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WO2025221620A1 - Systèmes et procédés de fusion de tomodensitométrie - Google Patents

Systèmes et procédés de fusion de tomodensitométrie

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Publication number
WO2025221620A1
WO2025221620A1 PCT/US2025/024389 US2025024389W WO2025221620A1 WO 2025221620 A1 WO2025221620 A1 WO 2025221620A1 US 2025024389 W US2025024389 W US 2025024389W WO 2025221620 A1 WO2025221620 A1 WO 2025221620A1
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WO
WIPO (PCT)
Prior art keywords
vasculature structure
representation
beacon
motion
patient
Prior art date
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Pending
Application number
PCT/US2025/024389
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English (en)
Inventor
Jeffery DECH
Erik E. Anderson
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Cloudnav Inc
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Cloudnav Inc
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Publication date
Application filed by Cloudnav Inc filed Critical Cloudnav Inc
Publication of WO2025221620A1 publication Critical patent/WO2025221620A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/50—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications
    • A61B6/503—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications for diagnosis of the heart
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/20—Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/48—Diagnostic techniques
    • A61B6/486—Diagnostic techniques involving generating temporal series of image data
    • A61B6/487—Diagnostic techniques involving generating temporal series of image data involving fluoroscopy
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
    • A61B6/5211—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data
    • A61B6/5229—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data combining image data of a patient, e.g. combining a functional image with an anatomical image
    • A61B6/5235—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data combining image data of a patient, e.g. combining a functional image with an anatomical image combining images from the same or different ionising radiation imaging techniques, e.g. PET and CT
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/44—Constructional features of apparatus for radiation diagnosis
    • A61B6/4429—Constructional features of apparatus for radiation diagnosis related to the mounting of source units and detector units
    • A61B6/4435—Constructional features of apparatus for radiation diagnosis related to the mounting of source units and detector units the source unit and the detector unit being coupled by a rigid structure
    • A61B6/4441—Constructional features of apparatus for radiation diagnosis related to the mounting of source units and detector units the source unit and the detector unit being coupled by a rigid structure the rigid structure being a C-arm or U-arm

Definitions

  • a computed tomography scan is a medical imaging technique used to obtain detailed internal images of the body.
  • CT scanners use a rotating X-ray tube and a row of detectors placed in a gantry to measure X-ray attenuations by different tissues inside the body.
  • the multiple X-ray measurements taken from different angles are then processed on a computer using tomographic reconstruction algorithms to produce tomographic (cross-sectional) images of a body.
  • CT scan can be used in patients with metallic implants or pacemakers.
  • SUMMARY Devices, systems, and methods for generating a guidance map to aid in the in situ navigation of invasive medical devices incorporating positioning beacons are described.
  • a system for determining a representation of a vasculature structure of a patient includes at least one beacon, an array of magnetic sensors, external to the patient, configured to sense the at least one beacon integrated into an invasive medical device, and at least one processor.
  • the at least one processor is configured to determine a location of the at least one beacon in the vasculature structure, generate a two-dimensional (2D) International Application Attorney Docket No.: 123178.8008.WO00 projection of the vasculature structure based on the location, a previously obtained representation of the vasculature structure, and an output image from a live X-ray device, determine, using motion information from the at least one beacon, a motion or position of the vasculature structure relative to the output image from of the live X-ray device, generate, based on combining the 2D projection and the motion or position of the vasculature structure, the representation of the vasculature structure, and track, based on the representation of the vasculature structure, a location of the invasive medical device in the vasculature structure.
  • 2D two-dimensional
  • a method for determining a representation of a vasculature structure of a patient includes determining a location of at least one beacon, which is removably affixed to a medical device, in the vasculature structure of the patient. The method further includes generating a two-dimensional (2D) projection of the vasculature structure based on the location, a previously obtained representation of the vasculature structure, and an output image from a live X-ray device, and determining, using motion information from the at least one beacon, a motion or position of the vasculature structure relative to the output image from of the live X-ray device.
  • 2D two-dimensional
  • the method then combines the 2D projection and the motion or position of the vasculature structure to generate the representation of the vasculature structure, and tracks, based on the representation, a location of the medical device in the vasculature structure.
  • the above-described method may be implemented by an apparatus or device that includes a processor and/or memory.
  • this method may be embodied in the form of processor-executable instructions and stored on a computer-readable program medium.
  • the subject matter described in this patent document can be implemented in specific ways that provide one or more of the following features. BRIEF DESCRIPTION OF THE DRAWINGS [0010] FIG.
  • FIG. 1 illustrates an example of an arterial vasculature, imaged under X-ray, using a contrast agent.
  • FIG. 2 illustrates an example embodiment of a system for incorporating a previously generated representation of the regions of interest of the cardiac vasculature and overlaying it atop a live X-ray image.
  • FIG. 3 is a flow diagram describing an example method for determining the relative International Application Attorney Docket No.: 123178.8008.WO00 location and orientation of a previously generated representation of the regions of interest of the cardiac vasculature relative to a second two-dimensional image.
  • FIG. 4 illustrates an example of the placement of beacons on an invasive medical device within a patient’s heart.
  • FIG. 4 illustrates an example of the placement of beacons on an invasive medical device within a patient’s heart.
  • FIG. 5A illustrates an example embodiment of a beacon, which includes a permanent magnet, integrated into an invasive medical device.
  • FIG. 5B illustrates an example embodiment of a beacon, which includes an electromagnet, integrated into an invasive medical device.
  • FIG. 5C illustrates an example embodiment of a beacon, which includes both an electromagnet and a permanent magnet, integrated into an invasive medical device.
  • FIG. 6 illustrates an example embodiment of an array of sensors capable of sensing beacons incorporated into an invasive medical device.
  • FIG. 7 is a flow diagram for an example method for magnet localization using a single magnet.
  • FIG. 8 is a flow diagram for an example refinement process used in magnet localization.
  • FIGS. 9A–9C illustrate examples of X-axis, Y-axis, and Z-axis motion, respectively, for a beacon.
  • FIGS. 10A and 10B illustrate examples of azimuthal angle motion and elevation angle motion, respectively, for a beacon.
  • FIG. 11 is a flow diagram for an example static registration method.
  • FIG. 12 illustrates an example of generating a mask of heart vasculature.
  • FIG. 13 illustrates an example of Z-axis motion due to breathing.
  • FIG. 14 illustrates an example of heart rotational motion direction due to beating.
  • FIG. 15 illustrates an example of heart rotational angle due to beating. [0027] FIG.
  • FIG. 16 is a flow diagram for an example method to determine the heart rotational direction and angle parameters.
  • FIG. 17 is a flow diagram for an example method to determine the deformation parameters for dynamic registration.
  • FIG. 18 illustrates an example of projective view rendering.
  • FIG. 19A illustrates an example of a three-dimensional representation of a patient International Application Attorney Docket No.: 123178.8008.WO00 heart.
  • FIG. 19B illustrates an example of a two-dimensional X-ray view of a patient heart.
  • FIG. 19C illustrates an example of the correspondence between key points in a two- dimensional rendering of a three-dimensional representation and the live X-ray image.
  • FIG. 19A illustrates an example of a three-dimensional representation of a patient International Application Attorney Docket No.: 123178.8008.WO00 heart.
  • FIG. 19B illustrates an example of a two-dimensional X-ray view of a patient heart.
  • FIG. 19C illustrates an example of the correspondence between key points in
  • FIG. 20A illustrates an example of dynamic motion and deformation correction of a three-dimensional representation to match the two-dimensional X-ray view of a patient heart.
  • FIG. 20B illustrates an example of registration and overlay of a corrected three- dimensional representation over top of a two-dimensional X-ray view of a patient heart .
  • FIG. 20C illustrates an example of the correspondence between key points in a two- dimensional rendering of a deformed three-dimensional representation and the live X-ray image.
  • FIG. 21 illustrates a flowchart of an example method for determining a representation of a vasculature structure of a patient.
  • FIG. 22 is a block diagram illustrating an example system configured to implement embodiments of the disclosed technology.
  • Cardiovascular disease is the world’s largest disease burden.
  • a major cause is atherosclerosis, a chronic inflammation of the arteries which causes them to harden and accumulate cholesterol plaques on the artery walls, constricting or blocking blood flow.
  • arteries in the heart become blocked, patients may undergo percutaneous coronary interventions International Application Attorney Docket No.: 123178.8008.WO00 (PCIs) to clear blockages or the buildup of plaque on the arterial walls.
  • PCI belongs to a class of diagnostic and treatment procedures where a hollow catheter tube is inserted into the patient’s arteries, typically through the arm or thigh, and is guided by a physician through the vascular network into the heart.
  • IVUS intravenous ultrasound
  • Angiographic diagnosis often precedes a PCI or IVUS procedure. This is an X-ray based imaging procedure used to survey the coronary vasculature.
  • fluoroscopy a medical imaging method which uses a continuous X-ray or X-ray bursts to capture a stream of real time images of a patient’s internal anatomical structures, giving the physician a video-like sequence of images, capturing the motion of the heart and the catheter.
  • a catheter is guided to the coronary arteries, where it is used to inject a contrast agent into the arterial network.
  • contrast agents are typically liquids containing high atomic number materials (e.g., iodine with atomic number 53 and gadolinium with atomic number 64).
  • Contrast agents are also often used in PCI to aid the physician in navigating the complex vasculature network of the heart, enabling them to deliver the catheter to the target artery with higher precision.
  • care must be taken as using large amounts of contrast agent during a PCI procedure can lead to serious complications such as contrast-induced acute kidney injury (CI-AKI). Therefore, the physician is constantly balancing the desire to use more contrast to aid in navigation, with that to use less contrast to avoid patient injury and complications.
  • CI-AKI contrast-induced acute kidney injury
  • Another consideration is that X-rays are a form of ionizing radiation. The harmful effects of repeated exposure to and high doses of ionizing radiation are well known. Therefore, reducing the amount of exposure is highly beneficial for both the patient and health practitioners.
  • roadmapping systems that aid in navigation
  • visualize previously obtained X-ray images of the vasculature over live fluoroscope data correcting for motion through image analysis and analysis of other signals such as electrocardiogram time series data. They can also aid in navigation by capturing maps of the local vasculature in situ, rather than during a separate procedure.
  • Some existing systems generate roadmaps by obtaining an initial contrast scan at a given fluoroscope angle, masking it, and then overlaying this on the live X-ray images.
  • Direct measurement using additional sensors in situ can provide full three- dimensional information that could not otherwise be obtained without additional X-ray perspectives.
  • Slow update rates Since fluoroscopic systems typically obtain images on a 7-15 Hz update rate, the motion bandwidth that can be analyzed is limited to ⁇ 7.5 Hz. However, the bandwidth of cardiac motion can extend up to 50 Hz, which means these dynamics cannot be measured using fluoroscopy alone. While the roadmaps themselves only need to be refreshed at the update rate of the fluoroscope, the higher frequency motion dynamics are important for tracking and compensating for heart motion, which is a key purpose of these systems. [0055] – Lower radiation dosage.
  • a cardiac pre-scan such as a CT scan, which is typically performed before the procedure for diagnostic purposes, is used to generate a roadmap which is then aligned and overlaid on a live X-ray image during the procedure. Overlay registration and updates are performed using positioning beacons which are inserted into the patient, incorporating an invasive medical device.
  • this is a magnetic or electrical source which is sensed and positioned using a plurality of sensors placed external to the patient.
  • live X-ray images are generated by a fluoroscope.
  • An example embodiment of a system which implements this is shown in FIG. 2.
  • an invasive device with an incorporated beacon is inserted into a patient and monitored by a sensor array and a live X-ray device.
  • a processing unit determines the appropriate overlay of a pre-scan and renders a visualization of the pre-scan combined with the live X-ray image.
  • the system will analyze the pre-scan data, beacon positions over a given period, and live X-ray images.
  • the pre-scan is scaled, translated, and rotated to align the pre-scan to the live image, and store these transformations in an internal model.
  • This model will be updated to maintain alignment for future live X-ray frames.
  • a two-dimensional projection is rendered for visualization to aid in guiding the physician and medical team.
  • Beacon data will continue to be captured and processed, which will be used to update the internal model.
  • the internal model with updates will be rendered as a 2D overlay and visualized along with the live X-ray frames.
  • An example flow diagram implanting such a process is shown in FIG. 3.
  • 2 Roadmap generation [0060]
  • the roadmap is generated from a previous CT scan.
  • a 3D image is generated by imaging the patient in a tube with multiple X-ray images at different angles, usually by rotating the source in a corkscrew.
  • the vasculature is imaged using a contrast agent, similar to a traditional 2D angiogram.
  • the data generated by CT scanning is far richer than a set of 2D images, giving true 3D information.
  • voxels containing vasculature can be masked and separated from the International Application Attorney Docket No.: 123178.8008.WO00 surrounding heart tissue. [0061] Masked data is stored as a 3D representation.
  • the data is stored as a point cloud, with the location of each voxel stored as a set of x, y and z coordinates.
  • the data is mapped to a set of cubic B-splines and stored as a set of control point coordinates with associated spline parameters.
  • a 3D roadmap is generated from a series of 2D X-ray images with the vasculature imaged under contrast. Images are taken at various angles about the heart and stored to generate the reconstruction. This is analogous to the method used by a dedicated CT scanner to create its 3D representation. 3D reconstruction can be performed algorithmically using one of several well-established methods such as filtered back projection or iterative reconstruction techniques.
  • 2D roadmaps are extracted from live fluoroscopes during the procedure.
  • the fluoroscope can be triggered mechanically or electronically to save an image some specified delay after contrast is injected.
  • This image is then analyzed, masked to extract the contrast containing pixels and then used as the overlay reference for data fusion.
  • Such an image’s utility will be restricted to positions where the imaging source of the fluoroscope is in a similar position to where the image was taken. However, it is still possible to manipulate this image to form an effective overlay for surgical guidance.
  • beacons For embodiments, such as the previously discussed 2D roadmaps, where the scan is obtained with the beacon tracking system in place and catheters placed within the heart volume, it is possible to simultaneously record the position of the beacons during roadmap acquisition.
  • the absolute positions of the beacons during the scan can be associated with the beacons observed position in the roadmap image for later registration and data fusion.
  • 3 Positioning beacons Embodiments of the disclosed technology include one or more position references, referred to as “beacons,” which are used to track the position and movement of points of interest, particularly within the body of the patient.
  • Embodiments of these beacons include, but are not limited to, magnetic sources tracked with a magnetic positioning system (e.g., as described in Section 3), electric sources tracked with an impedance measurement, or physical fiducial markers which are tracked with photons.
  • An example of a fiducial marker is a gold spheroid International Application Attorney Docket No.: 123178.8008.WO00 embedded inside the patient near the heart and tracked using the X-ray imaging.
  • Examples of magnetic source embodiments include electromagnets, permanent bar magnets, or both.
  • These beacons may be placed on invasive medical devices which may carry other treatment devices and payloads, or on separate catheters which are placed within the heart vasculature. FIG.
  • beacon 4 shows an example of such an arrangement, wherein beacons are placed on an invasive medical device, e.g., a catheter or guidewire.
  • the beacon is a permanent magnet, e.g., rare earth magnets and magnetized sections of catheter wire.
  • the beacon can be an electromagnet.
  • power is delivered from outside the body, along wires embedded in the catheter structure to the coil.
  • both permanent magnets and electromagnets can be incorporated into the invasive medical device.
  • a permanent magnet with an axis pointing along the long axis with an AC magnet along the cross axis are used.
  • Embodiments using magnetic sources are localized as described in later sections, providing location and orientation information for the beacons as well as information regarding the motion of these locations within the heart volume and the heart itself. This enables tracking of the heart’s location and deformation as it beats, as well as during breathing.
  • Embodiments of the disclosed technology can be configured to track magnetic beacons within the body. These are located by means of a plurality of sensors placed external to the patient, as illustrated in FIG. 6.
  • the vector ⁇ is stored as a set of three coordinates x, y, and z.
  • the unit vector ⁇ is stored as the azimuthal and elevation angles ⁇ and ⁇ respectively.
  • FIG. 7 is a flow diagram of an example method for localization of a magnetic beacon.
  • the localization procedure begins with initializing the sensor array state, and loading the magnetic model constraints and initial parameter estimates.
  • the data collection rate is every millisecond.
  • each datum that is collected may be processed.
  • the collected data may be downsampled (or upsampled) prior to processing.
  • processing may include a demodulation step to obtain DC magnetic field levels.
  • the following series of operations are performed prior to performing the refinement procedure: [0077] (a) an initial pole axis search is performed with a constrained orientation range; [0078] (b) the residual error minimization along the target axis is performed. [0079] The refinement procedure is followed by estimating the model parameters (e.g., x, y, z, ⁇ , and ⁇ ) and the convergence metric. The estimated parameters are used to update the predicted sensor measurements in the feedback path illustrated in FIG. 7. [0080] In some embodiments, the operations in the flow diagrams illustrated in FIG. 7 and FIG. 8 include: 1) Magnetic field measurements are taken at each sensor within the sensor array.
  • FIG. 7 shows a model with 5 parameters, representing x, y, and z position of a single cylindrical dipole magnet plus azimuth and elevation. In the case of a magnetic dipole, the rotation about the magnet axis does not change the resulting magnetic field, so this parameter does not need to be modeled.
  • the magnetic poles are aligned in the sensor reference frame x-direction, with x position of the positive magnetic pole being less than the x position of the negative magnetic pole.
  • Candidate model parameters can be used to predict the corresponding locations of each magnetic pole and the resulting magnetic field measurements at each sensor in the receive sensor array.
  • a convergence metric representing the difference between the set of field measurements at each element of the sensor array and the predicted field measurement for each element of the sensor array, is calculated.
  • the convergence metric is a function of the set of differences between the measured values and the predicted values. a) In some embodiments, the convergence metric is a nonlinear function.
  • the initial location estimates of position and orientation are a blend of the geometric feature analysis and the table lookup method, with the relative weights of each method determined by the convergence metric. 7) After initial position and orientation estimates have been made, precise estimates are made using a refinement stage (e.g., illustrated in FIG. 8) which successively updates the best candidate model parameters using the set of partial derivatives of the convergence metric relative to changes in each parameter, such that the system attempts to drive the convergence metric toward zero.
  • the absolute magnetic field strengths of the magnetic beacon or magnets are used in the convergence metric.
  • the measured and predicted magnetic fields are normalized relative to each other such that the total energy in the set of measured field value matches the total energy in the set of predicted field values.
  • the initial geometric estimator can be skipped, and the system can proceed directly to the refinement stage. This is analogous to the continuous tracking mode following initial acquisition for a GPS navigation system.
  • the choice of whether to perform full position acquisition or continue with tracking mode is made by calculating the convergence metric between the last estimated location and the new set of measurements. The tracking mode is used if this metric is below a threshold.
  • FIGS. 9A-9C and 10A-10B show an example of the five beacon parameters.
  • FIGS. 9A-9C a times-series plot of the x, y, and z positions (in cm), respectively, of three magnetic beacons incorporated into an invasive medical device placed within a porcine heart are shown.
  • the beating of the heart and breathing can be seen.
  • FIG. 10A shows a time-series of the azimuthal angle of the beacon orientation
  • FIG. 10B shows a time-series of the elevation angle (in degrees) of the beacon orientation.
  • 5 Data augmentation While tracking and compensation are primarily driven by the tracking of beacons, additional sensors can be used to augment these operations. For example, motion from respiration or the heart beating can be simultaneously tracked by separate sensors and this data can be fused with the magnetic positioning data for more accurate inference.
  • heartbeat data can be generated from electrical sensing through an electrocardiogram (ECG) system.
  • ECG electrocardiogram
  • the heart motion may also be inferred from the patient’s pulse International Application Attorney Docket No.: 123178.8008.WO00 using devices readily available in a medical setting such as an optical pulse monitor or a cuff monitor placed on the patient’s limb.
  • breathing can be tracked by using a band sensor wrapped around the patient’s chest that is sensitive to expansion and contraction.
  • breathing can be tracked using an inertial measurement unit (IMU), which includes one or more of an accelerometer, a gyroscope, or a magnetometer.
  • IMU inertial measurement unit
  • breathing motion may be tracked optically using a camera system or a laser range-finding device, which tracks the movement of the patient’s chest.
  • the movement and positions of the surgical equipment can be tracked using signals directly obtained from the equipment. For example, encoder positions of the C-arm or the timing of the X-ray pulses generated by the fluoroscope may be transmitted to the system as analog or digital signals.
  • surgical equipment is tracked indirectly using auxiliary sensors and signals.
  • the C-arm position can be tracked using devices including, but not limited to, IMUs, additional magnetic sensors and beacons, or optical camera systems.
  • 6 Static registration the system first registers the translation, orientation, and scaling parameters to overlay the roadmap onto the live X-ray view. Dynamic adjustments to compensate for the motion of the beacons due to processes such as breathing and the beating of the heart are described in Section 5.
  • the registration is defined by the 6-parameter model including translations x, y, and z, rotations in azimuth and elevation, and a scaling parameter.
  • FIG. 11 shows a flow diagram of an example embodiment of a static registration method to align a three- dimensional model to a view using a two-dimensional X-ray image taken with the vasculature under contrast.
  • FIG. 11 includes the following operations: [0091] 1. Load the initial parameters for registration including the initial learning rate, a representation of the roadmap model in three-dimensions, including only the relevant vasculature, the system feature positions, including the C-arm position and table position in the world frame, the beacon positions in the world frame, the beacon trajectory history, system constraints for possible view positions and registration parameter bounds, and/or the initial guesses for the translation, rotation, and scaling parameters.
  • the representation may be a three-dimensional voxel grid or mesh. In other examples, the representation may be parametrically defined. [0093] 3. Iteratively perform the following operations: [0094] 3a. Generate a projective view of the roadmap in the live X-ray image pixel dimensions, given the current perspective parameters and form a mask, as illustrated in the examples shown in FIG. 12. [0095] 3b. Compute the likelihood of the current projective view perspective configuration.
  • the time history of the beacon positions is used to form an estimate of the trajectory of the beacons and of the vasculature structure for registration purposes.
  • the motion of the beacons describe its path through the vasculature. The likelihood that the trajectory matches the structure of a region of the vasculature measured in the pre-scan can be computed and the maximum likelihood used to determine which branch the beacon is currently in.
  • the motion of the heart is more complex.
  • the heart is modeled to rotate about a single axis along with perturbative motion about the moment of rotation.
  • some systems can consider a deformational component which corresponds to warpage of the heart’s surface relative to its rest state as it pumps. This deformation occurs due to the chambers of the heart expanding and contracting during the phases of a heartbeat.
  • the rotational and translational components can be viewed as a motion of the entire heart while the deformational component is a local effect occurring for specific areas of the surface.
  • input data that includes, but is not limited to, the current and historical beacon locations
  • input data is used to generate a motion of the model and continuously update that model to best align its projection to the current live X- ray image.
  • These updates may include scaling, translations, and rotations to compensate for both respiration and breathing, as well as deformational updates to compensate for heart surface changes during different phases of the beat cycle.
  • the scaling, translational and rotational components are treated separately from the deformation component.
  • the entire roadmap is transformed as a whole with its internal structure preserved.
  • local sections of the roadmap are treated separately to compensate for local deformations in the surface of the heart.
  • the heart is modeled as a system with a coordinate system whose origin is at the centroid of the beacon locations and basis vectors defined by the axis along which the bulk system rotates, and the two vectors forming plane perpendicular to this axis.
  • the main axis can be found, for example, by principal component analysis (PCA).
  • PCA principal component analysis
  • the beacon positions may be expressed in this coordinate system.
  • the motion due to breathing is modeled as a translation of the centroid and a rotation of the basis vector set. An example of translational motion due to breathing can be seen in FIG. 13.
  • the bulk motion of the heart while beating is modeled as a rotation of a central vector about a single axis along with additional perturbative adjustments.
  • FIG. 14 A diagram depicting the direction of motion is shown in FIG. 14, where the direction of the arrow indicates the plane in which rotation occurs.
  • FIG. 15 shows a time-series of the actual measured rotation angle (in degrees) of this motion, measured in a porcine heart with a magnetic beacon.
  • the motion model for the bulk heart motion can be determined using the flow diagram shown in FIG. 16, which considers an example system with three beacons. As shown therein, the operations include: [00113] a. Loading the reference parameters. [00114] b. Retrieving the beacon positions for a predetermined time interval, e.g., 30 sec. [00115] c. For each time interval, determining the leading basis vector describing the main heart motion direction, e.g., using singular value decomposition (SVD).
  • SSVD singular value decomposition
  • the rotation angle is associated with a phase of the heartbeat and regressed with a function containing a periodic component.
  • ECG data is used to determine the R-R peak interval, which is used in estimating the phase of the heartbeat for regression.
  • the motion due to breathing is regressed with a function containing a periodic component.
  • an initial model is used to predict future motion patterns using a predictive method that is updated as data is processed by the algorithm.
  • the predictive model is implemented as a Kalman filter.
  • the motion parameters are estimated over some time interval using a regression model and the regressed function is used as the predictor. [00135]
  • the motion generated by these transformations is applied to the roadmap, thereby translating and rotating its basis frame to match that measured for the current fluoroscope image.
  • the current perspective of the X-ray source is then used to generate a 2D projection of the roadmap view which is overlaid on the live X-ray images.
  • Embodiments of the disclosed technology may also correct for the local deformation of the heart’s surface during the heartbeat cycle.
  • the heart’s surface is composed of muscle fibers that stretch and contract as the heart pumps, acting as an elastically deformable surface.
  • the surface can be sampled as a mesh of points. A subset of these are chosen to be control points which are adjusted in position to deform the surface to conform the shape to match that of the heart during a specific phase of the heartbeat. The remaining points are then adjusted such that the energy due to elastic deformation is minimized.
  • a three-dimensional roadmap model is overlaid on a two- dimensional X-ray image.
  • a two-dimensional view of the model must be generated corresponding to the view that would be seen from the perspective of the X-ray source.
  • This view can be generated using the registered positioning relative to the X-ray source described in Section 7, or using projective geometry techniques.
  • the projective view is rendered on a display device.
  • Some example renderings include an overlay atop the live X-ray images, or a rendering overlaid with the real time beacon positions overlaid atop the projective view, and the like.
  • FIG. 19A-19C show an example of rendering processes.
  • a three-dimensional (3D) representation of the patient’s heart is illustrated in FIG. 19A.
  • the representation is dynamically corrected to match the current view of the heart, including its motion and deformation due to beating and respiration, as illustrated in FIG. 19B.
  • matching is characterized by the distance between key points in the representation and image spaces and the matching metric is the Euclidean distance between the measured and rendered key points, e.g., t ]ku]t ⁇ k .
  • FIG. 19C An example in the undeformed reference rendering and the measured image is illustrated in FIG. 19C.
  • the registration and deformation process produces a rendering that more closely matches the observed live X-ray image.
  • FIGS. 20A-20C show an example of a deformed three-dimensional representation.
  • a three-dimensional representation of a patient’s deformed heart is shown in FIG. 20A.
  • the International Application Attorney Docket No.: 123178.8008.WO00 deformed representation must then be rendered as an overlay, and combined with the live X-ray view, as shown in FIG. 20B.
  • the rendering metric includes the distances between key points
  • a lower metric is measured after deformation. This is illustrated in FIG. 20C where the positions of the key points match the live X-ray more closely than the undeformed model shown in FIG. 19C.
  • the method 2100 includes determining (2110) a location of at least one beacon, which is removably affixed to a medical device, in the vasculature structure, and generating (2120) a two-dimensional (2D) projection of the vasculature structure based on the location, a previously obtained representation of the vascular structure, and an output of a live X-ray device.
  • the method further includes determining (2130), using motion information from the at least one beacon, a motion or position of the vasculature structure relative to the output of the live X-ray device, and generating (2140), based on combining the 2D projection and the motion or position of the vasculature structure, the representation of the vasculature structure.
  • the method then includes tracking (2150), based on the representation of the vasculature structure, a location of the medical device in the vasculature structure.
  • a method for determining a representation of a vasculature structure of a patient comprising: determining a location of at least one beacon in the vasculature structure, wherein the at least one beacon is removably affixed to a medical device; generating a two-dimensional (2D) projection of the vasculature structure based on the location, a previously obtained representation of the vasculature structure, and an output image from a live X-ray device; determining, using motion information from the at least one beacon, a motion or position of the vasculature structure relative to the output image from of the live X-ray device; generating, based on combining the 2D projection and the motion or position of the vasculature structure, the representation of the vasculature structure; and tracking, based on the representation of the vasculature structure, a location of the medical device in the vasculature structure.
  • 2D two-dimensional
  • any of solutions S1 to S4 comprising: constraining, based on image information from the output image or structural information from the previously obtained representation, the representation.
  • S6 The method of solution S5, wherein the image information comprises a pixel intensity of the output image or an observed motion of the at least one beacon in a plurality of output images from the live X-ray device.
  • S7 The method of solution S5, wherein the structural information comprises at least one of: surface contours of the vasculature structure; a branching or a physical layout of the vasculature structure within a larger anatomical structure; or a deformation dynamic based on a material property or a physical orientation property.
  • S8 The method of any of solutions S1 to S4, comprising: constraining, based on image information from the output image or structural information from the previously obtained representation, the representation.
  • any of solutions S1 to S7 comprising: tracking a time history of the location and an orientation of the at least one beacon.
  • S9 The method of any of solutions S1 to S8, wherein the vasculature structure comprises a heart of the patient, and wherein the method comprises: tracking, based on the representation of the vasculature structure, a motion of the heart using an adaptive tracking loop.
  • a system for determining a representation of a vasculature structure of a patient comprising: at least one beacon; an array of magnetic sensors, external to the patient, configured to sense the at least one beacon integrated into an invasive medical device; and at least one processor configured to: determine a location of the at least one beacon in the vasculature structure, generate a two-dimensional (2D) projection of the vasculature structure based on the location, a previously obtained representation of the vasculature structure, and an output image from a live X-ray device, determine, using motion information from the at least one beacon, a motion or position of the vasculature structure relative to the output image from of the live X-ray device, generate, based on combining the 2D projection and the motion or position of the vasculature structure, the representation of the vasculature structure, and track, based on the International Application Attorney Docket No.: 123178.8008.WO00 representation of the vasculature structure, a location of the invasive medical device
  • the arbitrary waveform generator (e.g., the AWG70000B Series Arbitrary Waveform Generator from Tektronix) is part of an integrated system that includes the at least one beacon, the array of magnetic sensors, and the at least one processor.
  • S16 The system of any of solutions S10 to S15, wherein the at least one beacon comprises a permanent magnet with a first magnetic axis and an electromagnet with a second magnetic axis that is perpendicular to the first magnetic axis.
  • S17 The system of solution S16, wherein the first magnetic axis is parallel to an axis of the invasive medical device.
  • S18 S18.
  • S22 The system of solution S21, wherein the biological process comprises a heart beat of the patient, and wherein the at least one signal comprises an electrical signal of an electrocardiogram (ECG), an output signal from magnetically sensing a heart’s current, or a pulse signal generated by an optical sensor or a pressure sensor.
  • ECG electrocardiogram
  • S23 The system of solution S22, wherein an interval of the heart beat is monitored using the electrical signal of the ECG or a magnetocardiogram.
  • S24 The system of solution S21, wherein the biological process comprises a heart beat of the patient, and wherein the at least one signal comprises an electrical signal of an electrocardiogram (ECG), an output signal from magnetically sensing a heart’s current, or a pulse signal generated by an optical sensor or a pressure sensor.
  • the system of solution S21 wherein the biological process comprises breathing by the patient, and wherein the at least one signal comprises: an electrical signal indicative of a motion of a chest of the patient, a measurement signal corresponding to an acceleration, an orientation, or a magnetic field strength, or an optical signal.
  • the system of solution S24 comprising: an inertial measurement unit (IMU) configured to generate the measurement signal; or an optical means configured to detect the optical signal, wherein the IMU comprises at least one of a magnetometer, an accelerometer, or a gyroscope, and wherein the breathing is monitored using a band sensitive to mechanical strain from the breathing, the IMU, or the optical means.
  • IMU inertial measurement unit
  • the inertial measurement unit (IMU, or IMMU when the magnetometer is incorporated) and/or the optical means are part of an integrated system that includes the at least one beacon, the array of magnetic sensors, and the at least one processor.
  • S26 The system of solution S25, wherein the optical means comprises a camera or a laser range-finding device.
  • S27 The system of solution S25, wherein the optical means comprises a camera or a laser range-finding device.
  • the previously obtained representation of the vasculature structure comprises at least one of a three-dimensional (3D) computed tomography (CT) scan, a collection of 2D X-ray images captured from multiple viewing angles, a single 2D X-ray image captured from a viewing angle of the live X-ray device, or another representation obtained from an imaging modality that excludes X-rays.
  • 3D three-dimensional
  • CT computed tomography
  • S32. A method for determining a relative location and orientation of a previously generated representation of regions of interest of a cardiac vasculature relative to a two- dimensional image, wherein the determining is based on a location and orientation of positioning beacons incorporated into one or more invasive medical devices, and feature information from within the previously generated representation and the two-dimensional image.
  • a method of visually representing a relative location and orientation of a previously generated representation of regions of interest of a cardiac vasculature relative to a two-dimensional image comprising: making a first determination of a relative location and orientation of a previously generated representation of the regions of interest of the cardiac vasculature relative to a two-dimensional image; making a second determination that the relative location and orientation has changed; and updating, based on the second determination, the relative location and orientation of the regions of interest of the cardiac vasculature.
  • FIG. 22 shows an example of a hardware platform 2200 that can be used to implement some of the techniques described in the present document.
  • the hardware platform 2200 can implement method 2100, or implement the various modules and algorithms described herein.
  • the hardware platform 2200 includes a processor 2202 that can execute code to implement a method.
  • the hardware platform 2200 includes a memory 2204 that is used to store processor-executable code and/or store data.
  • the hardware platform 2200 further includes International Application Attorney Docket No.: 123178.8008.WO00 magnets 2206 and magnetometers 2208, which can communicate with the processor 2202 using leads or a wireless protocol.
  • the processor 2202 is configured to implement localization, fusion, and registration algorithms.
  • the memory 2204 comprises multiple memories, some of which are exclusively used by the processor 2202 when implementing the fusion, localization, or registration algorithms.
  • the computer readable medium can be a machine- readable storage device, a machine-readable storage substrate, a memory device, a composition of matter effecting a machine-readable propagated signal, or a combination of one or more of them.
  • the term “data processing unit” or “data processing apparatus” encompasses all apparatus, devices, and machines for processing data, including by way of example a programmable processor, a computer, or multiple processors or computers.
  • the apparatus can include, in addition to hardware, code that creates an execution environment for the computer program in question, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of them.
  • a computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.
  • a computer program does not necessarily correspond to a file in a file system.
  • a program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub programs, or portions of code).
  • a computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a International Application Attorney Docket No.: 123178.8008.WO00 communication network.
  • the processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output.
  • the processes and logic flows can also be performed by, and devices can be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit).
  • processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer.
  • a processor will receive instructions and data from a read-only memory or a random-access memory or both.
  • the essential elements of a computer are a processor for performing instructions and one or more memory devices for storing instructions and data.
  • a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks. However, these are optional.
  • Computer readable media suitable for storing computer program instructions and data include all forms of nonvolatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices.
  • semiconductor memory devices e.g., EPROM, EEPROM, and flash memory devices.
  • the processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.

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Abstract

L'invention concerne des dispositifs, des systèmes et des procédés pour générer une carte de guidage pour aider à la navigation in situ de dispositifs médicaux invasifs incorporant des balises de positionnement. Un procédé donné à titre d'exemple pour déterminer une représentation d'une structure vasculaire d'un patient consiste à déterminer un emplacement d'au moins une balise, qui est fixée de manière amovible à un dispositif médical, dans la structure vasculaire du patient. Le procédé consiste en outre à générer une projection 2D de la structure de système vasculaire sur la base de l'emplacement, d'une représentation précédemment obtenue de la structure de système vasculaire, et d'une image de sortie provenant d'un dispositif à rayons X en direct, et à déterminer, à l'aide d'informations de mouvement provenant de ladite balise, un mouvement ou une position de la structure de système vasculaire par rapport à l'image de sortie provenant du dispositif à rayons X en direct. La projection 2D et le mouvement ou la position de la structure vasculaire sont combinés pour générer la représentation de la structure vasculaire.
PCT/US2025/024389 2024-04-16 2025-04-11 Systèmes et procédés de fusion de tomodensitométrie Pending WO2025221620A1 (fr)

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