DBS procedure optimization using pre-specified contact selection

Abstract

Methods and systems for planning configurations of neuromodulation systems having leads with multiple electrodes. The configurations are planned using an optimizer that analyzes potential segmentations after removing unavailable electrodes and adjusting candidate segmentations to compensate for the removed electrodes according to an analysis. The unavailable electrodes can be identified by a physician or by analyzing the impedance of the electrodes.

Description

Cross-reference to related applications

[0001] This application claims the benefit of U.S. Provisional Patent Application Serial No. 63 / 595,572, filed November 2, 2023, the disclosure of which is incorporated herein by reference. Background Technology

[0002] Deep brain stimulation (DBS) is a form of neuromodulation in which electrodes are implanted in a patient's brain to deliver stimulation. Treatments for a variety of conditions, including Alzheimer's disease, Parkinson's disease, cognitive and / or memory decline, depression, and others, have been proposed and / or implemented. Each patient has a unique anatomy, and each treated condition may require different parts of the brain to receive treatment. Therefore, accurate and precise targeted therapy is desired.

[0003] For various reasons, one or more electrodes in a given implanted system may become unusable for treatment delivery. For example, the impedance at each electrode is typically monitored during use and compared to an impedance range; if the impedance at a given electrode is outside the range, that electrode may be disabled and marked as unusable by the system. For example, high impedance may indicate a break in the conductor providing the electrical connection between the pulse generator and the electrode. A physician may decide to mark an electrode as unusable as needed. Typical responses to an electrode becoming unusable might include, for example, disabling any treatment procedure that uses the electrode as an anode or cathode. New and alternative methods and systems are expected to address unusable electrodes more rigorously in treatment planning. Summary of the Invention

[0004] The inventors have recognized, among other things, the need to address the requirement for new and / or alternative systems and methods that more rigorously handle unavailable electrodes in treatment planning. In an illustrative example, the treatment plan is modified to adjust guidance and current distribution strategies during the optimization of the treatment goal setting process.

[0005] The first illustrative and non-limiting example takes the form of a configuration system for configuring the delivery of neuromodulation to a specific tissue of a patient via an implantable system having multiple electrodes. The configuration system includes: a receiver module configured to receive at least patient data and lead positions indicating the location of leads carrying at least two of the multiple electrodes relative to the patient's neural tissue; an optimizer for identifying a set of candidate treatment parameters indicative of the utilization of the multiple electrodes during treatment, the optimizer including: a guidance module for identifying a potential subdivision to be analyzed, the potential subdivision setting a proportion of the total current emitted by each electrode; an electrode removal module that receives the potential subdivision and removes unusable electrodes from the potential subdivision to generate a reduced subdivision; an adjustment module that receives the reduced subdivision and creates an adjusted subdivision; a scoring module that receives the adjusted subdivision and calculates multiple metrics of the adjusted subdivision using multiple amplitude settings; and a candidate module that uses the multiple metrics to identify one or more candidate treatments.

[0006] Alternatively or additionally, the optimizer is configured to use a guidance module to identify multiple potential subdivisions.

[0007] Alternatively or additionally, the potential segmentation identifies active and inactive electrodes, and the adjustment module creates the adjusted segmentation by proportionally increasing the current segmentation delivered by each active electrode not removed by the electrode removal module.

[0008] Alternatively or additionally, the potential subdivision identifies active and inactive electrodes, and the adjustment module modifies the current subdivision by adding current to the active electrode in proportion to the proximity of the inactive electrode. Alternatively or additionally, this proportion is based on a Gaussian curve.

[0009] Alternatively or additionally, the electrode removal module removes electrodes with impedance outside the impedance range.

[0010] Alternatively or additionally, the electrode removal module removes electrodes that have been identified as unusable by the physician.

[0011] Additionally or alternatively, the electrode removal module is configured to identify electrodes that can be removed by recognizing those that are less than a threshold proximity to a neural structure and suggesting electrode removal to a physician via a user interface.

[0012] Additionally or alternatively, the electrode removal module is configured to identify removable electrodes by recognizing electrodes with impedance outside the impedance range and suggesting electrode removal to the physician via a user interface.

[0013] Additionally or alternatively, the system may also include a voxel calculation module that identifies the volume around the lead as voxels and marks at least some voxels as target voxels for treatment.

[0014] Additionally or alternatively, the voxel calculation module will also mark at least some voxels as avoidable voxels to be avoided in treatment.

[0015] Alternatively, the scoring module may calculate multiple metrics by determining which voxels will be activated under adjusted subdivision at multiple current amplitudes.

[0016] Additionally or alternatively, the scoring module uses one or more of the following to calculate the metric: the weight of the target voxel, the weight of the avoidance voxel, the weight of the total activated voxel, and / or the weight of the total activated non-target and non-avoidance voxels.

[0017] Alternatively or additionally, the lead is configured to be implanted in the patient's brain. Alternatively or additionally, patient data includes anatomical data indicating the location of actual or probable brain structures.

[0018] Another illustrative and non-limiting example takes the form of an operational method in a neuromodulation system, comprising an implantable system having a plurality of electrodes and a configuration system configured to perform the steps of the method, the method comprising: a) receiving at least patient data of a patient and lead locations, the lead locations indicating the positions of leads carrying at least two of the plurality of electrodes relative to the patient's neural tissue; b) identifying potential subdivisions to be analyzed, the potential subdivisions setting a proportion of the total current emitted by each electrode; c) removing unusable electrodes from the potential subdivisions to generate reduced subdivisions; d) adjusting the reduced subdivisions to create adjusted subdivisions; e) calculating multiple metrics of the adjusted subdivisions using multiple amplitude settings; and identifying one or more adjusted subdivisions as one or more candidate treatments using the multiple metrics.

[0019] Additionally or alternatively, the method further includes a pulse generator for transmitting one or more candidate treatments from a configuration system to an implantable system, and activating the pulse generator to deliver neuromodulation to the patient using at least one of the one or more candidate treatments.

[0020] Additionally or alternatively, the method further includes identifying a plurality of potential subdivisions and performing each of c), d) and e) on each of the plurality of potential subdivisions.

[0021] Additionally or alternatively, potential segmentation identifies active and inactive electrodes, and step d) includes proportionally increasing the current segmentation delivered by each active electrode that was not removed during step c).

[0022] Alternatively or additionally, the potential subdivision identifies active and inactive electrodes, and step d) includes increasing the proportion of the total current emitted by each electrode in proportion to the proximity of the inactive electrode. Alternatively or additionally, this proportion is based on a Gaussian curve.

[0023] Alternatively or additionally, step c) includes removing an electrode having impedance outside the impedance range.

[0024] Alternatively or additionally, step c) may include removing electrodes that have been identified as unusable by a physician.

[0025] Additionally or alternatively, step c) includes identifying an electrode as potentially unusable based on its proximity to a neural structure being less than a threshold proximity and suggesting, via a user interface, that the electrode be removed from the physician.

[0026] Alternatively or additionally, step c) is performed by identifying removable electrodes by recognizing electrodes with impedance outside the impedance range and suggesting their removal to the physician via a user interface.

[0027] Additionally or alternatively, step e) includes: identifying the volume located around the lead as a voxel; marking at least some voxels as target voxels for treatment; and marking at least some voxels as avoidable voxels to be avoided from treatment.

[0028] Alternatively or additionally, step e) includes determining which voxels will be activated by the adjusted subdivision at multiple current amplitudes.

[0029] Alternatively or additionally, step e) may include applying one or more of the weights of the target voxel, the weights of the avoidance voxel, and the weights of the total activated voxel.

[0030] Alternatively or additionally, the lead is implanted in the patient's brain, and the patient data includes anatomical data indicating the location of actual or possible brain structures.

[0031] This invention is intended to provide an overview of the subject matter of this patent application. It is not intended to provide an exclusive or exhaustive interpretation. A detailed description is included to provide further information regarding this patent application. Attached Figure Description

[0032] In the drawings not drawn to scale, the same numbers may describe similar parts in different views. The same numbers with different letter suffixes may represent different instances of similar parts. The drawings are illustrated in general terms by way of example and not limitation, of the various embodiments discussed in this document.

[0033] Figure 1An illustrative DBS system implanted in a patient is shown;

[0034] Figure 2 Details of the universal directional DBS lead are shown;

[0035] Figure 3 The lead electrodes are shown.

[0036] Figure 4 The illustrative method is shown in the form of a block diagram;

[0037] Figure 5 The illustrative optimization method is shown in block diagram form; and

[0038] Figure 6 The illustrative system is shown in the form of a block diagram. Detailed Implementation

[0039] Figure 1 An illustrative DBS system implanted in a patient is shown. The system includes a pulse generator 10, shown implanted in the upper torso of a patient 20. The pulse generator 10 is coupled to a lead 12, which extends subcutaneously to the head of the patient 20, through a drill hole formed in the patient's skull, and then into the patient's brain. In the example shown, the lead 12 includes multiple electrodes positioned near the distal end 14 of the lead, such as... Figure 2 As shown. Lead 12 can be placed at any suitable location in the brain where the therapeutic target is identified. For example, lead 12 can be positioned such that distal end 14 is close to the midbrain and / or various structures known in the art for providing stimulation to treat various diseases.

[0040] DBS can target neural tissues such as, but not limited to, the following: thalamus, globus pallidus, subthalamic nucleus, peduncular nucleus, substantia nigra reticularis, cortex, lateral globus pallidus, medial anterior tract, periaqueductal gray matter, periventricular gray matter, habenular nucleus, subgenual cingulate gyrus, ventral intermediate nucleus, anterior nucleus, other thalamic nuclei, zona indeterminate, ventral internal capsule, ventral striatum, nucleus accumbens, and / or white matter tracts connecting these and other structures. Data related to DBS may include the identification of neural tissue regions determined through analysis that are associated with side effects or benefits observed in practice. The term “target” as used herein refers to brain structures associated with therapeutic benefits, while “avoided” or “avoided” regions refer to brain structures associated with side effects.

[0041] The conditions to be treated may include dementia, Alzheimer's disease, Parkinson's disease, various tremors, depression, anxiety or other mood disorders, sleep-related disorders, etc. Treatment benefits may include, for example, but not limited to, improved cognition, alertness, and / or memory; improved mood or sleep; avoidance of pain or tremors; reduction of movement disorders; and / or maintenance of existing function and / or cellular structure, such as preventing tissue loss and / or cell death. Side effects may include a wide range of problems, such as, for example, but not limited to, decreased cognition, alertness, and / or memory; worsened sleep quality; depression; anxiety; unexplained weight gain / loss; tinnitus; pain; tremors, etc. Treatment benefits and side effects may be monitored using, for example, patient surveys, performance tests, and / or physical monitoring (such as monitoring gait, tremors, etc.). These are merely examples, and the discussion of diseases, benefits, and side effects is illustrative and not exhaustive.

[0042] The illustrative system of claim 1 includes various external devices. A clinician programmer (CP) 30 can be used to determine / select treatment procedures, including guidance (explained further below) and stimulation parameters. Stimulation parameters may include the amplitude of the stimulation pulses, the frequency or repetition rate of the stimulation pulses, the pulse width of the stimulation pulses, and more complex parameters known in the art, such as pulse train definitions. Biphasic square waves are typically used, but nothing in this invention is limited to biphasic square waves; ramp, triangle, sine, monophasic, monophasic with passive recovery, and other stimulation types may be used as needed. The CP 30 may be, for example, a laptop computer or tablet computer, and may be used by or under the guidance of a physician to acquire data from and provide instructions to the pulse generator 10 via a suitable communication protocol (such as Bluetooth or MedRadio or other wireless communication protocols) and / or via other means (such as inductive telemetry).

[0043] The patient can use the patient remote control (RC) 40 to perform various actions related to the pulse generator 10. These can be physician-defined options and may include, for example, turning treatment on and / or off, making (limited) adjustments to the treatment, such as selecting from available treatment programs and adjusting amplitude settings, and / or entering required information, such as answering questions about the activity, treatment benefits, and side effects. The RC 40 can communicate via telemetry technology similar to the CP 30 to control and / or acquire data from the pulse generator 10. The patient RC 40 can be programmable on its own or can communicate with or link to the CP 30.

[0044] If the pulse generator 10 is rechargeable, a charger 50 can be provided to the patient to allow the patient to charge the pulse generator 10. Some pulse generators 10 are not rechargeable, and therefore the charger 50 can be omitted. The charger 50 can provide power to charge the pulse generator 10, for example, by generating a changing magnetic field using known methods to activate an inductor associated with the pulse generator 10.

[0045] Some systems may include an external test stimulator (ETS) 60. After the lead 12 has been positioned within the patient, the ETS 60 can be used during surgery to test treatment procedures for the patient 20. For example, initial implantation of the lead 12 can be performed using, for instance, a stereotactic guidance system, where the pulse generator 10 is temporarily omitted. The proximal end of the lead 12 can be connected to an intermediate connector (sometimes referred to as an operating room cable) coupled to the ETS 60. After the lead 12 is implanted and coupled to the ETS 60, the ETS 60 can be programmed with various treatment procedures and stimulation parameters using CP 30, which are tested to determine therapeutic efficacy. During this process, the lead position can be adjusted as needed. Once the suitability for treatment in the patient is determined, a permanent pulse generator 10 is implanted and the lead 12 is attached to it, after which the ETS 60 is removed for use.

[0046] The pulse generator 10 may include operational circuitry for generating output stimulation programs and / or pulses according to stored instructions. Examples of current or prior versions of such circuitry, as well as planned future examples, can be found in U.S. Patent 10,716,932, the disclosure of which is incorporated herein by reference. The pulse generator circuitry may include various commercially known implantable pulse generator circuits for spinal cord stimulation, vagus nerve stimulation, and deep brain stimulation, which are also well-known. Additional examples of the pulse generator 10, CP 30, RC 40, charger 50, and ETS 60 can be found, for example, but not limited to, U.S. Patent Nos. 6,895,280, 6,181,969, 6,516,227, 6,609,029, 6,609,032, 6,741,892, 7,949,395, 7,244,150, 7,672,734, 7,761,165, 7,974,706, 8,175,710, 8,224,450, and 8,364,278, the entire disclosure of which is incorporated herein by reference.

[0047] Figure 2Details of the universal directional DBS lead are shown. The distal end 14 carrying multiple electrodes is shown. As shown, two ring electrodes 16a, 16b (collectively referred to as ring electrodes 16) may be provided, and multiple segmented electrodes (collectively referred to as segmented electrodes 18) are shown at 18a, 18b, 18c, 18d, 18e, 18f. Each electrode 16, 18 is individually addressable in the system, such as by using a pulse generator with multiple independent current controls (MICCs) or multiple voltage sources.

[0048] A MICC is a stimulation control system that provides multiple independently generated output currents, each with its own magnitude. The use of a MICC allows for the creation of spatially selective fields through therapeutic outputs. The term "fractionalization" refers to how the total current emitted via the pulse generator through the electrodes is distributed between electrodes 16 and 18.

[0049] The pulse generator housing can be used as a return electrode, for example, during therapeutic output. Depending on the need, one of the lead electrodes (such as one or more of the ring electrode 16 or segmented electrode 18) can be alternatively used as the return electrode. Thus, for example, during one phase of stimulation pulse delivery, the lead electrode can be used as a cathode, while the pulse generator housing acts as an anode (which can be reversed in another phase of stimulation pulse delivery). In another example, during one phase of stimulation pulse delivery, some lead electrodes 16, 18 act as cathodes, while others act as anodes. Any suitable combination and number of anodes and cathodes can be used for therapeutic purposes, and any lead electrode and / or housing electrode can be used in any of these roles as needed.

[0050] Examples of electrical leads having segmented or oriented lead structures include, but are not limited to, those disclosed in U.S. Pre-Publication Patents 20100268298, 20110005069, 20110078900, 20110130803, 20110130816, 20110130817, 20110130818, 20110238129, 20110313500, 20120016378, 20120046710, 20120071949, 20120165911, 20120197375, 20120203316, 20120203320, and 2012020332. The disclosures shown in 1, 20130197602, 20130261684, 20130325091, 20130317587, 20140039587, 20140353001, 20140358207, 20140358209, 20140358210, 20150018915, 20150021817, 20150045864, 20150021817, 20150066120, 20130197424, and 20150151113, and U.S. Patent Nos. 8,483,237 and 8,321,025, are incorporated herein by reference.

[0051] MICCs used in conjunction with directional leads can facilitate precise therapeutic targeting. For example, as... Figure 2 The directional leads shown can be used to generate, for example... Figure 2 The stimulation field is shown at point 70. For illustrative purposes, the outer boundary of field 70 can be understood as representing an isoelectric or isofield boundary within which the electric field is above the activation threshold, and outside of which the electric field is below that threshold. The activation threshold can represent or approximate the voltage / field threshold at which a nerve cell will be activated or “fired.” The activation threshold can be determined based on a population, such as by relating it to the voltage / field determined to have a 50% probability of activation for 50% of the cell population, but other boundaries / thresholds can also be used. The shape of the field can be adjusted by modifying the subdivision of the current emitted via the electrodes using MICC, as described in the reference cited above. For example, by using electrode 18c as the cathode and surrounding electrodes 18a and 18e as the anode, an output that generates the activation field boundary, as shown at point 70, can be generated (roughly). The actual characteristics of subdivision can be more complex than this simple example.

[0052] Figure 2The boundary shown at point 70 can be used to illustrate the stimulus field effect and can be generated using stimulus field modeling (SFM) for display purposes. In SFM, for example, a finite element model is used to model the tissue, where the lead body is treated as an insulator, surrounded by a thin encapsulation sheath, and then by neural tissue. The neural tissue can be modeled as isotropic and homogeneous, but more complex modeling can be used if desired. For SFM, a set of model voxels is defined around the lead, decomposing the volume into segments, each of which can be analyzed within the model. As mentioned above, the outer boundary of the SFM can be determined using a population-based activation threshold. The result can be that, given a subdivision and total stimulation current, the SFM can be generated as a three-dimensional surface surrounding a portion of the lead and enclosing a volume of neural tissue. For example, field 70 can be understood as a two-dimensional representation of a slice of SFM. As mentioned above, SFM can be used as a visual tool to explain to patients or physicians which tissue is stimulated or not stimulated with a given subdivision and total current.

[0053] Figure 3 Another representation of a set of electrodes on the lead is shown. The lead is shown as a dashed line at 80. Each electrode on the lead is numbered as shown as 82, 84, 86, 88, 90, 92, 94, 96. Some electrodes are shown with a set of asterisks (***), indicating that those electrodes 84, 94 have been marked as unavailable, which also shows the basis for the lack of availability. This means that pulse generator 10 ( Figure 1 ) and via CP 30 ( Figure 1 The programming of these electrodes 84 and 94 will not allow them to be used to receive or emit current or voltage in any treatment procedure.

[0054] Electrode 84 is marked as unavailable, for example, with an asterisk (***), and the reason is that the impedance, as indicated by Ω, is out of range. For example, each electrode can be tested to determine the impedance experienced by a current passing through the electrode. The tested impedance is compared to an acceptable range. Those skilled in the art will understand that there can be many different reasons why electrode impedance may be out of range. For example, if a current control system is used, excessively high impedance may prevent treatment delivery because the constant current circuit may require a voltage source greater than the electronics can support. High impedance may occur due to a conductor break within lead 80, or due to other reasons, such as a welding failure at the point where the conductor is electrically connected to the electrode itself. High impedance may also occur due to excessive corrosion at the electrode-tissue interface. For example, excessively low impedance may occur due to a short circuit somewhere in the lead or fluid intrusion into an undesirable part of the pulse generator head (where the lead is coupled to the pulse generator). Voltage field measurements can be performed and used similarly, such as by applying an output current or voltage between the ring electrodes 82, 96 and sensing the electric field generated on the remaining electrodes 84 to 94, to confirm the connection between the electrodes and the internal circuitry of the pulse generator.

[0055] Electrode 94 was also marked as unusable, but this time it was marked "PD" due to the physician's decision. For example, the physician can determine, while reviewing images taken after lead implantation, whether electrode 94 is located adjacent to or too close to structures the physician does not want to be affected by the electric field. CP ( Figure 1 (30 locations) could include a user interface and screens that would allow doctors to make such choices.

[0056] Existing systems do not provide robust methods for handling unavailable electrodes. For example, if an electrode's impedance test fails, the problem is initially addressed via a doctor's alert. For instance, any procedure using the electrode for treatment delivery might be automatically disabled by the pulse generator. For example, manual reprogramming might be required when the patient returns for their next appointment and is programmed by the doctor. New and alternative methods are needed.

[0057] Figure 4 An illustrative method is shown in block diagram form. In this illustrative method, the location of the lead in the patient's body is determined at 100. For illustrative purposes, the location of the lead in the brain will be explained; however, the invention can be used when modeling and optimizing neural stimulation in other parts of the body. The lead location 100 can be determined after the lead has been implanted using imaging 104, such as using various methods, including X-ray, CT scan, MRI, or others.

[0058] Next, the system maps the structures, as indicated at 102. Mapping structure 102 may include identifying structures within the brain using preoperative and / or postoperative imaging 104 and data from brain atlas 106. Brain atlas 106 may include data from a patient population indicating the gross location and nature of structures in the brain, allowing the images to be referenced to a population example. Illustrative structures may include the thalamus, globus pallidus, subthalamic nucleus, and / or other structures mentioned above, and actual data (from imaging) or estimated data (e.g., from the population / atlas) identifying such structures may be referred to as patient anatomical data. Data input to 102 may also include other data 108, such as, for example, but not limited to, input from a database of treatment settings from previously programmed / treated patient populations, as needed. That is, treatments issued by other implantable systems may repeatedly target similar structures and thus provide additional understanding of, for example, best practices. Other data 108 may also include brain functional data, such as data collected using function-based imaging or electrophysiological activity recorded using implanted leads, each of which may also be entered into the system as data input at 102. This dataset was used to map the location of structures in the brain, as well as “sweet” and “sour” spots—regions associated with treatment benefits and / or harms or side effects.

[0059] The user or physician then selects a structure in box 110. Structures can be identified as target structures or avoidance structures. Target structures are those that the physician determines should be stimulated as much as possible, while avoidance structures are those that the physician determines should not be stimulated to the extent possible. Typically, target structures are associated with therapeutic benefits, while avoidance structures are associated with side effects.

[0060] Voxel calculations occur as indicated in 112. Voxel calculation 112 defines a mesh of volume elements (voxels) in the tissue region surrounding the lead and determines which voxels reside in various structures, as further described below. As used herein, "voxel" refers to any segment of volume used in the analysis, regardless of shape, and may include cubes, polygons, partially cylindrical, partially toroidal shapes, etc. Voxel calculations may reference any of the world coordinate system, anatomical coordinate system, or image coordinate system. Any suitable voxel definition and coordinate system (such as Cartesian, spherical, or polar coordinates) may be used as needed. Some systems may use an anatomical reference to the relevant coordinate system to define lead location and structure location / positioning. Those skilled in the art will understand transformations from one coordinate system to another. Voxel calculation 112 includes using the selection made at box 110 to identify which target structures and avoidance structures contain which voxels. A single voxel may reside in multiple structures.

[0061] Optimization is performed after iteration box 120. Structure selection 110 and voxel calculation 112, and / or device history or other inputs are used to determine the initial guidance or subdivision at guidance configuration 122. Guidance configuration 122 is then used to determine I th Table I th The table indicates the minimum total current that will be required to trigger or may trigger neural activity in a given voxel, given a given guidance state and subdivision. th The values ​​in the table are used to create I th Volume histogram 124. For each target structure or avoidance structure, create I... th A volume histogram, containing bins for each available amplitude setting (voltage or current level). Using I... th Table data, where each voxel is characterized as active or inactive at multiple amplitudes. Relative to each target or avoidance structure, a voxel has a "value" calculated as discussed further below, where the voxel value partially indicates the subdivision of voxels within a particular structure. Each stripe has a value and an associated amplitude, where the stripe value is determined by summing the products of the voxel volume of each voxel and the voxel value, which activates the voxel when it changes from an amplitude below the stripe amplitude to the stripe amplitude. That is, I th Each bar in the volume histogram is for the purpose of generating I. thThe table's guidance parameters and other treatment parameters specify the variation in the stimulated volume of each structure at each amplitude within the amplitude range.

[0062] These I th The content of the volume histogram 124 and the target / avoidance region selection are combined with weights 126 to generate I. th The metric histogram is 128. In a simple approach, there might be two user-adjustable weights and one preset weight: the target volume weight w. T It can be preset to 1, and avoids structural weight w. A and background weight w B Each of these can be user-adjustable; other methods can be used to weight the target structure, avoidance structure, and background structure. Therefore, for each of the multiple amplitudes, I... th The metric histogram 128 indicates the metric change per magnitude based on which voxels are activated and in the target or avoidance region, as weighted according to weight 126.

[0063] The weighted value of each voxel is 126 and I th The product of volume histogram 124 is called I. th Metric histogram 128. At box 130, each magnitude change of the metric is integrated to determine the highest metric value for the guidance configuration being analyzed and the associated magnitude that generated the highest metric value. These values, along with those generated by previous iterations of optimization, are used to generate the next guidance state, indicating the next iteration, as indicated at 132. If an exit condition is met, such as by showing that the metric does not increase with the new guidance configuration, the iteration in 120 terminates, and at 140, the analysis includes candidate results comprising various maximum metrics and magnitudes.

[0064] exist Figure 4 During the analysis, each voxel can be understood as having its own value, depending on whether the voxel is in the target region or the avoidance region. As used below, the background is the model predicting the entire volume to be stimulated, including both the target and avoidance regions, as well as voxels that are neither in the target nor the avoidance region. This value can then be used to generate a metric by multiplying it by weights. At a higher level, the total metric can be understood as indicated in Equation 1:

[0065] Equation 1

[0066] Where v target It is the volume of the target tissue being stimulated, v avoid It is the volume of the stimulus-avoidance region, and v sfm It is the total stimulated region under optimized amplitude. In Equation 1, w A and wB As mentioned earlier, and each of them can be user-adjustable; if needed, a target weight w can be included. T (Preset to 1 in some examples), and combine it with v target Multiplication. A similar version of Equation 1 can also be used on a voxel-by-voxel basis to fill I. th Measurement histogram 128.

[0067] Figure 4 Other examples and possible details used in the previous description of the algorithm can be found in U.S. Patent 11,195,609, the disclosure of which regarding details of voxelization, histograms, and optimization procedures is incorporated herein by reference. However, the foregoing description is one way optimization 120 can be implemented. In other examples, different sequences of operations may be used. For example, in one alternative, for each given guidance configuration, the search algorithm may be used to test different magnitude metrics without generating a histogram, wherein the search algorithm is used through multiple iterations until the current magnitude that maximizes the metric calculated in Equation 1 above for a given guidance configuration is determined.

[0068] While the simplest way to find the highest metric could be to scan all available guide and amplitude configurations (as well as other parameters such as pulse width, shape, and frequency), such a procedure can be computationally too burdensome. A more selective approach might be preferable. In some examples, for a given patient's anatomy, guide location, and medical condition, optimization at 120 could be achieved using similarity analysis to identify similar patient characteristics in a database (such as "Other Data 108"), and this analysis could be used to generate a starting point for optimization 120. As mentioned earlier, these are merely examples.

[0069] These combinations of guidance configurations and stimulation parameters that produce the highest metrics can be characterized as candidate treatments, as indicated by 140. Candidate treatments 140 can also be rated or analyzed using secondary factors such as power consumption. Candidate treatments can be presented to the physician. The physician can then select the guidance configuration and stimulation parameters for subsequent testing of the system. Testing can be performed using an ETS or an implantable pulse generator as needed. If an ETS is used for testing, the pulse generator housing can be simulated via a skin patch; otherwise, the return current during ETS use passes through the lead electrodes.

[0070] The preceding discussion assumes that all system electrodes are available. Therefore, different guidance configurations can be used to identify the highest-scoring metrics; however, as... Figure 3As shown, one or more electrodes may be unavailable. One approach is to modify box 122 as shown at 150 by limiting the electrode configurations available when determining new guidance or subdivisions at 122 during iterations of optimizer 120. That is, for example, selecting guidance configuration box 122 may use, for example, but not limited to, best-fit or cost function type analysis to compute a new subdivision after electrode removal that recreates the electric field and / or therapeutic effect of the pre-candidate parameter set.

[0071] Another approach for analysis when one or more electrodes are unavailable is to add a box, as shown at 160, to remove and recalculate the optimized parameters of one or more “pre-candidate” treatment parameter sets, which are then passed as candidates to box 140. Removal and recalculation 160 can be performed using, for example, but not limited to, best-fit or cost function type analysis, to compute a new subdivision after electrode removal that recreates the electric field and / or treatment effect of the pre-candidate parameter sets.

[0072] Figure 5 This illustrates another method for optimization using the newly reconfigured optimizer. Here, voxel calculations are performed for 200 voxels. Figure 4 This occurs as shown, and the voxel calculation is passed to optimizer 210. In the optimizer, the guidance configuration is selected as shown at 212, similar to... Figure 4 Box 122 (omitted) Figure 4 (An alternative to middle frame 150). After generating the guidance configuration and subdivision at 212, the potential subdivision is passed to frame 214. At 214, any unusable electrodes are removed from the subdivision, generating a reduced subdivision that is passed to frame 216. For example, the electrode removal frame 214 may receive data from an implantable pulse generator or ETS indicating electrodes that are unusable due to high or low impedance (or any other reason), and / or data from a clinician indicating that the selected electrode will not be used and is therefore unusable.

[0073] Next, as indicated at 216, the subdivision is adjusted. If there is no need to remove the electrodes, this method can bypass boxes 214 and 216, as shown in the figure. Adjusting the subdivision 216 can be performed by increasing the current on each available electrode in a proportional manner. This proportional method may be referred to as normalization. The table shows a simplified example:

[0074]

[0075] Here, as indicated by X, electrode E2 is unavailable. Normalized subdivision increases the current in each active electrode of the original subdivision proportionally to the original current allocation, while the non-active electrode (E5) remains zero. Although the graph shows a method based on linear scaling, other adjustments can be made as needed. For example, one approach could use a Gaussian curve (or multiple curves) centered on one or more removed / unavailable electrodes as a weighting function, adding current to the electrodes based on their proximity to the removed / unavailable electrodes. As a simple example, using... Figure 3 The layout shown may differ slightly from the subdivisions depicted in the chart.

[0076]

[0077] Here, compared to E1 and E4 (which are farther from E2), more of the redistributed current is allocated to E3 (which is closest to E2), and compared to E4, E1 receives more of the redistributed current.

[0078] Then, the adjusted subdivision from box 216 is passed to I at 218. th The volume histogram is calculated, and weight 220 at box 222 is used to generate I. th A metric histogram is passed to box 224. In general, boxes 218, 220, 222, and 224 can be described as scoring box 228, used to score the adjusted segmentation received from box 216. Boxes 218, 220, 222, 224, 226, and 230 can be respectively associated with… Figure 4 The same applies to boxes 124, 126, 128, 130, 132, and 140.

[0079] Figure 6An illustrative system is shown. This system may include a data receiver box 300. For example, communication circuitry 350 may be coupled to a software or hardware module configured to receive and store information relating to patient anatomy, lead location, and / or other information, including, for example, population-based structural data. As needed, the data input to 300 may also include input from a database of treatment settings from previously programmed / treated patient populations. Furthermore, brain functional data collected using function-based imaging, or electrophysiological activity recorded using implanted leads, may also be used as data input at 300 as part of an overall mapping of “sweet” and “sour” points (regions associated with treatment benefits and / or harms or side effects). Additionally or alternatively, the data receiver 300 may receive the patient’s SFM or other previously calculated treatment field or modeling data, which may be fed forward and used to optimize the procedure as needed. Additionally or alternatively, any previously created targets for the patient may be received. Such data, whether in its entirety or in the portion available to a given patient (whether including or omitting anatomical data itself, or using previously generated target, SFM, or other modeling data), can be referred to as patient data received by receiver module 300.

[0080] At 302, the data in box 300 is then used for voxel definition, which can be implemented as another software module and / or by a separate or dedicated circuit (application-specific integrated circuit, microcontroller, etc.). Voxel definition box 302 provides voxelization to structure selection box 304.

[0081] The structure selection box 304 is configured to receive user / physician input from a user interface 306, which may include one or more of a keyboard, mouse, trackball, touchscreen, monitor / output screen, voice, or other audio input / output devices. The structure selection box 304 may also receive structural data from a data receiver 300, such as data that helps identify structural boundaries and structures. The user interface 306 allows the user / physician to identify and select target and avoidance areas within the patient's anatomy for use by the structure selection box 304. If necessary, the box 304 may also restrict which structures can be selected as targets, taking into account the clinician's expected treatment and / or system labeling limitations.

[0082] The user interface is also used to allow users / doctors to select or modify the structural weights for background, target, and / or avoidance as described above. Furthermore, the user interface can allow doctors to identify or select electrodes to use or not use during the optimization process. Structural selection 304 can be applied to voxel definition to structurally identify the priority of each structure for stimulation (e.g., using a separate weight for each target structure) and / or avoidance (e.g., using a separate weight for each avoidance structure). The effect of structural selection 304 is to use voxelization to determine the value of each voxel for each target and avoidance structure. As used herein, the voxel values, as described above, indicate each of the following: the number of voxels filled with structures or structural portions (such as probability shells), the probability of a neural response when stimulated, and / or the presence of a structure in the voxel (whether target or avoidance). Target and avoidance structure data, along with their corresponding voxel values, are passed to optimizer 310.

[0083] Optimizer 310 selects a guided configuration at 312, thus initiating a series of iterative analyses. At box 314 (if any electrode is unavailable), electrode removal then occurs, using, for example, instructions from the physician provided via user interface 306 and / or data received from the communication block at 350 indicating unavailable electrodes from the implantable pulse generator or ETS. In some examples, electrode removal module 314 is configured to identify removable electrodes by recognizing proximity to neural structures below a threshold proximity and suggesting electrode removal to the physician via the user interface. In other examples, electrode removal module is configured to identify removable electrodes by recognizing electrodes with impedance outside the impedance range and suggesting electrode removal to the physician via the user interface.

[0084] As indicated by 316, the original subdivision from box 312 is then adjusted. The adjustment at 316 may include normalizing the data, or using different adjustments, such as adjustments based on proximity to the removed / unavailable electrode.

[0085] I th The table is generated at 318, and the metric / amplitude data is generated at 320. That is, for a given guidance configuration, the metric / amplitude data provides an indication of pairing the generated metrics with the amplitudes. One or more optimal combinations are selected by optimizer 310 and stored in memory 330. If no exit condition occurs, the next iteration is triggered at 322, and a new guidance configuration is set at 312, and the process continues iterating. Exit conditions and guidance reconfiguration selection can be as described, for example, in U.S. Patent 11,195,609, the disclosure of which is incorporated herein by reference.

[0086] When the exit conditions are met, the dataset in memory 330 will provide one or more “best” or highest-rated guidance settings and amplitude or parameter selections. These are then presented to the user / doctor by the treatment selection module 340 via user interface 306. The user / doctor can then select or approve one or more suggested treatments. Treatment selection box 340 can generate SFM for display via user interface 306 to aid the treatment selection process. Once the user selects the treatment to be implemented, communication box 350 is used to transmit treatment parameters to the pulse generator or ETS. The pulse generator or ETS then delivers the selected treatment to the patient.

[0087] The guidance selection at 312 can utilize artificial intelligence methods and / or search functions, where stopping conditions are predetermined. In the example, box 310 can be configured to receive structural selection data that can inform the process of selecting a guidance configuration. For example, the guidance selection for the iterative process can use (but is not limited to) a database of guidance selection configurations for other similar patients. By generally comparing the database of guidance configurations with the received structural selections, optimizer 310 and guidance selection box 312 are able to quickly eliminate most possible guidance configurations to build a shortened list. Some illustrative methods include iterative optimization methods such as gradient descent search, genetic algorithms, simulated annealing, stochastic coordinate descent, particle swarm optimization, fuzzy logic, and other machine learning search algorithms. Various details of the search process are also explained in U.S. Patent 11,195,609, the disclosure of which is incorporated herein by reference.

[0088] While the above discussion largely focuses on the use of DBS, other tissue areas can also be treated. For example, anatomical mapping can be used to identify nerves and / or other structures to be targeted or avoided during other treatments such as spinal cord stimulation (SCS), peripheral nerve stimulation, occipital nerve stimulation, muscle and muscle nerve fibers, treatments targeting the digestive tract or other areas, and vagus nerve stimulation. As an example, in SCS, such as in the cervical spine, the spinal cord carries neural signals from various parts of the body. With advancements in science related to spinal cord structure, knowledge can be obtained about which parts of the spinal cord carry signals to and from which parts of the body at a given vertebral level. With this knowledge, treatment and avoidance areas in the spinal cord can be defined / identified. If multiple guides or paddle guides are present at a given vertebral level, guidance and SFM models can be determined for that given vertebral level using spinal cord atlases and guide implantation / location data (such as from X-rays or other imaging systems). A similar process to that described above can be used to define treatment targeting the portions of the spinal cord that carry interacting neural signals (such as pain signals), while other portions (such as those carrying motor signals) are avoided. The aforementioned metric calculations can then be used to optimize guidance to limit side effects and achieve the desired therapeutic effect.

[0089] Back Figure 6 The data receiver 300 and / or communication frame 350 may include communication circuitry (transceiver, antenna, and similar devices such as Bluetooth, WiFi, Medradio, etc.) and / or input / output circuitry for, for example, a local area network cable. On the other hand, in some examples, the data receiver 300 is a software module that communicates with other applications in the CP; communication via external hardware may be optional for the data receiver 300. A microcontroller or microprocessor having specially configured software or other instructions stored thereon, such as stored in non-transient memory, such as memory 330 known in the art, which may include flash memory, RAM, ROM, etc. Overall, Figure 6 The implementation can be done on a tablet or laptop computer, such as a clinician programmer or CP as described above.

[0090] Each of these unrestricted examples can exist independently or can be combined with one or more other examples in various permutations or combinations.

[0091] The above detailed description includes references to the accompanying drawings, which form part of the detailed description. The drawings illustrate specific embodiments by way of illustration. These embodiments are also referred to herein as "examples." These examples can also include elements other than those shown or described. However, the inventors also contemplate examples that provide only those elements shown or described. Furthermore, the inventors contemplate examples using any combination or arrangement of those elements (or one or more aspects thereof) shown or described, whether concerning a particular example (or one or more aspects thereof) or other examples (or one or more aspects thereof) shown or described herein.

[0092] In the event of any inconsistency between the usage in this document and any other document incorporated by reference, the usage in this document shall prevail.

[0093] In this document, the terms “a” or “an” (as is common in patent documents) include one or more, and are not related to any other example or use of “at least one” or “one or more”. Furthermore, in the claims, the terms “first,” “second,” and “third,” etc., are used merely as labels and are not intended to impose numerical requirements on their objects.

[0094] The methods described herein can be implemented, at least in part, by a machine or computer. Some examples can include computer-readable or machine-readable media encoded with instructions operable to configure an electronic device to perform the methods described in the examples above. Implementations of such methods can include code, such as microcode, assembly language code, high-level language code, etc. Such code can include computer-readable instructions for performing various methods. The code can form part of a computer program product. Furthermore, in one example, the code can be tangibly stored on one or more volatile, non-transient, or non-volatile tangible computer-readable media, such as during execution or at other times. Examples of such tangible computer-readable media can include, but are not limited to, hard disks, removable disks or optical discs, magnetic tape cassettes, memory cards or memory sticks, random access memory (RAM), read-only memory (ROM), and similar devices.

[0095] The above description is intended to be illustrative and not restrictive. For example, the above examples (or one or more aspects thereof) can be used in combination with each other. Other embodiments can be used, such as those used by those skilled in the art after reviewing the above description.

[0096] An abstract is provided to comply with 37 CFR § 1.72(b) so that the reader can quickly determine the nature of the technical disclosure. When submitting this abstract, it should be understood that it will not be used to interpret or limit the scope or meaning of the claims.

[0097] Furthermore, in the above detailed description, various features may be grouped together to simplify this disclosure. This should not be construed as meaning that unclaimed features are essential to any claim. Rather, the subject matter of the invention may reside in some features of a particular disclosed embodiment. Therefore, the following claims are incorporated herein by way of example or embodiment, wherein each claim exists independently as a separate embodiment, and these embodiments are contemplated to be combined with each other in various combinations or arrangements. The scope of protection should be determined with reference to the appended claims and the full scope of their equivalents.

Claims

1. A configuration system for configuring the delivery of neuromodulation to a specific tissue of a patient via an implantable system having multiple electrodes, the configuration system comprising: A receiver module configured to receive at least patient data and lead positions, the lead positions indicating the location of a lead carrying at least two of a plurality of electrodes relative to the patient's neural tissue; An optimizer for identifying a set of candidate treatment parameters indicating the utilization of the plurality of electrodes during treatment, the optimizer comprising: A guidance module is used to identify potential subdivisions to be analyzed, the potential subdivisions being set by the proportion of the total current emitted by each electrode; An electrode removal module receives the potential subdivision and removes unusable electrodes from the potential subdivision to generate a reduced subdivision; The adjustment module receives the reduced subdivision and creates the adjusted subdivision; The scoring module receives the adjusted segmentation and uses multiple magnitude settings to calculate multiple metrics of the adjusted segmentation; and A candidate module that uses the plurality of metrics to identify one or more candidate treatments.

2. The configuration system according to claim 1, wherein, The optimizer is configured to use the guidance module to identify multiple potential subdivisions.

3. The configuration system according to any one of claims 1 to 2, wherein, The potential subdivision identifies active and inactive electrodes, and the adjustment module creates the adjusted subdivision by proportionally increasing the current subdivision delivered by each active electrode that was not removed by the electrode removal module.

4. The configuration system according to any one of claims 1 to 2, wherein, The potential subdivision identifies active and inactive electrodes, and the adjustment module modifies the current subdivision by adding current to the active electrode in proportion to the proximity of the inactive electrode.

5. The configuration system according to claim 4, wherein, The ratio is based on a Gaussian curve.

6. The configuration system according to any one of claims 1 to 5, wherein, The electrode removal module removes electrodes with impedance outside the impedance range.

7. The configuration system according to any one of claims 1 to 5, wherein, The electrode removal module removes electrodes that have been identified as unusable by the doctor.

8. The configuration system according to claim 7, wherein, The electrode removal module is configured to identify electrodes that can be removed by recognizing those that are less than a threshold proximity to a neural structure and suggesting electrode removal to the doctor via a user interface.

9. The configuration system according to claim 7, wherein, The electrode removal module is configured to identify removable electrodes by recognizing electrodes with impedance outside the impedance range and suggesting electrode removal to the doctor via a user interface.

10. The configuration system according to any one of claims 1 to 9, the configuration system further comprising a voxel calculation module that identifies the volume located around the lead as voxels and marks at least some voxels as target voxels for treatment.

11. The configuration system according to claim 10, wherein, The voxel calculation module also marks at least some voxels as avoidable voxels to be avoided in treatment.

12. The configuration system according to any one of claims 10 or 11, wherein, The scoring module calculates the multiple metrics by determining which voxels will be activated by the adjusted subdivision at multiple current amplitudes.

13. The configuration system according to claim 10, wherein, The scoring module uses one or more of the following to calculate the metric: the weight of the target voxel, the weight of the avoidance voxel, the weight of the total activated voxel, and / or the weight of the total activated non-target and non-avoidance voxels.

14. The configuration system according to any one of the preceding claims, wherein, The lead is configured to be implanted in the patient's brain.

15. The configuration system according to any of the preceding claims, wherein, The patient data includes anatomical data indicating the actual or possible locations of brain structures.

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