Electrical impedance tomography apparatus and system

Abstract

A surgical system includes a surgical stapler and an electrical impedance tomography (EIT) system. The surgical stapler includes a first jaw having an anvil and a second jaw having a stapler cartridge. The EIT system includes: an electrode array including a plurality of electrodes operably coupled to a first jaw and / or a second jaw; and a processor. The processor is configured to control application of current across the electrodes of the electrode array, measure a voltage difference across the electrodes of the electrode array, calculate an electrical impedance based on the measured voltage difference, and generate an electrical impedance tomography reconstruction based on the calculated electrical impedance.

Description

background 1. Technical Field

[0001] The present disclosure relates to surgical devices. More specifically, the present disclosure relates to surgical devices including electrode arrays for electrical impedance tomography and systems for reconstructing electrical impedance tomography images.

[0002] 2. Related technical background

[0003] Surgical staplers are commonly used in many open and laparoscopic cancer resection surgeries, including thoracic surgery, bariatric surgery, and colorectal surgery. For example, during lung surgery, surgical staplers are often used to perform wedge resections around suspected cancerous lung nodules. However, small lung nodules may not be visible and cannot be palpated using thoracoscopic methods during surgery, requiring different localization methods, such as hook wires, dyes, fiducial markers, contrast agents, or radioactive tracers. Although these localization methods are generally very effective (for example, the success rate of hook wire positioning via computed tomography (CT) guidance is 93.6% to 97.6%), they have certain disadvantages and may fail.

[0004] Because cancer is identified earlier, the size of the tumor found is smaller. This can make it difficult to identify the tumor intraoperatively. This is especially true for lung cancer. CT images can confirm the presence of cancer, but are still not easily translated into lung geometry because the geometry changes during surgery when the air is deflated. In addition, the cancer may be so small or deep within the parenchyma that the surgeon cannot identify them using video-assisted thoracic surgery (VATS) or even palpate them during open surgery. Therefore, there is a need for a method of intraoperatively locating cancerous lung nodules, or malignant tissue in general. Summary of the invention

[0005] The present disclosure provides a surgical system including a surgical stapler and an electrical impedance tomography (EIT) system. The surgical stapler includes an end effector including a first jaw having an anvil and a second jaw having a stapler staple cartridge. The EIT system includes: an electrode array including a plurality of electrodes operably connected to the first jaw; and a processor. The processor is configured to control the application of current across the electrodes of the electrode array, measure the voltage difference across the electrodes of the electrode array, calculate electrical impedance based on the measured voltage difference, and generate electrical impedance tomography reconstruction based on the calculated electrical impedance.

[0006] In one aspect, the electrode array can include sixty electrodes.

[0007] In one aspect, each electrode of the electrode array can be about 3 mm long and about 1 mm wide. As used herein, the term "about" means ±5% of a value.

[0008] In one aspect, the electrodes of the electrode array may be arranged in four columns and fifteen rows.

[0009] In one aspect, the electrodes of the electrode array can be grouped into four different groups of ten electrodes.

[0010] In one aspect, the processor can be configured to filter the calculated electrical impedance by removing noisy patterns prior to generating the electrical impedance tomography reconstruction.

[0011] In one aspect, the generated electrical impedance tomography reconstruction can include conductive inclusions and resistive inclusions, wherein the conductive inclusions are visually distinguishable from the resistive inclusions.

[0012] In one aspect, the processor can be configured to detect tumor margins based on the electrical impedance tomography reconstruction.

[0013] In one aspect, the processor can be configured to control the application of the current at a frequency of about 10 kHz to about 80 kHz.

[0014] In another aspect of the present disclosure, an electric surgical instrument is provided. The electric surgical instrument includes: an end effector including a first jaw and a second jaw; and an electrical impedance tomography system. The electrical impedance tomography system includes: a first electrode array including a plurality of electrodes operably connected to the first jaw; a second electrode array including a plurality of electrodes operably connected to the second jaw; and a processor. The processor is configured to: control the application of current across any two electrodes of the first electrode array and the second electrode array, measure the voltage difference across the first electrode array and the second electrode array (for example, any two other electrodes of the first electrode array and the second electrode array) or between any two electrodes of the first electrode array or the second electrode array, calculate the electrical impedance based on the measured voltage difference, and generate the electrical impedance tomography reconstruction based on the calculated electrical impedance.

[0015] In one aspect, the first electrode array may include sixty electrodes and the second electrode array includes eight electrodes.

[0016] In one aspect, each electrode of the first electrode array can be about 3 mm long and about 1 mm wide, and each electrode of the second electrode array can be about 3 mm long and about 3 mm wide.

[0017] In one aspect, the electrodes of the first electrode array may be arranged in four columns and fifteen rows, and the electrodes of the second electrode array may be arranged in two columns and four rows.

[0018] In one aspect, at least a portion of the plurality of electrodes of the first electrode array may be grouped into four different groups of ten electrodes, each group of ten electrodes being paired with eight electrodes of the second electrode array.

[0019] In one aspect, the processor can be configured to filter the calculated electrical impedance by removing noisy patterns prior to generating the electrical impedance tomography reconstruction.

[0020] In one aspect, the generated electrical impedance tomography reconstruction can include conductive inclusions and resistive inclusions, wherein the conductive inclusions are optically distinguishable from the resistive inclusions.

[0021] In one aspect, the processor can be configured to detect tumor margins based on the electrical impedance tomography reconstruction.

[0022] In one aspect, the processor can be configured to control application of current across the first electrode array and the second electrode array at a frequency of about 10 kHz to about 80 kHz.

[0023] In another aspect of the present disclosure, a surgical system includes an electric surgical instrument, an electrical impedance tomography system, and a display. The electric surgical instrument includes a first jaw and a second jaw. The electrical impedance tomography system includes: a first electrode array, the first electrode array including a plurality of electrodes operably connected to the first jaw; a second electrode array, the second electrode array including a plurality of electrodes operably connected to the second jaw; and a processor. The processor is configured to control the application of current across the first electrode array and the second electrode array, measure the voltage difference across the first electrode array and the second electrode array, calculate the electrical impedance based on the measured voltage difference, and generate the electrical impedance tomography reconstruction based on the calculated electrical impedance. The display is operably connected to the electrical impedance tomography system and is configured to display the electrical impedance tomography reconstruction.

[0024] In one aspect, the processor can be configured to control application of current across the first electrode array and the second electrode array at a frequency of about 10 kHz to about 80 kHz. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Embodiments of the present disclosure are described herein with reference to the accompanying drawings, in which:

[0026] Figure 1 is a surgical system according to an embodiment of the present disclosure, the surgical system comprising an electrical impedance tomography system and a surgical instrument;

[0027] Figure 2 According to the embodiments of the present disclosure Figure 1A perspective view of an exemplary surgical instrument in the form of an electric surgical stapler including a handle assembly, an adapter assembly, and an end effector;

[0028] Figure 3 yes Figure 2 Schematic diagram of a handle assembly, an adapter assembly and an end effector of a surgical instrument;

[0029] Figure 4 yes Figure 2 A top view of a bottom electrode array of a surgical instrument;

[0030] Figure 5 yes Figure 2 A top view of a top electrode array of a surgical instrument;

[0031] Figure 6 It can be displayed in Figure 1 Electrical impedance tomography reconstruction on the graphical user interface (GUI) of the surgical system;

[0032] Figure 7 According to one aspect of this disclosure Figure 2 A diagram of a bottom electrode array of a surgical instrument relative to a simulated grid marking for segmentation;

[0033] Fig. 8A is a graph showing area under the curve (AUC) calculations performed across all difference-EIT reconstructions on top and bottom electrodes based on simulated tests using 2% simulated noise and varying the sensitivity threshold from 1 / 50 to 1 / 1000;

[0034] Figure 8B is a graph showing AUC calculations across all difference-EIT reconstructions on only the bottom electrode based on simulated testing using 2% simulated noise and varying the sensitivity threshold from 1 / 50 to 1 / 1000;

[0035] Fig.9A is a graph showing AUC calculations across all difference-EIT reconstructions based on simulation tests while varying the voltage noise using 2% simulated noise and a sensitivity threshold of 1 / 50;

[0036] Fig. 9B is a graph showing AUC calculations across all difference-EIT reconstructions based on simulation tests while varying the reference z-height using 2% simulated noise and a sensitivity threshold of 1 / 50;

[0037] Fig. 10Ais a graph showing AUC calculations across all available difference-EIT reconstructions using 2% voltage noise and a sensitivity threshold of 1 / 50 based on simulated tests analyzed across contrasts;

[0038] Fig. 10B is a graph showing AUC calculations across all available difference-EIT reconstructions using 2% voltage noise and a sensitivity threshold of 1 / 50 for simulated tests analyzed according to span size; and

[0039] Fig. 10C is a graph showing AUC calculations across all available difference-EIT reconstructions from simulated tests analyzed across the x / y distance from the electrode to the center of the inclusion using 2% voltage noise and a sensitivity threshold of 1 / 50. DETAILED DESCRIPTION

[0040] Embodiments of the presently disclosed surgical device and adapter assembly, and / or handle assembly for a surgical device are described in detail with reference to the accompanying drawings, in which like reference numerals represent identical or corresponding elements in each of the several views. As used herein, the term "distal" refers to that portion of a surgical instrument or a component thereof that is further away from a user, and the term "proximal" refers to that portion of a surgical instrument or a component thereof that is closer to a user.

[0041] The present disclosure combines electrical impedance tomography (EIT) with surgical devices (such as laparoscopic staplers, surgical probes, surgical graspers, or any other surgical device) to generate electrical impedance tomography reconstructions or other electrical impedance data sets (e.g., EIT maps) and enable intraoperative identification of nodule (e.g., tumor) margins. Although detection of tumor margins is described, it is contemplated that these embodiments may also be used to detect disease states and / or critical structures. In embodiments, other surgical instruments may be combined with an EIT system according to the present disclosure, including but not limited to graspers, vascular closure devices (bipolar or ultrasonic), rods, probes, and the like.

[0042] EIT estimates electrical properties from many combinations of impedance measurements recorded by electrodes placed on the tissue. Electrical impedance (Z) can be calculated using a 4-point measurement, i.e., a current (I) can be applied across two electrodes and the voltage difference (V) from the two other electrodes is measured (Z=V / I). Significant cellular and extracellular differences between benign and malignant tissues or other tissues and nodules result in significant electrical impedance differences.

[0043] Figure 1A surgical system 10 is shown, which includes a computing device 100 configured to communicate with one or more surgical devices (e.g., surgical instrument 200). The computing device 100 includes one or more displays 12, which are configured to output information related to the device and surgical settings as a graphical user interface on the one or more displays 12. The display 12 can be any suitable monitor, augmented or virtual reality head-mounted device, head-up display, projector, etc. In an embodiment, the display 12 can also be a touch screen. The system 10 also includes an interface device 104, which is configured to communicate with the surgical instrument 200, which can include a modular surgical stapler (e.g., a linear stapler, a circular stapler, etc.) that can be electric or non-electric. The interface device 104 is further configured to receive device information from the surgical instrument 200 and process the device information to display on one or more displays 12.

[0044] The surgical system 10 further includes an electrical impedance tomography (EIT) system 450 configured to generate an electrical impedance tomography reconstruction 600 ( Figure 6 ) for display on display 12. EIT system 450 may be fully incorporated into surgical instrument 200 and configured to output data to computing device 100 for additional processing and display on display 12. Alternatively, EIT system 450 may include one or more components incorporated into surgical instrument 200 and one or more components separate from surgical instrument 200.

[0045] In various aspects, the surgical instrument 200 can be an electric surgical instrument, such as an electric surgical stapler 200a ( Figure 2 and Figure 3 ). Figure 2 Components of an example electric surgical stapler 200a are shown, which includes a power platform, i.e., a handle assembly 102, which includes one or more motors, a power source, a main controller, a storage device, a transmitter / receiver, etc. The electric surgical stapler 200a also includes a linear adapter 202, which is configured to connect the handle assembly 102 to a loading unit 204, which includes an end effector 206, which includes a first clamping jaw 208 with a stapler cartridge 210 and a second clamping jaw 212 with an anvil 214. The linear adapter 202 includes various mechanical linkages that couple the end effector 206 to the handle assembly 102, thereby enabling the end effector 206 to be actuated to perform various functions, such as clamping, suturing, and cutting. For further details on the construction and operation of the linear stapler components, reference may be made to U.S. Patent No. 9,839,425 filed on March 30, 2015, the entire contents of which are incorporated herein by reference.

[0046] refer to Figure 3 , the handle assembly 102 includes a main controller circuit board 142, a rechargeable battery 144 configured to power any electrical component of the handle assembly 102, and a plurality of motors (e.g., a first motor 152a, a second motor 152b, and a third motor 152c) coupled to the battery 144. The handle assembly 102 also includes a display 146. In an embodiment, the motors 152a, 152b, and 152c can be coupled to any suitable power source (such as an AC / DC transformer) configured to provide electrical energy to the motors 152a, 152b, and 152c. Each of the motors 152a, 152b, and 152c is coupled to a motor controller 143, which controls the operation of the corresponding motors 152a, 152b, and 152c, including the flow of electrical energy from the battery 144 to the motors 152a, 152b, and 152c. A main controller 147 is provided, which controls the handle assembly 102. The main controller 147 is configured to execute software instructions embodied as algorithms, such as a clamping algorithm, a stapling algorithm, and a cutting algorithm that control the operation of the handle assembly 102 .

[0047] The motor controller 143 includes a plurality of sensors (not shown) configured to measure the operating state of the motors 152a, 152b, 152c and the battery 144. The sensors may include strain gauges, and may also include voltage sensors, current sensors, temperature sensors, telemetry sensors, optical sensors, and combinations thereof. The strain gauges may be disposed within the linear adapter 202. The sensors may measure the voltage, current, and other electrical characteristics of the electrical energy supplied by the battery 144. The sensors may also measure the angular velocity (e.g., rotational speed) in revolutions per minute (RPM), torque, temperature, current consumption, and other operating characteristics of the motors 152a, 152b, 152c. The sensors may also include an encoder configured to count the number of revolutions or other indicators of the motors 152a, 152b, 152c, which is then used by the main controller 147 to calculate the linear movement of the components that can be moved by the motors 152a, 152b, and 152c. Angular velocity can be determined by measuring the rotation of the motors 152a, 152b, 152c or a drive shaft (not shown) coupled to these motors and rotated by the motors 152a, 152b and 152c. The positions of the various axially movable drive shafts can also be determined by using various linear sensors disposed in or near the shafts, or extrapolated from RPM measurements. In an embodiment, torque can be calculated based on the adjusted current consumption of the motors 152a, 152b, 152c at a constant RPM. In other embodiments, the motor controller 143 and / or the main controller 147 can measure time and process the above values ​​as a function of time (including integration and / or differentiation), for example to determine the rate of change of the measured values. The main controller 147 is also configured to determine the distance traveled by various components of the linear adapter 202 and / or the end effector 206 by counting the number of revolutions of the motors 152a, 152b and 152c.

[0048] The motor controller 143 is coupled to a main controller 147, which includes a plurality of inputs and outputs for interfacing with the motor controller 143. In particular, the main controller 147 receives measured sensor signals from the motor controller 143 regarding the operating states of the motors 152a, 152b, 152c and the battery 144, and in turn outputs control signals to the motor controller 143 to control the operation of the motors 152a, 152b, 152c based on the sensor readings and specific algorithmic instructions. The main controller 147 is also configured to accept a plurality of user inputs from a user interface (e.g., switches, buttons, touch screen, etc.) coupled to the main controller 147.

[0049] The main controller 147 is also coupled to the memory 141. The memory 141 may include volatile memory (e.g., RAM) and non-volatile storage devices configured to store data (including software instructions for operating the handle assembly 102). The main controller 147 is also coupled to strain gauges (not shown) using a wired or wireless connection and is configured to receive strain measurements from the strain gauges, as well as impedance information, which will be used during operation of the handle assembly 102.

[0050] The handle assembly 102 includes a plurality of motors 152a, 152b, 152c, each of which includes a respective motor shaft (not explicitly shown) extending therefrom and configured to drive a respective transmission assembly. The rotation of the motor shaft caused by the respective motor serves to drive the shaft and / or gear components of the linear adapter 202 to perform various operations of the handle assembly 102. In particular, the motors 152a, 152b, 152c of the handle assembly 102 are configured to drive the shaft and / or gear components of the linear adapter assembly 202 to actuate the end effector 206.

[0051] The handle assembly 102 also includes a communication interface 162 that is configured to communicate using a wired (e.g., Serial Serial etc.) or wireless (e.g. Wireless Tiny 802.11IEEE and other radio, infrared, UHF, VHF communications, etc.) connection to the interface device 104. The interface device 104 is configured to store data transmitted to the interface device by the electric surgical instrument 200 and to process and analyze the data. The interface device 104 is also connected to other devices, such as the processor 451 of the EIT system 450 (when the processor is external to the surgical instrument 200) and the computing device 100.

[0052] Now go to Figure 4 and Figure 5 , the EIT system 450 includes a first electrode array 400, and in various aspects, further includes a second electrode array 500. The first electrode array 400 is coupled to the first jaw 208 ( Figure 2 ), and in the second electrode array 500 ( Figure 5), the second electrode array 500 is coupled to the second jaw 212 of the end effector 206. Although described in this particular configuration, the first electrode array 400 and / or the second electrode array 500 can be coupled to a probe (e.g., on a single side of a surgical device). The first electrode array 400 may include any suitable number of electrodes, which may be sixty electrodes arranged in multiple columns of fifteen electrodes, i.e., arranged as a first column of electrodes 401a...401o, a second column of electrodes 403a...403o, a third column of electrodes 405a...405o, and a fourth column of electrodes 407a...407o. Although sixty electrodes are shown and described, any number of electrodes may be utilized. Each electrode of the first electrode array may be 3 mm long and 1 mm wide. The second electrode array 500 may include eight electrodes, i.e., electrodes 501a, 501b, 501c, 501d, 501e, 501f, 501g, and 501h. Each electrode of the second electrode array 500 may be 3 mm long and 3 mm wide. Although described and illustrated as including an electrode array, the EIT system 450 can include any number of electrodes or electrode groups, e.g., one or more electrodes. For example, in various aspects, one or more of the first electrode array 400 and / or the second electrode array 500 include a number of electrodes ranging between eight electrodes and one hundred and twenty-eight electrodes.

[0053] In various aspects, the electrodes of the first electrode array 400 can be grouped into four different groups of ten electrodes (e.g., a first group 410, a second group 420, a third group 430, and a fourth group 440), wherein each group of ten electrodes is paired with eight electrodes of the second electrode array 500. Depending on the number of inputs included in the EIT system 450, the electrodes of the first electrode array 400 and / or the electrodes of the second electrode array 500 can be multiplexed to match the number of inputs required.

[0054] The EIT system 450 is configured to apply a current across the first electrode array 400 and the second electrode array 500 or across only the first electrode array 400, for example, at a frequency of about 10 kHz to about 80 kHz, but other frequencies, such as frequencies in the range of 100 Hz to 1 MHz, are also contemplated. The voltage difference across the first electrode array 400 and the second electrode array 500 or across only the first electrode array 400 is measured, and the processor 451 calculates the electrical impedance of the tissue based on the measured voltage difference. The EIT system 450 is configured to apply a current across any two electrodes of one or both of the first electrode array 400 and / or the second electrode array 500, and calculate the voltage difference between any two electrodes of one or both of the first electrode array 400 and / or the second electrode array 500. Therefore, the EIT system 450 can be configured to apply a current across electrodes of a single electrode array (e.g., the first electrode array 400) and measure the voltage, or to apply a current across electrodes of two electrode arrays (e.g., electrodes of the first electrode array 400 and electrodes of the second electrode array 500 are located on opposing jaws) and measure the voltage.

[0055] The processor 451 then generates an electrical impedance tomography reconstruction 600 based on the calculated electrical impedance ( Figure 6 ) to be displayed on the display 12 ( Figure 1 ) or for other processing (e.g., alerts and notifications) by computing device 100. The generated electrical impedance tomography reconstruction can be in 3D ( Figure 6 ) or as a 2D image visualization, where areas of high conductivity values, low conductivity values, or specific conductivity values ​​can be highlighted to show cancerous areas, mark different tissues, mark healthy states, and / or detect key structures. The EIT data set or reconstruction can also include reactance inclusions (e.g., inclusions with a dielectric constant). In various aspects, the processor can detect noise within the impedance data and filter noisy patterns before generating the electrical impedance tomography reconstruction 600.

[0056] refer to Figure 6 , an electrical impedance tomography reconstruction 600 is shown, which includes conductive inclusions 605 and resistive inclusions 607 reconstructed based on electrical impedance data. Conductive inclusions 605 can be optically distinguished from resistive inclusions 607 by being displayed in a different color or shade within the electrical impedance tomography reconstruction 600, but other non-optical or non-visual feedback can be combined in addition or alternatively. The data provided to form the electrical impedance tomography reconstruction 600 can also be used by the processor to detect tumor edges for display within the electrical impedance tomography reconstruction 600.

[0057] The following examples illustrate embodiments of the present disclosure. These examples are intended to be illustrative only and are not intended to limit the scope of the present disclosure.

[0058] Experiments and simulations

[0059] Simulation experiments were used to determine the ideal sensitivity threshold, evaluate modeling / noise factors (impedance noise, assumed suture separation errors), and evaluate the best way to analyze 3D EIT reconstruction. Further, single electrode array configuration / bottom electrode array configuration only (e.g., only the first electrode array 400) and dual electrode array configuration / top and bottom electrode array configuration (e.g., both the first electrode array 400 and the second electrode array 500) were evaluated in all experiments. This comparison of 1-side and 2-side electrode arrays can be used to develop a suture / EIT combination device that can be clinically translated because the two configurations will have different depth sensitivities. The technology was evaluated on ex vivo bovine samples to visualize and depict fat and muscle tissue. Accurate tissue reconstruction is a good indication of the robustness of the method in practice.

[0060] Two circuit boards containing gold-plated electrode arrays were used to simulate the two sides of a stapler or grasper. One side had sixty 3×1 mm closely spaced electrodes (bottom side), while the opposite side (top side) had eight 3×3 mm electrodes spaced further apart. A simulated grid of 700 ( Figure 7 ) to assist in segmenting the phantom. Although sixty electrodes are shown and described, any number of electrodes may be utilized. Both the first electrode array 400 and the second electrode array 500 span an area of ​​59×8 mm, which is a size suitable for fitting on a flat inner plate of a surgical stapler.

[0061] During the experiment, a 20-channel custom-built EIT system was used to collect EIT data. Due to the limited channel count, the 20 channels were multiplexed into four groups of 18 electrodes (e.g. Figure 4 The first group 410, the second group 420, the third group 430 and the fourth group 440 shown in the figure collect data from a subset of electrodes. Each group uses all eight electrodes on the top side and 10 electrodes in a single row on the bottom side. Therefore, only 48 of the 60 bottom electrodes are used. The EIT system collects a detailed IIVV mode of impedance data on these 18 electrode groups. Each measurement result is called the IIVV mode, where II represents the current injection electrode pair (I1, I2), and VV represents the differential voltage sensing pair (V1, V2) of the electrode. Before image reconstruction, all acquired data are pre-filtered to remove noisy patterns. Data is recorded at 4 frequencies (10, 20, 40 and 80kHz).

[0062] Forward Problem: The forward problem computes the voltage on the electrode given a specified injection current and internal conductivity distribution on the electrode. A complete electrode model (CEM) is used, which realistically accounts for the contact impedance and shunting of the electrode. The method utilizes a 3D finite element method (FEM) implementation that uses linear primitives on tetrahedral mesh construction for this scenario. For example, the mesh can be constructed via the DistMesh mesh generator (for generating 2D triangulation of the outer boundaries with encoded electrodes) and the Gmsh mesh generator (for generating a complete 3D mesh). The stitcher separation is in the z-direction, with the short and long stitcher axes given by the x- and y-axes, respectively (see Figure 7 ). The boards were assumed to have a constant separation distance of 10 mm (at any x / y position). Open domains (open in the x and y directions) were modeled by extending the mesh until the impedance was not affected by the boundaries. In summary, the mesh extended 50 mm in the x direction and 30 mm in the y direction. The mesh density near the electrodes and in the background region was empirically tuned to produce accurate impedance values. The entire mesh had ~160k nodes and 830k elements. Poorly shaped elements were eliminated via the Gmsh element shape optimization routine.

[0063] Inversion problem: A standard Gauss-Newton algorithm is used with Laplace smoothing and Tikhonov regularization to produce a 3D conductivity image. The goal is to minimize the following objective function:

[0064]

[0065] where δσ is the conductivity update, σ0 is the initial estimate, J is the Jacobian, and v Tst and v Ref are the test voltage and reference voltage, L is the regularization matrix, and λ is the Tychonoff regularization factor. The Jacobian is solved using lead field theory, which gives the appropriate sensitivity for each electrode / impedance measurement due to the size and geometry of each electrode in a physics-based manner. The least squares solution to (1) is:

[0066]

[0067] where J and Δv are the Jacobian and voltage difference data. This process can be iterated to obtain an absolute reconstruction.

[0068] A dual-grid approach was used that mapped the fine FEM grid onto a coarse inverse grid. This step solved the numerical problem and also allowed a convenient framework to separate inverse voxels with sufficient sensitivity for imaging from those that were not sensitive enough. The dual grid in this study was based on a rectilinear grid of voxels 36 × 40 × 8, resulting in voxels of size 3.0 × 3.0 × 1.3 mm. Therefore, the Jacobian J with respect to the coarse grid is C The size is the number of IIVV patterns (N iivv ) multiplied by the number of inverse voxels (N I ). The method relies on choosing a threshold S and computing the relative sensitivity vector across all IIVV modes:

[0069]

[0070] The inverse voxels smaller than a threshold are then grouped into so-called giant nodes, resulting in a single reconstructed conductivity value for all corresponding voxels. This approach is particularly useful in applications where the domain is open, the electrodes are only on a portion of the surface, and where there are large areas with very limited sensitivity.

[0071] Simulated and measured phantom experiments were performed that evaluated the ability to detect single inclusions of varying size, contrast, and location. The inclusion locations were based on the grid visible on the electrode array. A complete list of the inclusion parameters considered is given in Table I, which resulted in a total of 720 simulated samples. There were 25 measured phantom tests, a subset of those in Table I, and an explicit list is provided in Table II.

[0072] Table I. Simulated inclusion parameters

[0073]

[0074] Table II. Measured inclusion parameters

[0075]

[0076] *Indicates that duplicate measurements were performed on these samples.

[0077] The inclusion test was performed by first constructing a 10 mm thick agar gel mold that extended beyond the electrodes in each direction. The agar gel formula was 3% agar powder (Hoosier Hill Farm, Ft. Wayne, IN), 1% sorbitol in a 0.1 S / m saline solution. After mixing and heating, the liquid gel was poured into the test cell to obtain gel conductivity and poured into the mold to be 10 mm thick. The resulting gel was measured to be 0.115 S / m. Metal tubes of 8, 12.5 and 16.5 mm diameter were used to cut inclusions from the gel and filled with saline corresponding to the desired contrast. Saline drops and 700 g brass weights were used to ensure good electrode contact between the electrode array and the gel.

[0078] Two parameters need to be selected to optimize the reconstruction; the Tikhonov / regularization parameter (λ) and the sensitivity threshold (S). The Tikhonov parameter is selected to maximize resolution while limiting artifacts, and is selected heuristically by qualitative evaluation of a set of difference reconstructions. The sensitivity threshold is selected to maximize the area under the curve (AUC) from the receiver operating characteristic (ROC) curve analysis of all samples in the simulated database. The AUC analysis is performed on an x / y slice basis, i.e., using all voxels from all reconstructions of a given slice. At these voxels, the EIT values ​​are compared to markers (background or inclusions).

[0079] The simulation parameter database additionally allows the study of the effects of position, size, contrast, and the effects of varying voltage noise and reference height. Changing the reference height is a modeling error test that evaluates the effect of incorrectly modeling the distance between the top and bottom electrodes. In all voltage noise analyses, 20 replicates were sampled using unbiased, normally distributed noise at a specified percentage (0.1% to 5%) of the ideal voltage value.

[0080] Reconstructions using top and bottom electrodes or bottom electrodes only were considered throughout the analysis of simulated and measured inclusions. Top side electrodes were included to increase the depth of sensitivity but do increase the complexity of the system and may increase sensitivity to top-bottom array spacing.

[0081] Simulated inclusion testing: Simulated inclusion testing is used to 1) determine the optimal sensitivity threshold and x / y slice for analysis and 2) evaluate the sensitivity / impact of voltage noise, reference height mismatch, inclusion contrast, size, and x-offset. Reference height refers to the voltage used to calculate the reference voltage v Ref The grid height (or electrode array separation distance) of

[0082] The top and bottom electrodes ( Fig. 8A), and bottom electrode only ( Figure 8B ) AUC analysis with respect to x / y slices (z layers) and sensitivity thresholds revealed that: 1) the optimal z slice occurred at layer 2 from the bottom, and 2) a sensitivity threshold of 1 / 50 performed best regardless of which electrodes were used. Fig. 8A and Figure 8B There are two interesting aspects of the middle curve that are related to the shape of the sensitivity region. First, Fig. 8A In the example, the sensitive region is large near the top and bottom electrodes, but narrows in the center. This narrowing becomes a gradually increasing factor as the sensitivity threshold increases, i.e., note that Fig. 8A There are two peaks with central minima for higher sensitivity thresholds 1 / 50 and 1 / 100 in FIG. Similarly, when only the bottom electrode is used, the sensitivity area decreases significantly with higher thresholds, i.e., notice that Figure 8B All subsequent reconstructions used a 1 / 50 threshold and were analyzed at the 2nd z-slice.

[0083] Voltage Noise( Fig.9A ) and reference height ( Fig. 9B ) on AUC reveals minimal accuracy loss for noise up to 1%, and that the bottom-only reconstruction is much less sensitive to height mismatch. Specifically, AUC remains ~0.98 for voltage errors up to 1%, regardless of which electrodes are used, and drops to 0.97 at 2%. There is only a significant difference between the electrodes used at 5% noise (0.93 for bottom and top, and 0.90 for bottom only). In terms of reference height, if there is a 1mm error in the assumed separation (9mm or 11mm), the top and bottom electrodes result in a drop to 0.90 to 0.91, compared to a drop to 0.94 to 0.95 for the bottom electrode only, with the maximum AUC being 0.97, regardless of the electrodes used, and occurring when there is no reference height error.

[0084] The final factor considered was the AUC relative to inclusion contrast, size, and distance ( FIG. 10A to FIG. 10C ). Here, distance is the x / y distance from the electrode to the center of the inclusion. Contrast appears to be the factor with the greatest impact. The AUC for the bottom electrode only and the top and bottom electrodes at 10% contrast drop to 0.91 and 0.94, respectively, compared to a peak of 0.99 achieved at 30% and greater contrast. Size and distance variations have smaller effects, but in each case the bottom only results are slightly worse compared to the top and bottom electrodes. Regarding size, the bottom electrode only produces an AUC of 0.94 compared to 0.97, and regarding distance, there is a 1% drop for distances of 4mm and 8mm.

[0085] Based on simulation testing, the optimal area for analysis is within the 2nd x / y slice (z slice) (1.25mm from the bottom electrode), and when a sensitivity threshold of 1 / 50 is used, the optimal area extends essentially to the edge of the electrode. Although it is necessary to model the current flowing beyond / outside the array, it is intuitive that the most accurately imaged area falls directly between the arrays. The optimal z slice is slightly less intuitive. Electrode artifacts are often found in EIT, so imaging of the layers closest to the 60 electrodes side may be more challenging. Also, 1) quality may decrease in the middle of the domain with the least sensitivity, and 2) x / y resolution may be slightly limited toward the top side because there are only 8 electrodes. Finally, Niu's tests seem to suggest that the area for analysis should be further reduced in the y direction to approximately half of the total range. This was unexpected based on simulation testing and measured gel testing.

[0086] Although the present disclosure is presented with respect to a surgical instrument including a handle assembly, it should be understood that the principles of the present disclosure can also be applied to a robotic surgical system that technically does not include a handle assembly. The disclosed GUI solution can be suitable for a teleoperated robotic surgical system. It should be understood that various modifications can be made to the embodiments of the currently disclosed stapler. Therefore, the above description should not be interpreted as restrictive, but merely as an example of an embodiment. Those skilled in the art will envision other modifications within the scope and spirit of the present disclosure.

[0087] In one or more examples, the described techniques may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as one or more instructions or codes on a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media may include non-transitory computer-readable media, which corresponds to tangible media such as data storage media (e.g., RAM, ROM, EEPROM, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and can be accessed by a computer).

[0088] Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general-purpose microprocessors, application-specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuits. Accordingly, the term "processor" as used herein may refer to any of the above structures or any other physical structures suitable for implementing the described techniques. In addition, these techniques may be fully implemented in one or more circuits or logic elements.

Claims

1. A surgical system, comprising: A surgical stapler comprising an end effector including a first jaw having an anvil and a second jaw having a stapler cartridge; as well as An electrical impedance tomography system, the electrical impedance tomography system comprising: an electrode array comprising a plurality of electrodes operably coupled to the first jaw; and A processor, the processor being configured to: controlling application of current across electrodes of the electrode array; measuring a voltage difference across electrodes of the electrode array; calculating an electrical impedance based on the measured voltage difference; and An electrical impedance tomography reconstruction is generated based on the calculated electrical impedance.

2. The surgical system of claim 1, wherein: The electrode array includes a plurality of electrodes.

3. The surgical system of claim 1, wherein: Each electrode of the electrode array is about 3 mm long and about 1 mm wide.

4. The surgical system of claim 1, wherein: The electrodes of the electrode array are arranged in four columns and fifteen rows.

5. The surgical system of claim 1, wherein: The electrodes of the electrode array are grouped into four different groups of ten electrodes.

6. The surgical system of claim 1, wherein: The processor is configured to filter the calculated electrical impedance by removing noisy patterns prior to generating the electrical impedance tomography reconstruction.

7. The surgical system of claim 1, wherein: The generated electrical impedance tomography reconstruction includes conductive inclusions and resistive inclusions, wherein the conductive inclusions are optically distinguishable from the resistive inclusions.

8. The surgical system of claim 1, wherein: The processor is configured to detect a tumor margin based on the electrical impedance tomography reconstruction.

9. The surgical system of claim 1, wherein: The processor is configured to control the application of the current at a frequency of about 10 kHz to about 80 kHz.

10. An electric surgical instrument, comprising: an end effector, the end effector comprising a first clamping jaw and a second clamping jaw; An electrical impedance tomography system, the electrical impedance tomography system comprising: a first electrode array comprising a plurality of electrodes operably coupled to the first jaw; a second electrode array comprising a plurality of electrodes operably coupled to the second jaw; and A processor, the processor being configured to: controlling application of current across the first electrode array and the second electrode array; measuring a voltage difference across the first electrode array and the second electrode array; calculating an electrical impedance based on the measured voltage difference; and An electrical impedance tomography reconstruction is generated based on the calculated electrical impedance.

11. The electric surgical instrument according to claim 10, wherein: The first electrode array includes sixty electrodes and the second electrode array includes eight electrodes.

12. The electric surgical instrument according to claim 10, wherein: Each electrode of the first electrode array is about 3 mm long and about 1 mm wide, and each electrode of the second electrode array is about 3 mm long and about 3 mm wide.

13. The electric surgical instrument according to claim 10, wherein: The electrodes of the first electrode array are arranged in four columns and fifteen rows, and the electrodes of the second electrode array are arranged in two columns and four rows.

14. The electric surgical instrument according to claim 10, wherein: At least a portion of the plurality of electrodes of the first electrode array are grouped into four different groups of ten electrodes, each group of ten electrodes being paired with eight electrodes of the second electrode array.

15. The electric surgical instrument according to claim 10, wherein: The processor is configured to filter the calculated electrical impedance by removing noisy patterns prior to generating the electrical impedance tomography reconstruction.

16. The electric surgical instrument according to claim 10, wherein: The generated electrical impedance tomography reconstruction includes conductive inclusions and resistive inclusions, wherein the conductive inclusions are optically distinguishable from the resistive inclusions.

17. The electric surgical instrument according to claim 10, wherein: The processor is configured to detect a tumor margin based on the electrical impedance tomography reconstruction.

18. The electric surgical instrument according to claim 10, wherein: The processor is configured to control application of the current across the first electrode array and the second electrode array at a frequency of about 10 kHz to about 80 kHz.

19. A surgical system comprising: An electric surgical instrument, the electric surgical instrument comprising a first clamping jaw and a second clamping jaw; An electrical impedance tomography system, the electrical impedance tomography system comprising: a first electrode array comprising a plurality of electrodes operably coupled to the first jaw; a second electrode array comprising a plurality of electrodes operably coupled to the second jaw; and A processor, the processor being configured to: controlling application of current across the first electrode array and the second electrode array; measuring a voltage difference across the first electrode array and the second electrode array; calculating an electrical impedance based on the measured voltage difference; and generating an electrical impedance tomography reconstruction based on the calculated electrical impedance; and A display is operably coupled to the electrical impedance tomography system and configured to display the electrical impedance tomography reconstruction.

20. The surgical system of claim 19, wherein: The processor is configured to control application of the current across the first electrode array and the second electrode array at a frequency of about 10 kHz to about 80 kHz.

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