may be sent to one or more components of the system 100 (e.g., to the computing device 102, to the memory 106, to the database 130) or to one or more components external to the system 100. In some embodiments, the scan data may be stored in the database 130 for later use.

[0080] The method 400 also comprises determining, based on the scan data and tracking of the NMR profilometer, a location of the anatomical structure (step 408). The computing device 102 may use the ID depth profile(s) and navigation information from the navigation system 118 to determine the position of the anatomical structure (e.g., the brain of the patient). The computing device 102 may use transformation 124 to determine, based on the pose of the NMR profilometer 140 and the location of, for example, air gaps in the ID depth profiles, a position of the anatomical structure. For example, a first ID depth profile taken before a craniotomy may indicate that there is a 5 millimeter (mm)-thick layer CSF between the skull and the brain. After the craniotomy a second ID depth profile, generated by the NMR profilometer 140 at the same pose as to generate the first ID depth profile, may indicate that the CSF has been replaced with a 7 millimeter (mm) air gap. The computing device 102 may determine from this information that the brain has thus shifted 2 mm in the direction in which the magnetic field of the NMR profilometer 140 was propagated. The computing device 102 may perform such determinations for the remaining ID depth profiles, and determine an overall movement of the brain as a result of the craniotomy. Then, the computing device 102 may use transformation 124 to determine, based on the movement and the known pose of the NMR profilometer 140 at various locations, the location of the brain. In some embodiments, the computing device 102 may use one or more Al or ML models, which may take the scan data and the pose of the NMR profilometer 140 when generating the scan data as inputs and output the position of the anatomical structure. In some embodiments, the Al or ML models may be trained on historical data of similar surgeries or surgical procedures.

[0081] The method 400 also comprises determining a difference between the determined location of the anatomical structure and a depicted location of the anatomical structure in a multi-dimensional model (step 412). The determined location of the anatomical element from the step 408 may be compared with a location of the anatomical structure depicted in the multi-dimensional model, (which may be similar to or the same as the multidimensional data model 142) to determine a difference therebetween. The multidimensional data model 142 may be based on preoperative images 144 and/or intraoperative images 148 of the patient. The difference may be a value reflecting the overall difference in location between the determined location and the depicted location. The difference may be or comprise a percent difference (e.g., a relative change of the determined location from the depicted location), a percentage overlap (e.g., an amount of area or volume shared by the model of the anatomical structure with a model representative of the determined location), combinations thereof, and/or the like. Additionally or alternatively, the determined location may be compared to a depicted location of the preoperative image 144, and a value indicative of the difference between the two may be generated. In other words, the determined location of the anatomical structure may be compared with the multi-dimensional data model 142 and/or the preoperative image 144 to determine a difference between the determined location of the anatomical structure and the location of the anatomical structure as depicted by the multidimensional data model 142 and/or the preoperative image 144.

[0082] The method 400 also comprises comparing the difference to a threshold value (step 416). The threshold value may be stored in the database 130. The comparison may comprise determining whether a value associated with the difference is greater than, less than, or equal to the threshold value. The threshold value may be or comprise a value above which the determined location of the anatomical structure is considered to have moved relative to the previously known location of the anatomical structure. In other words, if the difference meets or exceeds the threshold value, the computing device 102 may treat the anatomical structure as having moved. For example, the threshold value may be 0.1%, which may specify that the anatomical structure is considered to have moved if the difference between the determined location of the anatomical structure and the location of the anatomical structure as provided by the multi-dimensional data model 142 and/or the preoperative image 144 is equal to or greater than 0.1%. Stated differently, the computing device 102 may treat the anatomical structure as having not moved if the difference value falls below 0.1% (even if the anatomical structure may have experienced some movement). In some embodiments, the threshold value may be based on safety tolerances of the system 100. For example, the threshold value may reflect a safety tolerance that movements at or above the threshold value constitute a sufficient movement in the anatomical structure to warrant adjustments to the surgical plan, the multidimensional data model 142, and/or the preoperative image 144. In some embodiments, the threshold value may be user-defined (e.g., input or selected by the physician prior to or during the surgery or surgical procedure).

[0083] The method 400 also comprises updating, when the difference meets or exceeds the threshold value, the multi-dimensional model to reduce the difference (step 420). When the difference meets or exceeds the threshold value, the computing device 102 may use one or more Al or ML models to adjust the multi-dimensional data model 142 and/or the preoperative image 144 to account for the difference. The Al or ML models may take the multi-dimensional data model 142 and/or the preoperative image 144, as well as the difference value, and output an updated model or image. In some embodiments, the Al or ML models may use the difference to generate a 3D vector field (e.g., a displacement field) indicative of the difference that is then applied to the multi-dimensional data model 142 and/or the preoperative image 144 to shift, rearrange, or otherwise adjust data associated with the multi-dimensional data model 142 and/or the preoperative image 144 to reduce the difference. Stated differently, the Al or ML model may generate a 3D vector field that alters the multi-dimensional data model 142 and/or the preoperative image 144 to more closely reflect the location of the anatomical structure determined based on the ID depth profiles. In some embodiments, the multi-dimensional data model 142 and/or the preoperative image 144 may be iteratively updated until the position depicted in the multidimensional data model 142 and/or the preoperative image 144 converge (e.g., within a predetermined and/or threshold distance) to the determined location.

[0084] Additionally or alternatively, the computing device 102 may use transformation 124 to transform the multi-dimensional data model 142 and/or the preoperative image 144. For example, the computing device 102 may use the determined location of the anatomical structure to generate, using transformation 124, mathematical operations (e.g., matrix transformations) that can be applied to the data of the multi-dimensional data model 142 and/or the preoperative image 144 to transform the data into the determined location. In some embodiments, the output of the updated multi-dimensional data model 142 and/or preoperative image 144 may be editable, such that the user (e.g., a surgeon) can adjust, update, or otherwise alter the data presented in the updated model or image. The user may make such changes through inputs via the user interface 110. [0085] The method 400 also comprises rendering, to the display, the updated multidimensional model and/or the scan data (step 424). The updated multi-dimensional model and/or the scan data may be rendered to a display, which may be similar to or the same as the display 136. In examples where the preoperative image 144 is additionally or alternatively updated, the updated preoperative image 144 may also be rendered to the display. In some embodiments, the method 400 may repeat. For example, the method 400 may repeat any time the NMR profilometer 140 is used to collect additional scan data, such as after the patient has moved, when the user desires to collect additional scan data (e.g., the surgeon believes the patient’s brain has moved again, the surgeon prefers to capture scan data after each step of the surgery or surgical procedure, etc.).

[0086] The present disclosure encompasses embodiments of the method 400 that comprise more or fewer steps than those described above, and/or one or more steps that are different than the steps described above.

[0087] As noted above, the present disclosure encompasses methods with fewer than all of the steps identified in Fig. 4 (and the corresponding description of the method 400), as well as methods that include additional steps beyond those identified in Fig. 4 (and the corresponding description of the method 400). The present disclosure also encompasses methods that comprise one or more steps from one method described herein, and one or more steps from another method described herein. Any correlation described herein may be or comprise a registration or any other correlation.

[0088] The foregoing is not intended to limit the disclosure to the form or forms disclosed herein. In the foregoing Detailed Description, for example, various features of the disclosure are grouped together in one or more aspects, embodiments, and/or configurations for the purpose of streamlining the disclosure. The features of the aspects, embodiments, and/or configurations of the disclosure may be combined in alternate aspects, embodiments, and/or configurations other than those discussed above. This method of disclosure is not to be interpreted as reflecting an intention that the claims require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed aspect, embodiment, and/or configuration. Thus, the following claims are hereby incorporated into this Detailed Description, with each claim standing on its own as a separate preferred embodiment of the disclosure.

[0089] Moreover, though the foregoing has included description of one or more aspects, embodiments, and/or configurations and certain variations and modifications, other variations, combinations, and modifications are within the scope of the disclosure, e.g., as may be within the skill and knowledge of those in the art, after understanding the present disclosure. It is intended to obtain rights which include alternative aspects, embodiments, and/or configurations to the extent permitted, including alternate, interchangeable and/or equivalent structures, functions, ranges or steps to those claimed, whether or not such alternate, interchangeable and/or equivalent structures, functions, ranges or steps are disclosed herein, and without intending to publicly dedicate any patentable subject matter. [0090] A set of example statements are provided below:

[0091] Statement 1. A method, comprising: receiving scan data associated with a Nuclear Magnetic Resonance (NMR) profilometer (140) scan of an anatomical structure; determining, based on the scan data and tracking of the NMR profilometer (1 0), a location of the anatomical structure; determining a difference between the determined location of the anatomical structure and a depicted location of the anatomical structure in a multi-dimensional model (142); comparing the difference to a threshold value; and updating, when the difference meets or exceeds the threshold value, the multi-dimensional model (142) to reduce the difference.

[0092] Statement 2: The method of Statement 1, wherein the scan data comprises onedimensional (ID) depth data.

[0093] Statement 3: The method of any of Statements 1-2, wherein the multidimensional model (142) is based on at least one of a preoperative image (144) of the anatomical structure and an intraoperative image (148) of the anatomical structure.

[0094] Statement 4: The method of any of Statements 1-3, further comprising:

[0095] rendering, to a display (136), at least one of the updated multi-dimensional model (142) and the scan data.

[0096] Statement 5: The method of any of Statements 1-4, wherein the updating of the multi-dimensional model (142) is performed by an Artificial Intelligence (Al) model.

[0097] Statement 6: The method of any of Statements 1-5, wherein the NMR profilometer (140) comprises a plurality of navigation markers.

[0098] Statement 7: The method of any of Statements 1-6, wherein the NMR profilometer (140) comprises a magnet and a tunable radiofrequency (RF) coil.

[0099] Statement 8: The method of any of Statements 1-7, wherein a navigation system navigates a surgical tool based on the updated multi-dimensional model (142).

[0100] Statement 9: A system, comprising: a processor (104); and a memory (106) storing data thereon that, when processed by the processor (104), enable the processor (104) to: receive scan data associated with a Nuclear Magnetic Resonance (NMR) profilometer (140) scan of an anatomical structure; determine, based on the scan data and tracking of the NMR profilometer (140), a location of the anatomical structure; determine a difference between the determined location of the anatomical structure and a depicted location of the anatomical structure in a multi-dimensional model (142); compare the difference to a threshold value; and update, when the difference meets or exceeds the threshold value, the multi-dimensional model (142) to reduce a value of the difference. [0101] Statement 10: The system of Statement 9, wherein the scan data comprises onedimensional (ID) depth data.

[0102] Statement 11 : The system of any of Statements 9-10, wherein the multidimensional model (142) is based on at least one of a preoperative image (144) of the anatomical structure and an intraoperative image (148) of the anatomical structure.

[0103] Statement 12: The system of any of Statements 9-11, wherein the data, when processed by the processor (104), further enable the processor (104) to: render, to a display (136), at least one of the updated multi-dimensional model (142) and the scan data. [0104] Statement 13: The system of any of Statements 9-12, wherein the updating of the multi-dimensional model (142) is performed by an Artificial Intelligence (Al) model. [0105] Statement 14: The system of any of Statements 9-13, wherein the NMR profilometer (140) comprises a plurality of navigation markers.

[0106] Statement 15: The system of any of Statements 9-14, wherein the NMR profilometer (140) comprises a magnet and a tunable radiofrequency (RF) coil.

[0107] Statement 16: The system of any of Statements 9-15, wherein a navigation system navigates a surgical tool based on the updated multi-dimensional model (142). [0108] Statement 17: A system, comprising: a Nuclear Magnetic Resonance (NMR) profilometer (140); a processor (104); and a memory (106) storing data thereon that, when processed by the processor (104), enable the processor (104) to: receive scan data associated with a scan performed by the NMR profilometer (140) of an anatomical structure; determine, based on the scan data and tracking of the NMR profilometer (140), a location of the anatomical structure; compare the determined location of the anatomical structure with a depicted location of the anatomical structure in a multi-dimensional model (142) to generate a value indicative of a difference between the determined location and the depicted location; compare the value indicative of the difference to a threshold value; and update, when the value indicative of the difference meets or exceeds the threshold value, the multi-dimensional model (142) to reduce the value of the difference. [0109] Statement 18: The system of Statement 17, wherein the scan data comprises onedimensional (ID) depth data.

[0110] Statement 19: The system of any of Statements 17-18, wherein the data, when processed by the processor (104), further enable the processor (104) to: render, to a display (136), at least one of the updated multi-dimensional model (142) and the scan data.

[OHl] Statement 20: The system of any of Statements 17-19, wherein the updating of the multi-dimensional model (142) is performed by an Artificial Intelligence (Al) model.

Claims

CLAIMS What is claimed is:

1. A method, comprising: receiving scan data associated with a Nuclear Magnetic Resonance (NMR) profilometer (140) scan of an anatomical structure; determining, based on the scan data and tracking of the NMR profilometer (1 0), a location of the anatomical structure; determining a difference between the determined location of the anatomical structure and a depicted location of the anatomical structure in a multi-dimensional model (142); comparing the difference to a threshold value; and updating, when the difference meets or exceeds the threshold value, the multidimensional model (142) to reduce the difference.

2. The method of claim 1, wherein the scan data comprises one-dimensional (ID) depth data.

3. The method of any of claims 1-2, wherein the multi-dimensional model (142) is based on at least one of a preoperative image (144) of the anatomical structure and an intraoperative image (148) of the anatomical structure.

4. The method of any of claims 1-3, further comprising: rendering, to a display (136), at least one of the updated multi-dimensional model (142) and the scan data.

5. The method of any of claims 1-4, wherein the updating of the multidimensional model (142) is performed by an Artificial Intelligence (Al) model.

6. The method of any of claims 1-5, wherein the NMR profilometer (140) comprises a plurality of navigation markers.

7. The method of any of claims 1-6, wherein the NMR profilometer (140) comprises a magnet and a tunable radiofrequency (RF) coil.

8. The method of any of claims 1-7, wherein a navigation system navigates a surgical tool based on the updated multi-dimensional model (142).

9. A system, comprising: a processor (104); and a memory (106) storing data thereon that, when processed by the processor (104), enable the processor (104) to: receive scan data associated with a Nuclear Magnetic Resonance (NMR) profilometer (140) scan of an anatomical structure; determine, based on the scan data and tracking of the NMR profilometer (140), a location of the anatomical structure; determine a difference between the determined location of the anatomical structure and a depicted location of the anatomical structure in a multi-dimensional model (142); compare the difference to a threshold value; and update, when the difference meets or exceeds the threshold value, the multi-dimensional model (142) to reduce a value of the difference.

10. The system of claim 9, wherein the scan data comprises one-dimensional (ID) depth data.

11. The system of any of claims 9-10, wherein the multi-dimensional model (142) is based on at least one of a preoperative image (144) of the anatomical structure and an intraoperative image (148) of the anatomical structure.

12. The system of any of claims 9-11, wherein the data, when processed by the processor (104), further enable the processor (104) to: render, to a display (136), at least one of the updated multi-dimensional model (142) and the scan data.

13. The system of any of claims 9-12, wherein the updating of the multidimensional model (142) is performed by an Artificial Intelligence (Al) model.

14. The system of any of claims 9-13, wherein the NMR profilometer (140) comprises a plurality of navigation markers, a magnet, and a tunable radiofrequency (RF) coil.

15. A system, comprising: a Nuclear Magnetic Resonance (NMR) profilometer (140); a processor (104); and a memory (106) storing data thereon that, when processed by the processor (104), enable the processor (104) to: receive scan data associated with a scan performed by the NMR profilometer (140) of an anatomical structure; determine, based on the scan data and tracking of the NMR profilometer (140), a location of the anatomical structure; compare the determined location of the anatomical structure with a depicted location of the anatomical structure in a multi-dimensional model (142) to generate a value indicative of a difference between the determined location and the depicted location; compare the value indicative of the difference to a threshold value; and update, when the value indicative of the difference meets or exceeds the threshold value, the multi-dimensional model (142) to reduce the value of the difference.