Method, apparatus, system, medium, and product for generating intracranial electrode lead trajectories

Abstract

This invention discloses a method, apparatus, system, medium, and product for generating intracranial electrode lead trajectories. The method includes: acquiring medical imaging data of a patient's brain after intracranial electrode lead implantation; extracting a set of feature points corresponding to the electrode lead from the medical imaging data; selecting a set of target feature points implanted in the patient's cranium from the set of feature points based on the trajectory characteristics of the electrode lead in the patient's cranium, wherein the trajectory characteristics at least indicate that the curvature of the electrode lead in the patient's cranium does not exceed a preset curvature value; and simulating the trajectory of the electrode lead in the patient's cranium based on the set of target feature points. This application utilizes the intracranial trajectory of the electrode lead to accurately identify the intracranial electrode lead portion. Through the points corresponding to the intracranial electrode lead portion, precise three-dimensional visualization rendering of the intracranial electrode lead is performed, enabling doctors to better understand the positional relationship between the intracranial electrode lead and surrounding nerve fiber bundles, which helps doctors optimize programming parameters and improve treatment outcomes.

Description

Technical Field

[0001] This invention relates to the field of implantable medical technology, specifically to a method, apparatus, implantable medical system, storage medium, and program product for generating the trajectory of an intracranial electrode lead for implanted patients. Background Technology

[0002] With the continuous development of modern medical technology, visual programming has been widely used in the field of implantable stimulation therapy. Visual programming uses 3D modeling technology to render the nuclei in the patient's brain, implanted electrode wires, stimulation range and nerve fibers into a three-dimensional model.

[0003] In existing technologies, only the coordinates of certain points on the electrode leads in the image can be extracted. It is impossible to identify which coordinates are inside the brain and which coordinates are outside the brain. Therefore, accurately identifying the intracranial electrode lead portion of the patient is very difficult, which makes precise rendering of the intracranial electrode lead extremely difficult and thus cannot achieve a good auxiliary programming effect.

[0004] This invention solves at least one of the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide a method for generating the trajectory of implanted intracranial electrode leads in patients, solving the technical problem that the existing technology cannot accurately identify the intracranial electrode lead portion, which makes accurate rendering of the intracranial electrode lead extremely difficult. This application utilizes the direction of the electrode lead within the skull to accurately identify the intracranial electrode lead portion, and uses the points corresponding to the intracranial electrode lead portion to perform accurate three-dimensional visualization rendering of the intracranial electrode lead, enabling doctors to better understand the positional relationship between the intracranial electrode lead and the surrounding nerve fiber bundles, thereby helping doctors optimize programming parameters and improve treatment outcomes.

[0006] The objective of this invention is achieved through the following technical solution:

[0007] A first aspect of the present invention provides a method for generating the trajectory of an implanted intracranial electrode lead, the method comprising:

[0008] Acquire medical imaging data of the patient's brain after intracranial electrode leads are implanted;

[0009] Extract the set of feature points corresponding to the electrode wires from the medical image data;

[0010] Based on the trajectory characteristics of the electrode wire in the patient's skull, a set of target feature points to be implanted in the patient's skull is selected from the set of feature points. The trajectory characteristics at least indicate that the degree of bending of the electrode wire in the patient's skull does not exceed a preset bending value.

[0011] Based on the target feature point set, the trajectory of the electrode wires inside the patient's skull is simulated.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0013] I. This application utilizes prior medical knowledge to precisely screen out intracranial electrode wire portions during implantable medical stimulation surgery, taking advantage of the significant difference between the curvature of the electrode wire at the cranial foramen and the completeness of the intracranial portion, i.e., the different directions of the electrode wire.

[0014] Second, the feature point set corresponding to the electrode wire is extracted from medical imaging data; and the portion of the electrode wire in the patient's skull with a bending degree not exceeding the preset bending value is accurately screened out using a preset bending value, and the target feature point set corresponding to this portion is simulated to obtain the trajectory of the electrode wire in the patient's skull.

[0015] Third, based on the obtained relatively accurate electrode lead trajectory, the intracranial electrode lead model is visualized and rendered, which provides good auxiliary programming for implantable stimulation surgery. This improves the accuracy of the relative position between the electrode lead and the stimulated nucleus, helping doctors adjust programming parameters and thus improve treatment outcomes. It also enables doctors to better understand the positional relationship between the electrode lead and the surrounding nerve fiber bundles, thereby helping them optimize programming parameters and improve treatment results.

[0016] In some possible implementations of the first aspect, based on the trajectory characteristics of the electrode wire within the patient's skull, a set of target feature points to be implanted into the patient's skull is selected from the set of feature points, including:

[0017] Starting from the feature point corresponding to the electrode wire implanted deepest in the cranium, calculate the degree of curvature of the electrode wire between any three adjacent feature points in all feature points.

[0018] When the degree of curvature is greater than the preset curvature value, the characteristic inflection point of the electrode wire implantation into the patient's skull is determined from the characteristic points corresponding to the degree of curvature.

[0019] Based on the feature inflection point, the target feature point set is obtained by filtering from the feature point set.

[0020] In some possible implementations of the first aspect, calculating the degree of bending of the electrode wire between any three adjacent feature points among all feature points includes:

[0021] Obtain the spatial coordinates of any three adjacent feature points;

[0022] Based on the spatial coordinates of two adjacent feature points in any three adjacent feature points, calculate the first direction vector and the second direction vector between the two adjacent feature points in sequence.

[0023] Calculate the dot product of the first direction vector and the second direction vector, and use the dot product as the degree of curvature of the electrode wire between three adjacent feature points.

[0024] In some possible implementations of the first aspect, based on the trajectory characteristics of the electrode wire within the patient's skull, a set of target feature points to be implanted into the patient's skull is selected from the set of feature points, including:

[0025] The initial electrode trajectory of the electrode wire is obtained by fitting the spatial coordinates of each feature point in the feature point set.

[0026] Based on the trajectory characteristics of the electrode wire in the patient's skull, determine the range of the electrode trajectory slope of the portion of the electrode wire implanted in the skull;

[0027] Based on the range of electrode trajectory slopes and the trajectory slopes at different positions of the initial electrode trajectory, at least a portion of the initial electrode trajectory is extracted to obtain the target electrode trajectory;

[0028] Based on the feature points in the target electrode trajectory, determine the set of target feature points to be implanted into the patient's skull.

[0029] In some possible implementations of the first aspect, the trajectory of the electrode wire within the patient's cranium is simulated based on the target feature point set, including:

[0030] Based on the spatial coordinates of each feature point in the target feature point set, the curve trajectory equation of the electrode wire in the patient's skull is fitted to obtain the equation of the curve trajectory of the electrode wire in the patient's skull.

[0031] The trajectory of the electrode wires inside the patient's skull is determined based on the curve trajectory equation and the brain environment information inside the patient's skull.

[0032] In some possible implementations of the first aspect, the method further includes:

[0033] Based on the curve trajectory equation, and taking the feature point corresponding to the deepest part of the implanted electrode wire in the cranium and the feature inflection point as the endpoint of the electrode implantation, the length of the electrode wire implanted in the patient's cranium is calculated.

[0034] In some possible implementations of the first aspect, the medical imaging data includes at least a set of CT images obtained by scanning along at least one computed tomography (CT) scan direction.

[0035] In some possible implementations of the first aspect, the method for obtaining the spatial coordinates of the feature point includes:

[0036] For each electrode wire and its corresponding image identifier, obtain at most one feature point corresponding to the electrode wire in each CT image of the CT image set;

[0037] The spatial coordinates of each feature point are determined based on the voxel coordinates corresponding to each feature point.

[0038] In some possible implementations of the first aspect, the CT scan orientation includes sagittal and coronal planes.

[0039] A second aspect of the present invention provides an apparatus for generating intracranial electrode lead trajectories, the apparatus comprising:

[0040] Image acquisition module: used to acquire medical imaging data of the patient's brain after intracranial electrode leads are implanted;

[0041] Feature point extraction module: used to extract the set of feature points corresponding to the electrode wires from the medical image data;

[0042] Target feature point acquisition module: Based on the trajectory characteristics of the electrode wire in the patient's skull, filter out the target feature point set to be implanted in the patient's skull from the feature point set, wherein the trajectory characteristics at least indicate that the bending degree of the electrode wire in the patient's skull does not exceed a preset bending value;

[0043] Conductor trajectory generation module: used to simulate the trajectory of the electrode conductor in the patient's skull based on the target feature point set.

[0044] A third aspect of the present invention provides an implantable medical system, the implantable medical system comprising:

[0045] A first processor is configured to communicate with a medical acquisition device and execute the above-described method, wherein the medical acquisition device is used to acquire medical image data of a patient.

[0046] The display screen is configured to display the medical imaging data, wherein the medical imaging data includes at least a set of CT images obtained from at least one computed tomography (CT) scan of the patient's brain after intracranial electrode wires have been implanted, and the trajectory of the electrode wires within the patient's brain.

[0047] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a second processor, implements the steps of the method described above.

[0048] A fifth aspect of the present invention provides a computer program product comprising instructions that, when executed on an electronic device, cause the electronic device to perform the steps of the above-described method. Attached Figure Description

[0049] Figure 1 This is a flowchart illustrating the overall steps of the method for generating intracranial electrode lead trajectory provided in this application embodiment;

[0050] Figure 2 This is a flowchart of step S3 in one embodiment provided by this application.

[0051] Figure 3 This is a flowchart of step S31a provided in the embodiments of this application;

[0052] Figure 4 This is a flowchart of the steps for obtaining spatial coordinates provided in an embodiment of this application;

[0053] Figure 5 This is a flowchart of step S3 in another embodiment provided in this application;

[0054] Figure 6 This is a flowchart of step S4 provided in the embodiments of this application;

[0055] Figure 7 This is a schematic diagram of the structure of the device for generating intracranial electrode wire trajectory provided in the embodiments of this application;

[0056] Figure 8 This is a schematic diagram of the structure of the implantable medical system provided in the embodiments of this application. Detailed Implementation

[0057] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided to make the invention more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and therefore repeated descriptions of them will be omitted.

[0058] First, a brief description will be given of one application area of ​​the embodiments of this application (i.e., implantable neurostimulation system).

[0059] Implantable medical systems include implantable neurostimulation systems, implantable cardiac stimulation systems (also known as pacemakers), implantable drug delivery systems (IDDS), and lead transfer systems. Examples of implantable neurostimulation systems include deep brain stimulation (DBS), cortical nerve stimulation (CNS), spinal cord stimulation (SCS), sacral nerve stimulation (SNS), and vagus nerve stimulation (VNS).

[0060] Implantable neurostimulation systems consist of a stimulator implanted in the patient's body (i.e., an implantable neurostimulator) and a programmed device placed outside the patient's body. In other words, the stimulator is a medical device, or medical devices include stimulators. Related neuromodulation techniques primarily involve stereotactic surgery to implant electrodes (e.g., electrode wires) at specific sites (target points) in the body's tissues. Discharge pulses are then delivered through these electrodes to the target points, modulating the electrical activity and function of corresponding neural structures and networks, thereby improving symptoms and alleviating pain.

[0061] As an example, a DBS includes an IPG (Implantable Pulse Generator), extension leads, and electrode leads. The IPG is connected to the electrode leads via the extension leads. The IPG is implanted in the patient's body, for example, in the chest or other internal locations.

[0062] As another example, DBS includes an IPG and electrode leads, with the IPG directly connected to the electrode leads. The IPG is implanted in the patient's head, for example, by creating a groove in the patient's skull and then placing the IPG in the groove. In this case, the IPG may not protrude from the outer surface of the skull, or it may protrude partially from the outer surface of the skull.

[0063] The IPG (Intracytoplasmic Gyroscope) responds to sample brain mask information sent by a programmable device, delivering controllable electrical stimulation (or electrical stimulation energy) to tissues within the body via a sealed battery and circuitry. When the battery is low, it needs to be recharged, which can be done wirelessly using an electromagnetic induction coil, bypassing the skin or other epidermal tissue. The IPG delivers one or more controllable electrical stimuli to specific areas of tissue within the body via electrode wires.

[0064] In some embodiments, the extension wire is used in conjunction with the IPG as a medium for transmitting electrical stimulation, thereby transmitting the electrical stimulation generated by the IPG to the electrode wire.

[0065] In some embodiments, electrical stimulation can be delivered in the form of a pulsed signal or a non-pulsed signal. For example, electrical stimulation can be delivered as a signal with various waveform shapes, frequencies, and amplitudes. Therefore, non-pulsed signal electrical stimulation can be a continuous signal, which can have a sinusoidal waveform or other continuous waveforms.

[0066] After receiving electrical stimulation from the IPG or extension leads, the electrode leads deliver the stimulation to specific areas of tissue within the body via multiple electrode contacts. The stimulator may have one or more electrode leads on one or both sides, with multiple electrode contacts on each lead. These contacts may be evenly or non-uniformly arranged circumferentially on the electrode leads. As an example, the electrode contacts may be arranged in a 4x3 array (a total of 12 contacts) circumferentially on the electrode leads. The electrode contacts may include stimulating electrode contacts and / or collecting electrode contacts. The electrode contacts may be in shapes such as sheet-like, ring-like, or dot-like.

[0067] In some embodiments, the stimulated tissue may be the patient's brain tissue, and the stimulated site may be a specific location within the brain tissue. Generally, the stimulated site differs depending on the patient's disease type, and the number of stimulation contacts (single-source or multi-source), the application of one or more specific electrical stimulation pathways (single-channel or multi-channel), and the stimulation parameters (values) also vary.

[0068] This application does not limit the applicable disease types, but can be any disease type applicable to deep brain stimulation (DBS), spinal cord stimulation (SCS), sacral nerve stimulation, gastric stimulation, peripheral nerve stimulation, or functional electrical stimulation. Among these, DBS can be used to treat or manage diseases including, but not limited to: spastic disorders (e.g., epilepsy), pain, migraines, mental illnesses (e.g., major depressive disorder (MDD)), bipolar disorder, anxiety disorders, post-traumatic stress disorder, mild depression, obsessive-compulsive disorder (OCD), behavioral disorders, mood disorders, memory disorders, mental state disorders, mobility disorders (e.g., essential tremor or Parkinson's disease), Huntington's disease, Alzheimer's disease, drug addiction, autism, or other neurological or psychiatric diseases and impairments.

[0069] In this embodiment of the application, when the programmable device and the stimulator establish a programmable connection, the programmable device can be used to adjust one or more stimulation parameters of the stimulator (or one or more stimulation parameters of the pulse generator, with different stimulation parameters corresponding to different electrical stimuli). Alternatively, the stimulator can sense the patient's electrophysiological activity to collect electrophysiological signals, and the collected electrophysiological signals can be used to continue adjusting the stimulation parameters of the stimulator to achieve closed-loop control (or adaptive adjustment) of the stimulation parameters.

[0070] Stimulation parameters may include at least one of the following: electrode contact identification for delivering electrical stimulation (e.g., electrode contact #2 and electrode contact #3), frequency (e.g., the number of electrical stimulation pulse signals per second, in Hz), pulse width (duration of each pulse, in μs), amplitude (generally expressed as voltage, i.e., the intensity of each pulse, in V), timing (e.g., continuous or bursty, bursty refers to discontinuous timing behavior composed of multiple processes), stimulation mode (including one or more of current mode, voltage mode, timed stimulation mode, and cyclic stimulation mode), physician control upper and lower limits (the range that the physician can adjust), and patient control upper and lower limits (the range that the patient can adjust independently).

[0071] In some embodiments, the stimulation parameters of the stimulator can be adjusted in current mode or voltage mode.

[0072] Programmable devices can include physician-controlled devices (i.e., devices used by physicians) and / or patient-controlled devices (i.e., devices used by patients). Physician-controlled devices are, for example, smart terminal devices such as tablets, laptops, desktop computers, and mobile phones equipped with programming software. Patient-controlled devices are, for example, smart terminal devices such as tablets, laptops, desktop computers, and mobile phones equipped with programming software; patient-controlled devices can also be other electronic devices with programming functions (e.g., chargers with programming functions, electrophysiological acquisition devices, etc.).

[0073] This application does not limit the data interaction between the doctor's programming device and the stimulator. When the doctor programs remotely, the doctor's programming device can interact with the stimulator through a server or the patient's programming device. When the doctor programs in person with the patient, the doctor's programming device can interact with the stimulator through the patient's programming device, or it can interact directly with the stimulator. The doctor sends a set of programming parameters to the stimulator through the programming device. The set of programming parameters (or the preset programming parameters mentioned below) includes multiple electrode contacts and stimulation parameters corresponding to each electrode contact.

[0074] In some embodiments, the patient programming device may include a host (communicating with a server) and a slave (communicating with a stimulator), the host and slave being communicatively connected. The doctor programming device can interact with the server via a 3G / 4G / 5G network, the server can interact with the host via a 3G / 4G / 5G network, the host can interact with the slave via Bluetooth / Wi-Fi / USB protocols, the slave can interact with the stimulator via a 401MHz-406MHz / 2.4GHz-2.48GHz operating frequency band, and the doctor programming device can directly interact with the stimulator via the 401MHz-406MHz / 2.4GHz-2.48GHz operating frequency band.

[0075] Combined with appendix Figure 1 As shown, the first aspect of this embodiment provides a method for generating the trajectory of an implanted intracranial electrode wire, including the following steps S1-S4.

[0076] Step S1: Obtain medical imaging data of the patient's brain after intracranial electrode leads are implanted.

[0077] It should be noted that the medical imaging data is DICOM (Digital Imaging and Communications in Medicine) data. DICOM is an international standard for medical images and related information, defining a medical image format that meets clinical needs and can be used for data exchange. DICOM data may include hierarchical information corresponding to the medical image file and / or identification information of the medical institution. Hierarchical information may include the patient's case number, the examination site, and the data type of the medical image file. Data types include, for example, CT (Computed Tomography) image data and MR (Magnetic Resonance) image data. Identification information of the medical institution may include the institution's name and geographical location.

[0078] In this embodiment, the medical imaging data includes at least a set of CT images obtained by scanning along at least one computed tomography (CT) scanning direction.

[0079] It's important to further clarify that CT scans include sagittal and coronal views. The sagittal view refers to the plane that divides the human brain into two symmetrical parts, left and right. This plane is parallel to the sagittal plane; it can also be a section perpendicular to the horizontal plane along the long axis of the brain. In the sagittal view, the distribution and morphology of brain structures in the left-right direction can be clearly seen. The coronal view, also called the frontal plane, refers to a section that divides the brain into two planes, anterior and posterior. It's equivalent to dissecting the brain from the front, creating a horizontal section that divides the brain into anterior and posterior parts, facilitating the observation of structures perpendicular to the long axis of the brain.

[0080] In CT scans, sagittal and coronal views are commonly used scanning directions, which provide doctors with the ability to observe the patient's internal structures from different angles, helping to make more accurate diagnoses and treatments.

[0081] Step S2: Extract the set of feature points corresponding to the electrode leads from the medical imaging data.

[0082] In this embodiment, the patient's brain is scanned in the coronal plane. The resulting CT image set includes multiple CT images along the coronal direction from the base of the skull to the top of the skull. In the CT images, since each electrode lead has a corresponding image identifier, the image identifier of the electrode lead is identified by using image recognition technology. At most one feature point corresponding to the electrode lead in each CT image can be identified, thereby obtaining the set of feature points corresponding to the electrode lead.

[0083] Step S3: Based on the trajectory characteristics of the electrode wires in the patient's skull, select the target feature point set to be implanted in the patient's skull from the feature point set.

[0084] It should be noted that the trajectory characteristics at least indicate that the degree of bending of the electrode wire within the patient's skull does not exceed a preset bending value.

[0085] The applicant here uses prior medical knowledge because when a patient undergoes implantable brain stimulation surgery, the electrode wires inside the skull are almost in the same direction. In other words, the degree of curvature of the intracranial electrode wires is very small, and to a certain extent, they are close to a straight line. However, at the cranial foramen where the implantation is performed, the electrode wires are close to the scalp, so the electrode wires will bend at the cranial foramen, and the degree of curvature is very large. In other words, there is a significant difference in the direction of the electrode wires inside the skull and at the cranial foramen.

[0086] For example, if the preset curvature value is K, then all curvatures of the intracranial electrode leads are less than or equal to K, while the curvature of the electrode leads at the cranial foramen is greater than K.

[0087] Understandably, by comparing the preset curvature value with all the curvatures of the electrode wires, the feature points corresponding to the intracranial electrode wires and the feature points corresponding to the electrode wires at the cranial foramen can be accurately screened from the feature point set, thereby clarifying the direction of the electrode wires in the intracranial part.

[0088] This allows us to select the feature points corresponding to the electrode leads whose curvature within the patient's skull does not exceed a preset curvature value, i.e., the target feature point set, from the feature point set of all feature points corresponding to the electrode leads in the CT image set.

[0089] It should be noted that this embodiment uses implantable brain stimulation, namely deep brain stimulation (DBS), as an example, but it does not constitute a limitation on the application scenario of this application. This application can also be applied to other implantable medical stimulation surgeries, such as implantable cortical nerve stimulation (CNS), implantable spinal cord stimulation (SCS), implantable sacral nerve stimulation (SNS), implantable vagus nerve stimulation (VNS), etc.

[0090] In one specific implementation, in conjunction with the appendix Figure 2 As shown, step S3 includes steps S31a-S33a.

[0091] Step S31a: Starting from the feature point corresponding to the electrode wire implanted deepest in the cranial cavity, calculate the degree of curvature of the electrode wire between any three adjacent feature points in all feature points.

[0092] Since any two adjacent feature points can only determine the direction of a line segment, to determine the degree of bending of the electrode wire, it is necessary to observe the change in direction. Therefore, it is necessary to introduce another adjacent feature point. By using any three adjacent feature points, two adjacent line segments can be formed, and their directions can be compared. In this way, any change in direction can be captured, which is the key to calculating the degree of bending of the electrode wire.

[0093] Furthermore, using three adjacent feature points to determine the degree of bending has locality, meaning it only focuses on the bending situation within a small range of the three currently adjacent feature points. This is very comprehensive and effective for detecting inflection points, bending points, or curve segments on electrode wires, and can show significant changes in the electrode wires in local directions.

[0094] In some specific implementation methods, in conjunction with the appendix Figure 3As shown, step S31a, which calculates the degree of bending of the electrode wire between any three adjacent feature points among all feature points, includes steps S311-S313.

[0095] Step S311: Obtain the spatial coordinates of any three adjacent feature points.

[0096] In some specific implementation methods, in conjunction with the appendix Figure 4 As shown, the method for obtaining the spatial coordinates of feature points includes steps S3111-S3112.

[0097] Step S3111: For each electrode wire and the corresponding image identifier, obtain at most one feature point corresponding to the electrode wire in each CT image of the CT image set.

[0098] Step S3112: Determine the spatial coordinates of each feature point based on the voxel coordinates corresponding to each feature point.

[0099] Since each electrode lead has a corresponding image identifier in the CT image, the voxel coordinates corresponding to each feature point can be determined using the image identifier. By using spatial matrix transformation, the spatial coordinates corresponding to each feature point can be obtained. This is existing technology and will not be elaborated here.

[0100] Step S312: Based on the spatial coordinates of two adjacent feature points in any three adjacent feature points, calculate the first direction vector and the second direction vector between the two adjacent feature points in sequence.

[0101] Specifically, for any three adjacent feature points, two adjacent line segments can be formed. By calculating the vectors corresponding to the line segments, the first direction vector F1 and the second direction vector F2 between the two adjacent feature points can be obtained.

[0102] Step S313: Calculate the dot product of the first direction vector and the second direction vector, and use the dot product as the degree of bending of the electrode wire between three adjacent feature points.

[0103] To determine the degree of curvature of the electrode wire between three adjacent feature points, the angle between the two adjacent line segments formed by the three feature points can be calculated. This angle can be obtained through the dot product, thus the dot product can accurately characterize the degree of curvature of the electrode wire between three adjacent feature points.

[0104] Step S32a: When the degree of curvature is greater than the preset curvature value, the characteristic inflection point of the electrode wire implantation into the patient's skull is determined from the characteristic points corresponding to the degree of curvature.

[0105] As mentioned earlier, at the cranial foramen during implantation surgery, the electrode wires are close to the scalp, so they will bend at the cranial foramen. When the degree of bending of the electrode wire between three adjacent feature points is greater than the preset bending value, that is, when the degree of bending at the bend is greater than the preset bending value, it means that among the three adjacent feature points corresponding to this degree of bending, the middle feature point is the feature inflection point corresponding to the bend. Thus, the feature inflection point can be accurately calculated from all feature points.

[0106] Step S33a: Based on the feature inflection point, select the target feature point set from the feature point set.

[0107] By using feature inflection points, all feature points on the electrode wire are precisely screened and segmented to determine the target feature point set of the electrode wire implanted in the patient's skull. In other words, the target feature point set includes feature inflection points, feature points corresponding to the electrode wire implanted at the deepest point in the skull, and all feature points between the two from the top of the skull to the bottom of the skull.

[0108] In another specific implementation, in conjunction with the appendix Figure 5 As shown, step S3 includes steps S31b-S33b.

[0109] Step S31b: Based on the spatial coordinates of each feature point in the feature point set, fit the initial electrode trajectory of the electrode wire.

[0110] Specifically, the initial electrode trajectory of the electrode wire can be obtained by fitting using the moving least squares method. The moving least squares method is a local fitting method that can perform local fitting around each feature point, thereby obtaining a smoother initial electrode trajectory of the electrode wire.

[0111] Step S32b: Determine the range of the electrode trajectory slope of the portion of the electrode wire implanted in the intracranial cavity based on the trajectory characteristics of the electrode wire in the patient's skull.

[0112] As mentioned above, the trajectory features at least indicate that the degree of bending of the electrode wire within the patient's skull does not exceed a preset bending value.

[0113] This implementation also utilizes the aforementioned medical prior knowledge. It is understood that because different degrees of curvature on the electrode wire correspond to different electrode trajectory slopes, that is, different directions, by comparing the preset curvature value with all degrees of curvature of the electrode wire, the range of electrode trajectory slopes of the part of the electrode wire implanted in the cranial cavity and the trajectory slope of the electrode wire at the cranial foramen can be screened out, thereby more accurately determining the range of electrode trajectory slopes of the part of the electrode wire implanted in the cranial cavity.

[0114] Step S33b: Based on the range of electrode trajectory slope and the trajectory slope at different positions of the initial electrode trajectory, at least a portion of the initial electrode trajectory is extracted to obtain the target electrode trajectory.

[0115] By comparing the slope range of the electrode trajectory with the slope of the trajectory at different positions of the initial electrode trajectory, the target electrode trajectory corresponding to the slope range of the electrode trajectory can be accurately extracted from the initial electrode trajectory.

[0116] Step S34b: Determine the set of target feature points to be implanted into the patient's skull based on the feature points in the target electrode trajectory.

[0117] Based on the target electrode trajectory, the target feature point set corresponding to the target electrode trajectory can be screened out from the feature point set. The electrode wire corresponding to this target feature point set is the electrode wire implanted in the patient's skull.

[0118] Step S4: Based on the target feature point set, simulate the trajectory of the electrode wires inside the patient's skull.

[0119] Specifically, the trajectory of the intracranial electrode wire can be obtained by fitting the moving least squares method. The moving least squares method is a local fitting method that can perform local fitting around each feature point, thereby obtaining a smoother trajectory of the intracranial electrode wire. This enables the visualization and rendering of the intracranial electrode wire model, which has a good auxiliary programming effect for implantable stimulation medical surgery.

[0120] In some specific implementation methods, in conjunction with the appendix Figure 6 As shown, step S4 includes steps S41-S42.

[0121] Step S41: Based on the spatial coordinates of each feature point in the target feature point set, fit the curve trajectory equation of the electrode wire in the patient's skull.

[0122] Step S42: Determine the trajectory of the electrode wires inside the patient's skull based on the curve trajectory equation and the brain environment information inside the patient's skull.

[0123] It should be noted that by using the spatial coordinates of each feature point in the target feature point set to fit the curve trajectory equation of the electrode wire in the patient's skull, the visualization rendering of the intracranial electrode wire model can be achieved. When applied to implantable stimulation medical surgery, it is necessary to simultaneously render the brain environment information in the patient's skull to obtain the brain tissue model of the patient's brain. Therefore, by using the curve trajectory equation and the brain environment information in the patient's skull, the intracranial electrode wire model and the brain tissue model are fused in the same spatial coordinate system to ensure their relative positional relationship, thereby obtaining a fused trajectory model of the electrode wire in the brain tissue, realizing the visualization rendering of the electrode wire and brain tissue model in implantable stimulation medical surgery.

[0124] In some specific implementations, the method for generating the trajectory of the intracranial electrode wire in the patient further includes: calculating the length of the electrode wire implanted in the patient's cranium based on the curve trajectory equation and using the feature points and feature inflection points corresponding to the electrode wire implanted at the deepest point in the cranium as the endpoints of the electrode implantation.

[0125] Specifically, the length of the electrode wire implanted in the patient's brain can be calculated using an integral method. For example, the length of the tangent at each of the two endpoints and each feature point between the two endpoints can be calculated using the curve trajectory equation, and then the length of the electrode wire implanted in the patient's brain can be obtained by integrating along the range of the two endpoints.

[0126] The above length is the actual length of the electrode wire implanted in the patient's skull. Before performing implantable stimulation surgery, doctors will pre-plan an estimated length for the electrode wire implanted in the patient's skull. By comparing the actual length with the estimated length, the reliability of implantable stimulation surgery can be verified.

[0127] In a second aspect of this embodiment, an apparatus for generating intracranial electrode lead trajectories is provided, which applies the generation method of the first aspect and combines it with the attached... Figure 7 As shown, the generating device includes an image acquisition module 100, a feature point extraction module 200, a target feature point acquisition module 300, and a guide trajectory generation module 400.

[0128] The image acquisition module 100 is used to acquire medical imaging data of the patient's brain after the intracranial electrode wire is implanted.

[0129] The feature point extraction module 200 is used to extract the set of feature points corresponding to the electrode wires from medical image data.

[0130] The target feature point acquisition module 300 is used to select the target feature point set to be implanted in the patient's skull from the feature point set based on the trajectory characteristics of the electrode wire in the patient's skull. The trajectory characteristics at least indicate that the bending degree of the electrode wire in the patient's skull does not exceed a preset bending value.

[0131] The conductor trajectory generation module 400 is used to simulate the trajectory of the electrode conductor inside the patient's skull based on the target feature point set.

[0132] This device utilizes the orientation of the electrode leads within the skull. By comparing preset bending values ​​with the degree of bending of the electrode leads within the skull, it can accurately identify the intracranial electrode lead portion. Using the points corresponding to the intracranial electrode lead portion, it can perform precise three-dimensional visualization rendering of the intracranial electrode lead, enabling doctors to better understand the positional relationship between the intracranial electrode lead and the surrounding nerve fiber bundles. This helps doctors optimize programming parameters and improve treatment outcomes.

[0133] In a third aspect of this embodiment, an implantable medical system 1 is provided, in conjunction with an appendix. Figure 8 As shown, the implantable medical system 1 includes a first processor 11 and a display screen 12.

[0134] The first processor 11 is configured to communicate with the medical acquisition device 20 and execute the generation method of the first aspect, the medical acquisition device 20 being used to acquire medical image data of a patient.

[0135] The display screen 12 is configured to display medical imaging data, which includes at least a set of CT images obtained from at least one computed tomography CT scan of the patient's brain after the implantation of an intracranial electrode lead and the trajectory of the electrode lead in the patient's brain.

[0136] This application obtains precise intracranial electrode wire trajectory through the first processor 11 and uses the display screen 12 to realize three-dimensional visualization rendering of the electrode wire trajectory in the patient's brain, which can be better applied to assisted programmed treatment and improve the treatment effect of implantable medical systems.

[0137] A fourth aspect of this embodiment provides a computer-readable storage medium on which a computer program is stored, wherein when the computer program is executed by a second processor, it implements the steps of the generation method of the first aspect.

[0138] In a fifth aspect of this embodiment, a computer program product is provided, the computer program product including instructions that, when executed on an electronic device, cause the electronic device to implement the steps of the generation method of the first aspect.

[0139] It is understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on the medical device. In other embodiments of this application, the medical device may include more or fewer components, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0140] The first processor 11 and / or the second processor may include one or more processing units, such as processing modules or circuits of a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), a micro-programmed control unit (MCU), an AI (Artificial Intelligence) processor, or a field-programmable gate array (FPGA). Different processing units may be independent devices or integrated into one or more processors. The first processor 11 and / or the second processor may include storage units for storing instructions and data. In some embodiments, the storage units in the first processor 11 and / or the second processor are cache memories.

[0141] Various embodiments of the mechanisms disclosed in this application can be implemented in hardware, software, firmware, or a combination of these implementation methods. Embodiments of this application can be implemented as computer programs or program code executable on a programmable system, the programmable system including at least one third processor, a storage system (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device.

[0142] Program code can be applied to input instructions to execute the functions described in this application and generate output information. The output information can be applied to one or more output devices in a known manner. For the purposes of this application, the processing system includes any system having a processor such as, for example, a digital signal processor (DSP), a microcontroller, an application-specific integrated circuit (ASIC), or a microprocessor.

[0143] The program code can be implemented using a high-level procedural language or an object-oriented programming language to communicate with the processing system. Assembly language or machine language can also be used when needed. In fact, the mechanisms described in this application are not limited to any particular programming language. In either case, the language can be a compiled language or an interpreted language.

[0144] In some cases, the disclosed embodiments may be implemented in hardware, firmware, software, or any combination thereof. The disclosed embodiments may also be implemented as instructions carried or stored thereon on one or more temporary or non-temporary machine-readable (e.g., computer-readable) storage media, which may be read and executed by one or more processors. For example, the instructions may be distributed via a network or through other computer-readable media. Therefore, machine-readable media may include any mechanism for storing or transmitting information in a machine-readable (e.g., computer-readable) form, including but not limited to floppy disks, optical disks, CD-ROMs, magneto-optical disks, read-only memory (ROM), random access memory (RAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic cards or optical cards, flash memory, or tangible machine-readable storage for transmitting information (e.g., carrier waves, infrared signals, digital signals, etc.) using the Internet in the form of electrical, optical, acoustic, or other propagation signals. Therefore, machine-readable media include any type of machine-readable medium suitable for storing or transmitting electronic instructions or information in a machine-readable (e.g., computer-readable) form.

[0145] In the accompanying drawings, some structural or methodological features may be shown in a specific arrangement and / or order. However, it should be understood that such a specific arrangement and / or order may not be necessary. Rather, in some embodiments, these features may be arranged in a manner and / or order different from that shown in the illustrative drawings. Furthermore, the inclusion of structural or methodological features in a particular figure does not imply that such features are required in all embodiments, and in some embodiments, these features may be omitted or may be combined with other features.

[0146] It should be noted that all units / modules mentioned in the device embodiments of this application are logical units / modules. Physically, a logical unit / module can be a physical unit / module, a part of a physical unit / module, or a combination of multiple physical units / modules. The physical implementation of these logical units / modules themselves is not the most important factor; the combination of functions implemented by these logical units / modules is the key to solving the technical problems proposed in this application. Furthermore, to highlight the innovative aspects of this application, the above-described device embodiments of this application have not introduced units / modules that are not closely related to solving the technical problems proposed in this application. This does not mean that the above-described device embodiments do not contain other units / modules.

[0147] It should be noted that in the examples and description of this patent, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one" does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0148] Although this application has been illustrated and described with reference to certain preferred embodiments thereof, those skilled in the art should understand that various changes in form and detail may be made thereto without departing from the spirit and scope of this application.

[0149] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the invention without departing from the principles and spirit of the invention, and all such changes should fall within the protection scope of the claims of the present invention.

Claims

1. A method for generating intracranial electrode lead trajectories, characterized in that, The method includes: Acquire medical imaging data of the patient's brain after intracranial electrode leads are implanted; Extract the set of feature points corresponding to the electrode wires from the medical image data; Based on the trajectory characteristics of the electrode wire in the patient's skull, a set of target feature points to be implanted in the patient's skull is selected from the set of feature points. The trajectory characteristics at least indicate that the degree of curvature of the electrode wire in the patient's skull does not exceed a preset curvature value. Based on the target feature point set, the trajectory of the electrode wires inside the patient's skull is simulated.

2. The generation method according to claim 1, characterized in that, Based on the trajectory characteristics of the electrode wire within the patient's skull, a set of target feature points for implantation into the patient's skull is selected from the set of feature points, including: Starting from the feature point corresponding to the electrode wire implanted deepest in the cranium, calculate the degree of curvature of the electrode wire between any three adjacent feature points in all feature points. When the degree of curvature is greater than the preset curvature value, the characteristic inflection point of the electrode wire implantation into the patient's skull is determined from the characteristic points corresponding to the degree of curvature. Based on the feature inflection point, the target feature point set is obtained by filtering from the feature point set.

3. The generation method according to claim 2, characterized in that, Calculate the degree of bending of the electrode wire between any three adjacent feature points among all feature points, including: Obtain the spatial coordinates of any three adjacent feature points; Based on the spatial coordinates of two adjacent feature points in any three adjacent feature points, calculate the first direction vector and the second direction vector between the two adjacent feature points in sequence. Calculate the dot product of the first direction vector and the second direction vector, and use the dot product as the degree of curvature of the electrode wire between three adjacent feature points.

4. The generation method according to claim 1, characterized in that, Based on the trajectory characteristics of the electrode wire within the patient's skull, a set of target feature points for implantation into the patient's skull is selected from the set of feature points, including: The initial electrode trajectory of the electrode wire is obtained by fitting the spatial coordinates of each feature point in the feature point set. Based on the trajectory characteristics of the electrode wire in the patient's skull, determine the range of the electrode trajectory slope of the portion of the electrode wire implanted in the skull; Based on the range of electrode trajectory slopes and the trajectory slopes at different positions of the initial electrode trajectory, at least a portion of the initial electrode trajectory is extracted to obtain the target electrode trajectory. Based on the feature points in the target electrode trajectory, determine the set of target feature points to be implanted into the patient's skull.

5. The generation method according to claim 3 or 4, characterized in that, Based on the target feature point set, the trajectory of the electrode wires within the patient's cranium is simulated, including: Based on the spatial coordinates of each feature point in the target feature point set, the curve trajectory equation of the electrode wire in the patient's skull is fitted to obtain the equation of the curve trajectory of the electrode wire in the patient's skull. The trajectory of the electrode wires inside the patient's skull is determined based on the curve trajectory equation and the brain environment information inside the patient's skull.

6. The generation method according to claim 5, characterized in that, The method further includes: Based on the curve trajectory equation, and taking the feature point corresponding to the deepest electrode wire implanted in the cranium and the feature inflection point as the endpoint of the electrode implantation, the length of the electrode wire implanted in the patient's cranium is calculated.

7. The generation method according to claim 1, characterized in that, The medical imaging data includes at least a set of CT images obtained by scanning along at least one computed tomography (CT) scan direction.

8. The generation method according to claim 7, characterized in that, The method for obtaining the spatial coordinates of the feature points includes: For each electrode wire and its corresponding image identifier, obtain at most one feature point corresponding to the electrode wire in each CT image of the CT image set; The spatial coordinates of each feature point are determined based on the voxel coordinates corresponding to each feature point.

9. The generation method according to claim 7, characterized in that, The CT scan directions include sagittal and coronal planes.

10. A device for generating intracranial electrode lead trajectories, characterized in that, The generating apparatus includes: Image acquisition module: used to acquire medical imaging data of the patient's brain after intracranial electrode leads are implanted; Feature point extraction module: used to extract the set of feature points corresponding to the electrode wires from the medical image data; Target feature point acquisition module: Based on the trajectory characteristics of the electrode wire in the patient's skull, filter out the target feature point set to be implanted in the patient's skull from the feature point set, wherein the trajectory characteristics at least indicate that the bending degree of the electrode wire in the patient's skull does not exceed a preset bending value; Conductor trajectory generation module: used to simulate the trajectory of the electrode conductor in the patient's skull based on the target feature point set.

11. An implantable medical system, characterized in that, The implantable medical system includes: A first processor is configured to communicate with a medical acquisition device and execute the method according to any one of claims 1 to 9, wherein the medical acquisition device is used to acquire medical image data of a patient; The display screen is configured to display the medical imaging data, which includes at least a set of CT images obtained from at least one computed tomography (CT) scan of the patient's brain after intracranial electrode wires have been implanted, and the trajectory of the electrode wires within the patient's brain.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a second processor, implements the steps of the method as described in any one of claims 1 to 9.

13. A computer program product, characterized in that, The computer program product includes instructions that, when executed on an electronic device, cause the electronic device to perform the steps of the method according to any one of claims 1 to 9.

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