Deep brain stimulation parameter recommendation system and method and storage medium

Abstract

The invention discloses a brain deep stimulation parameter recommendation system and method and a storage medium. The method comprises the following steps: determining each recommended electrode combination corresponding to a target stimulation target in the brain of the target object according to the target brain image through the processor, and selecting the target stimulation target in the brain of the target object according to a recommended stimulation parameter set of each recommended electrode combination and a preset screening condition set for the recommended stimulation parameter set, target stimulation parameters for stimulating the target stimulation target are determined, and the preset screening conditions at least comprise a stimulation range screening condition and a side effect screening condition. According to the invention, through systematic analysis of the spatial and functional relationship between the nervous system and the electrode slice, an accurate stimulation treatment window range is provided for electrical stimulation treatment, so that the accuracy and efficiency of electrical stimulation treatment are improved.

Description

Technical Field

[0001] This invention relates to the field of medical electrode stimulation technology, and in particular to a deep brain stimulation parameter recommendation system, method, and storage medium. Background Technology

[0002] With the development of brain nerve electrical stimulation technology, this technology has shown significant clinical value in the treatment of neurological diseases such as Parkinson's disease, epilepsy, and depression.

[0003] However, in current electrical stimulation therapy, doctors mainly rely on experience or indirect imaging data to select electrode combinations and electrical stimulation parameters. This traditional approach lacks a direct visual representation of the relationship between the precise location of nerve fibers and the electrode pads or nuclei, making it difficult to accurately locate the optimal treatment window; adjusting electrical stimulation parameters is time-consuming and requires multiple trials, increasing patient discomfort and time costs; and the treatment effect may be limited by inaccurate positioning or inappropriate parameter selection.

[0004] Therefore, there is an urgent need for a technique to determine the treatment window based on the spatial location analysis of the patient's nerve fibers, electrode pads, and nuclei. Summary of the Invention

[0005] This invention provides a deep brain stimulation parameter recommendation system, method, and storage medium to provide a precise stimulation window range for electrical stimulation therapy through a systematic analysis of the spatial and functional relationship between the nervous system and electrode pads, thereby improving the accuracy and efficiency of electrical stimulation therapy.

[0006] According to one aspect of the present invention, a deep brain stimulation parameter recommendation system is provided. The system includes a memory and a processor, wherein...

[0007] The memory is configured to store target brain images of the target subject after electrode implantation.

[0008] The processor is configured to determine, based on the target brain image, various recommended electrode combinations corresponding to target stimulation points in the brain of the target subject, and to determine target stimulation parameters for stimulating the target stimulation point based on a set of recommended stimulation parameters for each recommended electrode combination and preset screening conditions set for the set of recommended stimulation parameters, wherein the preset screening conditions include at least stimulation range screening conditions and side effect screening conditions.

[0009] According to another aspect of the present invention, a method for recommending deep brain stimulation parameters is provided. This method is applied to a deep brain stimulation parameter recommendation system, the system including a memory and a processor; the method includes:

[0010] The processor, based on target brain images stored in the memory, determines recommended electrode combinations corresponding to target stimulation points in the target brain. Then, based on a set of recommended stimulation parameters for each recommended electrode combination and preset screening conditions set for the recommended stimulation parameter sets, it determines target stimulation parameters for stimulating the target stimulation point. The preset screening conditions include at least stimulation range screening conditions and side effect screening conditions. According to another aspect of the invention, a computer-readable storage medium is provided, storing computer instructions that, when executed by a processor, implement the deep brain stimulation parameter recommendation method according to any embodiment of the invention.

[0011] The technical solution of this invention stores target brain images of the target subject after electrode implantation in a memory. A processor determines recommended electrode combinations corresponding to target stimulation points in the target subject's brain based on these brain images. Then, based on the set of stimulation parameters generated by the recommended electrode combinations and preset screening conditions for these stimulation parameters, the processor determines the target stimulation parameters for stimulating the target stimulation point. The preset screening conditions include at least stimulation range screening conditions and side effect screening conditions. This solves the problem of ambiguity in locating stimulation windows based on traditional experience, reduces human error in determination, shortens the stimulation treatment cycle, provides a precise stimulation treatment window range for electrical stimulation therapy, and improves the accuracy of electrical stimulation therapy.

[0012] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a schematic diagram of a deep brain stimulation parameter recommendation system provided in an embodiment of the present invention;

[0015] Figure 2 This is a schematic diagram of the processor structure provided in an embodiment of the present invention;

[0016] Figure 3 This is a schematic diagram of the stimulation parameter determination module provided in an embodiment of the present invention;

[0017] Figure 4 This is a flowchart of a method for recommending deep brain stimulation parameters according to an embodiment of the present invention;

[0018] Figure 5 This is a schematic diagram of the structure of an electronic device that implements the method for recommending deep brain stimulation parameters according to embodiments of the present invention. Detailed Implementation

[0019] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0020] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0021] One application area of ​​this invention (i.e., implantable devices) will be briefly described. An implantable neurostimulation system (an implantable medical system) mainly includes a stimulator implanted in the patient's body and a programmable device placed outside the patient's body.

[0022] In some embodiments, the stimulator may include an implantable pulse generator (IPG), electrode leads, and an extension lead disposed between the pulse generator and the electrode leads, through which data interaction between the pulse generator and the electrode leads is achieved. The pulse generator is disposed within the patient's body. Responding to programmed commands sent by a programmable device, controllable electrical stimulation energy is provided to the body's tissues via a sealed battery and circuitry. One or two controllable electrical stimuli are delivered to specific areas of the body's tissues via the implanted extension lead and electrode leads. The extension lead, used in conjunction with the pulse generator, serves as a medium for transmitting electrical stimulation signals, conveying the electrical stimulation signals generated by the pulse generator to the electrode leads. The electrode leads deliver electrical stimulation to specific areas of the body's tissues through their electrode contacts. The stimulator has one or more electrode leads on one or both sides, and each electrode lead has multiple electrode contacts.

[0023] In other embodiments, the stimulator may consist only of a pulse generator and electrode leads. In this case, the pulse generator may be embedded in the patient's skull, and the electrode leads may be implanted intracranially, with the pulse generator and electrode leads directly connected without the need for extension leads.

[0024] The electrode leads can be neurostimulation electrodes, delivering electrical stimulation to specific areas of tissue within the body via multiple electrode contacts. The stimulator has one or more electrode leads on one or both sides, with multiple electrode contacts on each lead. These contacts can be evenly or non-uniformly arranged circumferentially on the electrode leads. As an example, the electrode contacts can be arranged in a 4x3 array (a total of 12 contacts) circumferentially on the electrode leads. The electrode contacts can include stimulation contacts and / or acquisition contacts. The electrode contacts can be, for example, sheet-like, ring-like, or dot-like shapes.

[0025] In some possible approaches, the stimulated tissue can be the patient's brain tissue, and the stimulated site can be a specific area of ​​the brain tissue. Generally, the stimulated site differs depending on the patient's disease type, as well as the number of stimulation contacts (single-source or multi-source), the application of one or more specific electrical stimulation signals (single-channel or multi-channel), and the stimulation parameter data. It can be assumed that using multiple stimulation contacts (multi-source, multi-channel) will generate a larger amount of data compared to using a single-source, single-channel approach.

[0026] The embodiments of this invention do not limit the types of diseases to which they are applicable, but can include those applicable to deep brain stimulation (DBS), spinal cord stimulation (SCS), pelvic stimulation, gastric stimulation, peripheral nerve stimulation, and functional electrical stimulation. Specifically, 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 disorders and impairments.

[0027] Stimulation parameters may include: frequency (e.g., the number of electrical stimulation pulses per second, in Hz), pulse width (the 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 triggered), 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 physicians can adjust), and patient control upper and lower limits (the range that patients can adjust independently).

[0028] Figure 1 This is a schematic diagram of a deep brain stimulation parameter recommendation system provided in an embodiment of the present invention. This embodiment can be applied to determining the electrode stimulation window for electrode implantation. Figure 1 As shown, the system includes a memory and a processor.

[0029] The memory is configured to store target brain images of the target subject after electrode implantation.

[0030] The processor is configured to determine, based on the target brain image, various recommended electrode combinations corresponding to target stimulation points in the target brain, and to determine target stimulation parameters for stimulating the target stimulation point based on a set of recommended stimulation parameters for each recommended electrode combination and preset screening conditions set for the set of recommended stimulation parameters.

[0031] The target subject can refer to the individual undergoing electrode stimulation therapy (e.g., a medical patient or test subject) or to an individual who has already had electrodes implanted. The target brain image can refer to magnetic resonance imaging (MRI) data of the target subject's brain; for example, the target brain image can include MRI images and diffusion tensor images. The target stimulation point can refer to the brain target point on which the target subject will be subjected to brain electrode stimulation. It should be noted that the target stimulation point may differ for different target subjects at different treatment stages and needs to be determined based on the actual medical condition of the target subject. The target stimulation parameters can refer to the optimal stimulation parameters for medical stimulation of the target stimulation point, or the optimal stimulation window for medical stimulation of the target stimulation point.

[0032] In addition, it should be noted that the preset screening conditions include at least the stimulation range screening conditions and the side effect screening conditions. Based on the preset screening conditions, the optimal target stimulation parameters can be selected from multiple candidate stimulation parameters.

[0033] In fact, brain imaging data of the target subject after electrode implantation is acquired by magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI), and the target brain image is obtained and stored in the memory so as to determine the stimulation treatment window for different stimulation targets.

[0034] When it is necessary to determine the target stimulation parameters, the processor retrieves the target brain image from memory and analyzes the distribution of each stimulation electrode implanted in the brain. Based on the location information of the target stimulation point and the distribution of each stimulation electrode, recommended electrode combinations that have a stimulating effect on the target stimulation point are determined. According to preset screening conditions (such as stimulation range screening conditions and side effect screening conditions), the recommended electrode combinations can be screened to obtain the target stimulation parameters. Through systematic analysis of the spatial and functional relationship between the nervous system and the electrode pads, a precise stimulation treatment window range is provided for electrical stimulation therapy, thereby improving the accuracy and efficiency of electrical stimulation therapy.

[0035] The technical solution of this invention stores target brain images of the target subject after electrode implantation in a memory. A processor determines recommended electrode combinations corresponding to target stimulation points in the target subject's brain based on these brain images. Then, based on the set of stimulation parameters generated by the recommended electrode combinations and preset screening conditions for these stimulation parameters, the processor determines the target stimulation parameters for stimulating the target stimulation point. The preset screening conditions include at least stimulation range screening conditions and side effect screening conditions. This solves the problem of ambiguity in locating stimulation windows based on traditional experience, reduces human error in determination, shortens the stimulation treatment cycle, provides a precise stimulation treatment window range for electrical stimulation therapy, and improves the accuracy of electrical stimulation therapy.

[0036] Figure 2 This is a schematic diagram of the processor provided in an embodiment of the present invention, such as... Figure 2 As shown, the processor includes an electrode combination determination module and a stimulation parameter determination module, etc.

[0037] For example, the electrode combination determination module is configured to include:

[0038] A brain model construction unit is used to construct a target brain model of the target object's brain based on the target brain image;

[0039] The electrode combination determination unit is used to determine, based on the target brain model of the target brain, recommended electrode combinations corresponding to the target stimulation target points to be stimulated in the target brain from the various stimulation electrodes already implanted in the target brain.

[0040] It should be noted that the target brain model includes at least a three-dimensional nucleus model and a three-dimensional electrode model. The nuclei function by transmitting signals through the nerve fibers connected to them, establishing a correspondence between nerve fibers and nuclei. Nuclei are key nodes in the nervous system, influencing various physiological functions of the target object, such as sensory and motor functions, all of which can be associated with nuclei.

[0041] Specifically, the brain model construction unit can construct a neural fiber distribution model of the target object based on target brain images using neural fiber tracking algorithms, forming a basic dataset reflecting the structure and function of neural pathways. It also labels the nuclei connected to by different neural fiber bundles, forming a three-dimensional nucleus model.

[0042] Based on target brain imaging, the three-dimensional position, geometry, and orientation information of the implanted electrode pads are acquired to construct a three-dimensional electrode model. As previously described, the electrode pads are positioned on electrode leads to deliver electrical stimulation to the target brain, stimulating corresponding areas to achieve therapeutic purposes.

[0043] Furthermore, based on information such as the material properties and design parameters of the electrode pads, the range and intensity variation characteristics of their electric field distribution are defined. That is, according to the location of the electrode pads in the brain, combined with the given stimulation parameters (such as pulse amplitude, frequency, and pulse width), the electric field range corresponding to the stimulation parameters can be determined, and a functional model of the interaction between the electrode pads and the nervous system can be established. Specifically, the three-dimensional nucleus model and the three-dimensional electrode model are registered to obtain the target brain model, ensuring that the nerve fiber model can be aligned with the electrode pad model for subsequent analysis.

[0044] The electrode combination determination unit is used to analyze the range of nerve fibers that the electrode pads can cover by using a target brain model and the spatial relationship between the nerve fiber model and the electrode pad model. It analyzes which areas in the neural network functional pathway can be directly acted upon by the implanted electrode pads. In other words, through the signal transmission function of nerve fibers, it can determine which tissues (such as nuclei and other neural tissues) the electrical signals released by the electrode pads can be transmitted to. Then, it determines the recommended electrode combinations corresponding to the target stimulation points in the target brain from the various stimulation electrodes already implanted in the target brain.

[0045] For example, the electrode combination determining unit is configured specifically for:

[0046] Based on the target brain model of the target subject's brain and the target location information of the target stimulation target, each target stimulation electrode that matches the range of the target stimulation target is determined from the various stimulation electrodes implanted in the target subject's brain; the various target stimulation electrodes are combined to obtain various recommended electrode combinations.

[0047] It's important to note that before the implantation surgery, the doctor diagnoses the target patient's condition, determines the disease type, and then identifies the target stimulation points (generally referring to nuclei, such as the subthalamic nucleus corresponding to Parkinson's symptoms) based on the disease type. Then, based on the identified target stimulation points, the electrode implantation surgery is performed. After the surgery, at least one electrode contact will be implanted into the target stimulation point. Based on the positional relationship between the electrode contacts in the electrode leads and the target stimulation point, the individual target stimulation electrodes located at the target stimulation point are determined. Multiple recommended electrode combinations are then determined based on the set of target stimulation electrodes. Each recommended electrode combination includes at least one electrode contact. For example, if the stimulation electrode set includes three stimulation electrodes (A, B, and C), then there are seven recommended electrode combinations: A, AB, AC, ABC, B, BC, and C.

[0048] Figure 3 This is a schematic diagram of the stimulation parameter determination module provided in an embodiment of the present invention, as shown below. Figure 3As shown, the stimulus parameter determination module includes a first parameter determination unit, a second parameter determination unit, and a target parameter determination unit.

[0049] For example, the functions of each unit are as follows:

[0050] The first parameter determination unit is used to determine the first set of stimulation parameters corresponding to each of the recommended electrode combinations based on the recommended electrode combinations and the target coordinates of the target stimulation target.

[0051] The second parameter determination unit is used to determine the second stimulus parameter set from the first stimulus parameter set based on the electric field stimulation range corresponding to each first stimulus parameter in the first stimulus parameter set and the preset overlap threshold.

[0052] The target parameter determination unit is used to determine the target stimulus parameter from the second stimulus parameter set based on the stimulus side effect corresponding to each second stimulus parameter in the second stimulus parameter set.

[0053] Wherein, the first stimulation parameter can refer to a stimulation parameter capable of stimulating the target stimulation point. The second stimulation parameter can refer to a first stimulation parameter whose stimulation range conforms to a preset specification. The target stimulation parameter can refer to a second stimulation parameter whose stimulation side effects conform to a preset specification. The preset overlap threshold is determined based on the target stimulation point range. The overlap rate between the electric field stimulation range corresponding to each second stimulation parameter in the set of second stimulation parameters and the target stimulation point is not less than the preset overlap threshold.

[0054] Specifically, the first parameter determination unit compares the stimulation range of the stimulation parameters that the recommended electrode combination can generate with the target coordinates of the target stimulation point to select a first set of stimulation parameters from the stimulation parameters that the recommended electrode combination can generate. The second parameter determination unit compares the overlap between the electric field stimulation range of the first set of stimulation parameters and the stimulation range of the target stimulation point with a preset overlap threshold to determine a second set of stimulation parameters from the first set of stimulation parameters. The target parameter determination unit selects the target stimulation parameters that meet the requirements from the second set of stimulation parameters based on the stimulation side effects corresponding to the second set of stimulation parameters.

[0055] For example, the second parameter determining unit is configured to: compare the electric field stimulation range corresponding to each of the first stimulation parameters with the target stimulation range required for the target stimulation point; and determine the first stimulation parameter whose overlap rate between the electric field stimulation range and the target stimulation range is greater than the preset overlap threshold as the second stimulation parameter.

[0056] In other words, based on the target stimulation range required for the target stimulation point, the first stimulation parameter of each electrode contact combination is screened to obtain the second stimulation parameter. The overlap rate between the electric field range corresponding to the second stimulation parameter and the target stimulation range required for the target stimulation point must not be lower than a preset overlap threshold, such as not lower than 80%. This ensures that the stimulation parameter corresponding to each electrode contact combination is reasonable and effective, and can effectively stimulate the nucleus.

[0057] For example, the second parameter determining unit further includes a stimulus range determining subunit; the stimulus range determining subunit is configured to:

[0058] Determine the stimulation parameters of each target stimulation electrode in the recommended electrode combination corresponding to the first stimulation parameter;

[0059] Based on the stimulation parameters of each target stimulation electrode and the standard stimulation range of each target stimulation electrode, the actual stimulation range corresponding to each target stimulation electrode is determined.

[0060] By superimposing all the actual stimulation ranges, the electric field stimulation range corresponding to the first stimulation parameter is determined.

[0061] The standard stimulation range can refer to the range of stimulation that can be achieved by the stimulation parameters generated by each target stimulation electrode. The actual stimulation range can refer to the range of stimulation that can be achieved by the combination of the first stimulation parameters.

[0062] Specifically, the standard electric field range of each target stimulation electrode (i.e., the electric field range of the same stimulation parameter) is obtained through simulation. Then, through the principles of electric field superposition and proportional scaling, the electric field range of the recommended electrode combination is adjusted to the corresponding range, thereby obtaining the electric field stimulation range corresponding to the first stimulation parameter.

[0063] For example, the target parameter determination unit is configured to: for each second stimulation parameter, determine the set of nerve fibers that can be covered by the electric field range corresponding to the second stimulation parameter; determine the set of stimulation side effects caused by the second stimulation parameter based on the set of nerve fibers; and determine the second stimulation parameter with the least stimulation side effects as the target stimulation parameter.

[0064] It should be noted that different combinations of electrode contacts correspond to different electric field ranges, and therefore the nerve fibers they cover may also differ. Therefore, when the electric field range covers some unrelated nerve fibers, it may activate these fibers, causing them to malfunction (unnecessarily activated by an external electric field), transmitting electrical signals to other nuclei, ultimately causing those nuclei to transition from a normal to an abnormal state, thus causing side effects. Here, it is necessary to combine the distribution of nerve fibers in the brain obtained above to determine the set of nerve fibers that the electric field range corresponding to the second stimulation parameter can cover. Then, within this set of nerve fibers, identify the set of stimulation side effects caused by the second stimulation parameter. The second stimulation parameter with the fewest side effects is then identified as the target stimulation parameter. This final target stimulation parameter is recommended to the doctor, allowing the doctor to determine whether to output stimulation to the target individual.

[0065] For example, the target parameter determination unit further includes a stimulation side effect determination subunit; the stimulation side effect determination subunit is configured to: determine a first set of nerve fibers activated by the second stimulation parameter based on the set of nerve fibers, wherein different nerve fibers have different activation conditions, and the activation conditions include at least electric field strength and stimulation duration; determine a set of first nuclei abnormally stimulated by the second stimulation parameter based on the conduction path of each first nerve fiber; and determine the stimulation side effects caused by the second stimulation parameter based on the abnormally stimulated set of first nuclei.

[0066] Specifically, based on the set of nerve fibers that can be covered by the electric field range corresponding to the second stimulation parameter, the set of first nerve fibers that can be activated under the stimulation of the second stimulation parameter is determined. By analyzing the set of first nerve fibers, the set of first nuclei that are abnormally stimulated is determined, and then based on the abnormal working state of the first nuclei set, the set of stimulation side effects caused by the second stimulation parameter is determined.

[0067] For example, determining the second stimulus parameter with the least side effect as the target stimulus parameter includes: determining the side effect intensity corresponding to each second stimulus parameter based on the set of side effects caused by each second stimulus parameter and preset different side effect weights; and determining the second stimulus parameter with the least side effect intensity as the target stimulus parameter.

[0068] Specifically, by considering the set of nerve fibers covered by the electric field range of the second stimulation parameter and the set of nerve fibers to be stimulated, the set of stimulation side effects caused by the second stimulation parameter is determined. Based on the side effect weights of each side effect in the set, the intensity of the side effect corresponding to each second stimulation parameter is determined. The second stimulation parameter with the lowest side effect intensity is then identified as the target stimulation parameter.

[0069] The target parameter determination unit further includes a side effect intensity determination subunit; the side effect intensity determination subunit is configured to: determine each stimulus side effect produced by using the second stimulus parameter; and for each stimulus side effect, determine the stimulus side effect intensity corresponding to each second stimulus parameter according to the side effect weight corresponding to the stimulus side effect.

[0070] Specifically, since the electric field range of the stimulation parameter may cover multiple nerve fibers, there may be multiple side effects. Based on a three-dimensional nucleus model, the various stimulation side effects produced by using the second stimulation parameter are determined. Different stimulation side effects are assigned corresponding side effect weights, and then the intensity of the stimulation side effect corresponding to each second stimulation parameter is determined according to the side effect weight corresponding to each stimulation side effect.

[0071] It should be noted that, for the same side effect intensity, stimulation parameters with a larger electric field range will be given priority consideration.

[0072] Side effect screening can be a pre-set screening strategy by the doctor. Different side effects have different degrees of impact on patients. A certain intensity score can be set, and then all the side effects of the recommended stimulation parameters for each electrode contact combination can be determined. The final side effect intensity is determined by adding the intensity scores. The higher the intensity, the greater the impact of the side effect. The side effect with the lowest intensity is taken as the final target stimulation parameter for the final electrode contact combination.

[0073] Additionally, it should be noted that since the activation of nerve fibers also requires certain conditions, such as electric field strength, it is necessary to determine the activation threshold of each covered nerve fiber in addition to determining the range of electric field coverage. This can be based on prior knowledge of neurology. In this way, whether a nerve fiber is activated can be determined based on the strength of the electric field at which it is located. After that, we only need to consider the side effects brought about by the activated nerve fibers.

[0074] The technical solution of this invention provides a three-dimensional visualization of the treatment window range, nerve fiber distribution, and electrode pad location, enabling doctors to intuitively understand the relationship between the stimulation area and the neural functional pathway, simulate the possible effects of electrical stimulation, visually display the treatment window range and stimulation area, predict treatment targeting and potential side effects, and provide real-time auxiliary support for clinical treatment plan development. Simultaneously, it reduces patient discomfort during treatment and improves the stability and controllability of treatment effects.

[0075] Figure 4 This is a flowchart illustrating a method for recommending deep brain stimulation parameters, provided as an embodiment of the present invention. Figure 4 As shown, the method includes:

[0076] S401. Store the target brain image of the target object after electrode implantation through the memory;

[0077] S402. Using a processor, based on the target brain image, determine each recommended electrode combination corresponding to the target stimulation target point in the target brain, and based on the recommended stimulation parameter set for each recommended electrode combination and the preset screening conditions set for the recommended stimulation parameter set, determine the target stimulation parameters for stimulating the target stimulation target point, wherein the preset screening conditions include at least stimulation range screening conditions and side effect screening conditions.

[0078] Specifically, the processor is actually used for:

[0079] S1: Based on the patient's postoperative imaging data, construct a three-dimensional imaging model of the patient's brain. The three-dimensional imaging model includes at least a model of the patient's brain nuclei and an electrode model.

[0080] S2: Based on the three-dimensional image model, determine the set of electrode contacts to be implanted into the target point;

[0081] S3: Determine multiple electrode contact combinations based on the set of electrode contacts;

[0082] S4: Based on each electrode contact combination and the location of the target point, generate at least one recommended stimulation parameter corresponding to each electrode contact combination. The overlap rate between the electric field range corresponding to each recommended stimulation parameter and the target point shall not be lower than a preset threshold.

[0083] S5: Determine the side effects of the recommended stimulation parameters for all electrode contact combinations, and take the recommended stimulation parameter with the lowest side effects as the target recommended stimulation parameter.

[0084] The technical solution of this invention stores target brain images of the target subject after electrode implantation in a memory. A processor determines recommended electrode combinations corresponding to target stimulation points in the target subject's brain based on these brain images. Then, based on the set of stimulation parameters generated by the recommended electrode combinations and preset screening conditions for these stimulation parameters, the processor determines the target stimulation parameters for stimulating the target stimulation point. The preset screening conditions include at least stimulation range screening conditions and side effect screening conditions. This solves the problem of ambiguity in locating stimulation windows based on traditional experience, reduces human error in determination, shortens the stimulation treatment cycle, provides a precise stimulation treatment window range for electrical stimulation therapy, and improves the accuracy of electrical stimulation therapy.

[0085] Figure 5A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0086] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0087] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0088] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the deep brain stimulation parameter recommendation method.

[0089] In some embodiments, the deep brain stimulation parameter recommendation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the deep brain stimulation parameter recommendation method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the deep brain stimulation parameter recommendation method by any other suitable means (e.g., by means of firmware).

[0090] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0091] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0092] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0093] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0094] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0095] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0096] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0097] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A deep brain stimulation parameter recommendation system, characterized in that, Including memory and processor, among which, The memory is configured to store target brain images of the target subject after electrode implantation. The processor is configured to determine, based on the target brain image, various recommended electrode combinations corresponding to target stimulation points in the brain of the target subject, and to determine target stimulation parameters for stimulating the target stimulation point based on a set of recommended stimulation parameters for each recommended electrode combination and preset screening conditions set for the set of recommended stimulation parameters, wherein the preset screening conditions include at least stimulation range screening conditions and side effect screening conditions.

2. The system according to claim 1, characterized in that, The processor includes an electrode combination determination module; wherein the electrode combination determination module is configured to include: A brain model construction unit is used to construct a target brain model of the target object's brain based on the target brain image, wherein the target brain model includes at least a three-dimensional nucleus model and a three-dimensional electrode model; The electrode combination determination unit is used to determine, based on the target brain model of the target brain, recommended electrode combinations corresponding to the target stimulation target points to be stimulated in the target brain from the various stimulation electrodes already implanted in the target brain.

3. The system according to claim 2, characterized in that, The electrode combination determining unit is configured to specifically be used for: Based on the target brain model of the target object's brain and the target location information of the target stimulation target, each target stimulation electrode that matches the range of the target stimulation target is determined from the various stimulation electrodes implanted in the target object's brain. The various target stimulation electrodes are combined to obtain various recommended electrode combinations.

4. The system according to claim 1, characterized in that, The processor includes a stimulus parameter determination module; wherein the stimulus parameter determination module is configured to include: The first parameter determination unit is used to determine the first set of stimulation parameters corresponding to each of the recommended electrode combinations based on the recommended electrode combinations and the target point coordinates of the target stimulation target points. The second parameter determination unit is used to determine a second stimulation parameter set from the first stimulation parameter set based on the electric field stimulation range corresponding to each first stimulation parameter in the first stimulation parameter set and a preset overlap threshold, wherein the overlap rate between the electric field stimulation range corresponding to each second stimulation parameter in the second stimulation parameter set and the target stimulation point is not less than the preset overlap threshold. The target parameter determination unit is used to determine the target stimulus parameter from the second stimulus parameter set based on the stimulus side effect corresponding to each second stimulus parameter in the second stimulus parameter set.

5. The system according to claim 4, characterized in that, The second parameter determining unit is configured to specifically be used for: Compare the electric field stimulation range corresponding to each of the first stimulation parameters with the target stimulation range required for the target stimulation point; The first stimulation parameter, whose overlap rate with the electric field stimulation range is greater than the preset overlap threshold, is determined as the second stimulation parameter set.

6. The system according to claim 5, characterized in that, The second parameter determining unit further includes a stimulus range determining subunit; the stimulus range determining subunit is configured to: Determine the stimulation parameters of each target stimulation electrode in the recommended electrode combination corresponding to the first stimulation parameter; Based on the stimulation parameters of each target stimulation electrode and the standard stimulation range of each target stimulation electrode, the actual stimulation range corresponding to each target stimulation electrode is determined. By superimposing all the actual stimulation ranges, the electric field stimulation range corresponding to the first stimulation parameter is determined.

7. The system according to claim 4, characterized in that, The target parameter determination unit is configured to specifically be used for: For each of the second stimulation parameters, determine the set of nerve fibers that the electric field range corresponding to the second stimulation parameter can cover; Based on the set of nerve fibers, determine the set of stimulation side effects caused by the second stimulation parameter; The second stimulation parameter that has the least side effect is determined as the target stimulation parameter.

8. The system according to claim 7, characterized in that, The second stimulus parameter, which minimizes side effects, is determined as the target stimulus parameter, including: Based on the set of stimulus side effects caused by each second stimulus parameter and the preset different side effect weights, the intensity of the side effect corresponding to each second stimulus parameter is determined. The second stimulation parameter with the least side effect intensity was determined as the target stimulation parameter.

9. The system according to claim 7, characterized in that, The target parameter determination unit further includes a stimulus side effect determination subunit; the stimulus side effect determination subunit is configured to: Based on the set of nerve fibers, a first set of nerve fibers activated by the second stimulation parameter is determined, wherein different nerve fibers have different activation conditions, and the activation conditions include at least electric field strength and stimulation duration. Based on the conduction path of each of the first nerve fibers, determine the set of first nuclei that are abnormally stimulated by the second stimulation parameters; Based on the first set of nuclei that are abnormally stimulated, determine the set of stimulation side effects caused by the second stimulation parameter.

10. The system according to claim 7, characterized in that, The target parameter determination unit further includes a side effect intensity determination subunit; the side effect intensity determination subunit is configured to: Identify the individual stimulus side effects produced by using the second stimulus parameter; For each of the aforementioned stimulus side effects, the intensity of the stimulus side effect corresponding to each of the second stimulus parameters is determined based on the side effect weight corresponding to the stimulus side effect.

11. A method for recommending deep brain stimulation parameters, characterized in that, A method for recommending parameters for deep brain stimulation is used, the system comprising a memory and a processor; the method includes: The processor determines recommended electrode combinations corresponding to target stimulation points in the target brain based on target brain images stored in the memory, and determines target stimulation parameters for stimulating the target stimulation point based on a set of recommended stimulation parameters for each recommended electrode combination and preset screening conditions set for the recommended stimulation parameter set. The preset screening conditions include at least stimulation range screening conditions and side effect screening conditions.

12. An implantable deep brain stimulation system, characterized in that, The system includes: A pulse generator (stimulator) is implanted into the user's body and connected to an implanted electrode that is at least partially implanted into a target site in the user's brain. The pulse generator is used to deliver electrical stimulation to the target site through the implanted electrode. A programmable device, communicatively connected to the pulse generator, includes the system according to any one of claims 1 to 10 or performs the method according to claim 11, to obtain target stimulation parameters and send the target stimulation parameters to the pulse generator, so that the pulse generator delivers the electrical stimulation corresponding to the target stimulation parameters to the target target point.

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