Electrical impedance tomography device and system

Abstract

The 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 the first jaw and / or the second jaw, and a processor. The processor is configured to control the application of a 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

Technical Field

[0001] The present disclosure relates to surgical devices. More specifically, the present disclosure relates to a surgical device including an array of electrodes for electrical impedance tomography and a system for reconstructing electrical impedance tomography images.

Background Art

[0002] Surgical staplers are commonly used in a number of open and laparoscopic cancer resections, including thoracic surgery, bariatric surgery, and rectal surgery. For example, during lung surgery, surgical staplers are often used to cut a wedge resection around a pulmonary nodule suspected of cancer. However, small pulmonary nodules may be invisible and imperceptible under thoracoscopy during surgery, and different positioning methods, such as hook wires, dyes, fiducial markers, contrast agents, or radiation tracers, are required. These positioning methods are often very effective. For example, in the case of a hook wire via computed tomography (CT) guidance for positioning, it has a success rate of 93.6 - 97.6%, but has certain weaknesses and may fail.

[0003] Since the cancer has been previously identified, the size of the discovered tumor is smaller. This can make it difficult to identify the tumor during surgery. This is particularly true for lung cancer. CT images can confirm the presence of cancer, but since the shape changes during contraction during surgery, it is still not easy to convert to the shape of the lung. In addition, since cancer may be very small or very deep within soft tissue, surgeons may not be able to confirm them using video-assisted thoracic surgery (VATS) or even palpate them during an open procedure. Therefore, a method for positioning cancerous pulmonary nodules or malignant tissue in general is needed.

Summary of the Invention

Means for Solving the Problems

[0004] 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 cartridge. The EIT system includes an electrode array including a plurality of electrodes operably coupled to the first jaw, and a processor. The processor is configured to control application of a 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.

[0005] In one aspect, the electrode array can include 60 electrodes.

[0006] In one aspect, each electrode of the electrode array can have a length of about 3 mm and a width of about 1 mm. As used herein, the term "about" means ±5% from a numerical value.

[0007] In one aspect, the electrodes of the electrode array can be arranged in 4 columns and 15 rows.

[0008] In one aspect, the electrodes of the electrode array can be grouped into 4 separate sets of 10 electrodes.

[0009] In one aspect, the processor can be configured to filter the calculated electrical impedance by removing a noisy pattern before generating the electrical impedance tomography reconstruction.

[0010] In one aspect, the generated electrical impedance tomography reconstruction may include conductive inclusions and resistive inclusions, and the conductive inclusions are visually distinguishable from the resistive inclusions.

[0011] In one aspect, the processor can be configured to detect a tumor boundary based on the electrical impedance tomography reconstruction.

[0012] In one aspect, the processor may be configured to control the application of current at a frequency of about 10 kHz to about 80 kHz.

[0013] In another aspect of the present disclosure, a powered surgical instrument is provided. The powered 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 coupled to the first jaw, a second electrode array including a plurality of electrodes operably coupled 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 a voltage difference across the first electrode array and the second electrode array (e.g., any other two electrodes of the first electrode array and the second electrode array), or a voltage difference between any two electrodes of the first electrode array or the second 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.

[0014] In one aspect, the first electrode array may include 60 electrodes, and the second electrode array includes 8 electrodes.

[0015] In one aspect, each electrode of the first electrode array may have a length of about 3 mm and a width of about 1 mm, and each electrode of the second electrode array may have a length of about 3 mm and a width of about 3 mm.

[0016] In one aspect, the electrodes of the first electrode array may be arranged in 4 columns and 15 rows, and the electrodes of the second electrode array may be arranged in 2 columns and 4 rows.

[0017] In one aspect, at least a portion of the plurality of electrodes of the first electrode array may be grouped into four separate sets of 10 electrodes, and each set of 10 electrodes may be paired with the 8 electrodes of the second electrode array.

[0018] In one aspect, the processor may be configured to filter the calculated electrical impedance by removing noisy patterns before generating an electrical impedance tomography reconstruction.

[0019] In one aspect, the generated electrical impedance tomography reconstruction may include conductive inclusions and resistive inclusions, and the conductive inclusions are optically distinguishable from the resistive inclusions.

[0020] In one aspect, the processor may be configured to detect a tumor boundary based on the electrical impedance tomography reconstruction.

[0021] In one aspect, the processor may be configured to control the application of current across the first electrode array and the second electrode array at a frequency of about 10 kHz to about 80 kHz.

[0022] In another aspect of the present disclosure, a surgical system includes a powered surgical instrument, an electrical impedance tomography system, and a display. The powered surgical instrument includes a first jaw and a second jaw. The electrical impedance tomography system includes a first electrode array including a plurality of electrodes operably coupled to the first jaw, a second electrode array including a plurality of electrodes operably coupled 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 an electrical impedance tomography reconstruction based on the calculated electrical impedance. The display is operably coupled to the electrical impedance tomography system and is configured to display the electrical impedance tomography reconstruction.

[0023] In one aspect, the processor may be configured to control the application of current across the first electrode array and the second electrode array at a frequency of about 10 kHz to about 80 kHz.

[0024] Embodiments of the present disclosure are described herein with reference to the accompanying drawings.

Brief Description of the Drawings

[0025]

Figure 1

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Figure 10

[0026] Embodiments of the surgical devices disclosed herein, as well as adapter assemblies for surgical devices and / or handle assemblies, are described in detail with reference to the drawings, in which like reference numerals designate the same or corresponding elements in each of the several views. As used herein, the term "distal" refers to a part of a surgical instrument or a component thereof that is farther from the user, while the term "proximal" refers to a part of a surgical instrument or a component thereof that is closer to the user.

[0027] The present disclosure provides for the incorporation of electrical impedance tomography (EIT) into surgical devices such as laparoscopic staplers, surgical probes, surgical grasping instruments, or any other surgical device to generate electrical impedance tomography reconstructions or other electrical impedance datasets (e.g., EIT mapping) to enable intraoperative identification of nodule (e.g., tumor) boundaries. Although detection of tumor boundaries is described, it is contemplated that embodiments may also be utilized to detect disease states and / or critical structures. In embodiments, other surgical instruments including, but not limited to, grasping instruments, vessel sealers (bipolar or ultrasonic), wands, probes, etc. may incorporate the EIT system according to the present disclosure.

[0028] EIT estimates electrical properties from many combinations of impedance measurements recorded from electrodes placed in tissue. Electrical impedance (Z) may be calculated using a four-point measurement, i.e., a current (I) can be applied across two electrodes and the voltage difference (V) from two other electrodes can be measured (Z = V / I). Significant cellular and extracellular differences between benign and malignant tissue or other tissue and nodules result in significant differences in electrical impedance.

[0029] FIG. 1 shows a surgical system 10 that 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 and virtual reality headset, 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 configured to communicate with the surgical instrument 200, and the surgical instrument can include a modular surgical stapler (e.g., a linear stapler, a circular stapler, etc.) that can be either powered or non-powered. The interface device 104 is further configured to receive device information from the surgical instrument 200 and process the device information for display on the one or more displays 12.

[0030] The surgical system 10 further includes an electrical impedance tomography (EIT) system 450 configured to generate an electrical impedance tomography reconstruction 600 (FIG. 6) of a portion of the surgical site for display on the display 12. The EIT system 450 may be fully incorporated into the surgical instrument 200 or may be configured to output data to the computing device 100 for additional processing and display on the display 12. Alternatively, the EIT system 450 may include one or more components incorporated within the surgical instrument 200 and one or more components separate from the surgical instrument 200.

[0031] In one aspect, the surgical instrument 200 may be a powered surgical instrument, such as a powered surgical stapler 200a (Figs. 2 and 3). Fig. 2 shows the components of an exemplary powered surgical stapler 200a that includes a power platform, i.e., a handle assembly 102 that includes one or more motors, a power source, a main controller, a memory device, a transmitter / receiver, etc. The powered surgical stapler 200a also includes a linear adapter 202 configured to connect the handle assembly 102 to a loading unit 204 that includes an end effector 206 having a first jaw 208 with a stapler cartridge 210 and a second jaw 212 with an anvil 214. The linear adapter 202 includes various mechanical linkage mechanisms that couple the end effector 206 to the handle assembly 102, enabling the operation of the end effector 206 to perform various functions such as clamping, stapling, cutting, etc. For further details regarding the structure and operation of the linear stapler components, reference can be made to U.S. Patent No. 9,839,425, filed Mar. 30, 2015, the entire contents of which are incorporated herein by reference.

[0032] Referring to FIG. 3, the handle assembly 102 includes a main controller circuit board 142, a rechargeable battery 144 configured to supply power to any of the electrical components of the handle assembly 102, and a plurality of motors coupled to the battery 144, such as a first motor 152a, a second motor 152b, and a third motor 152c. The handle assembly 102 also includes a display 146. In an embodiment, the motors 152a, 152b, 152c may be coupled to any suitable power source configured to supply electrical energy to the motors 152a, 152b, 152c, such as an AC / DC transformer. Each of the motors 152a, 152b, 152c is coupled to a motor controller 143 that controls the operation of the corresponding motor 152a, 152b, 152c, including the flow of electrical energy from the battery 144 to the motors 152a, 152b, 152c. A main controller 147 for controlling the handle assembly 102 is provided. The main controller 147 is configured to execute software instructions that implement algorithms for controlling the operation of the handle assembly 102, such as clamping, stapling, and cutting algorithms.

[0033] The motor controller 143 includes a plurality of sensors (not shown) configured to measure the operating states of the motors 152a, 152b, 152c, and the battery 144. The sensors may include strain gauges, and may further 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 measure the angular velocity as revolutions per minute (RPM) (e.g., rotational speed), torque, temperature, draw current, and other operating characteristics of the motors 152a, 152b, 152c. The sensors may also include an encoder configured to count the rotation or other indicators of the motors 152a, 152b, 152c, which is then used by the main controller 147 to calculate the linear motion of the components movable by the motors 152a, 152b, 152c. The angular velocity may be determined by measuring the rotation of the motors 152a, 152b, 152c or a drive shaft (not shown) coupled to the motors and rotatable by the motors 152a, 152b, 152c. The position of the drive shaft movable in various axial directions may also be determined using various linear sensors disposed within or proximate to the shaft, or may be extrapolated from the RPM measurements. In an embodiment, the torque may be calculated based on the regulated draw current of the motors 152a, 152b, 152c at a constant RPM. In a further embodiment, the motor controller 143 and / or the main controller 147 measures time and processes the above-described values as a function of time, including integration and / or differentiation, to determine, for example, the rate of change of the measured values. The main controller 147 is also configured to determine the distance traveled by the various components of the linear adapter 202 and / or the end effector 206 by counting the rotations of the motors 152a, 152b, 152c.

[0034] The motor controller 143 is coupled to the main controller 147, which includes a plurality of inputs and outputs for interfacing with the motor controller 143. Specifically, the main controller 147 receives sensor signals measured regarding the operating conditions of the motors 152a, 152b, 152c and the battery 144 from the motor controller 143, and then outputs control signals for controlling the operations of the motors 152a, 152b, 152c to the motor controller 143 based on the sensor readings and specific algorithm instructions. The main controller 147 is also configured to receive a plurality of user inputs from a user interface (such as switches, buttons, touch screens, etc.) coupled to the main controller 147.

[0035] The main controller 147 is also coupled to the memory 141. The memory 141 may include a volatile memory device (such as RAM) and a non-volatile memory device configured to store data including software instructions for operating the handle assembly 102. The main controller 147 is also coupled to a strain gauge (not shown) using a wired or wireless connection and is configured to receive strain measurement values and further impedance information from the strain gauge, which are used during the operation of the handle assembly 102.

[0036] The handle assembly 102 includes a plurality of motors 152a, 152b, 152c, and each motor includes a respective motor shaft (not explicitly shown) that extends from the motor and is configured to drive a respective transmission assembly. The rotation of the motor shaft by each motor functions to drive the drive shaft and / or gear components of the linear adapter 202 to perform various operations of the handle assembly 102. Specifically, 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 operate the end effector 206.

[0037] The handle assembly 102 also includes a communication interface 162 configured to connect to an interface device 104 using a wired connection (e.g., Firewire®, USB®, Serial RS232®, Serial RS485®, USART®, Ethernet®, etc.) or a wireless connection (e.g., Bluetooth®, ANT3®, KNX®, ZWave®, X10® Wireless USB®, IrDA®, Nanonet®, Tiny OS®, ZigBee®, 802.11 IEEE, and other wireless, infrared, UHF, VHF communications, etc.). The interface device 104 is configured to store data transmitted to the interface device by the powered surgical instrument 200 and to process and analyze that data. The interface device 104 is also connected to other devices such as a processor 451 of the EIT system 450 (when the processor is external to the surgical instrument 200) and a computing device 100.

[0038] Returning now to FIGS. 4 and 5, the EIT system 450 includes a first electrode array 400 and, in some embodiments, also includes a second electrode array 500. The first electrode array 400 is coupled to the first jaw 208 (FIG. 2) of the end effector 206, and in embodiments that include the second electrode array 500 (FIG. 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 may be coupled to a probe (e.g., at a single side of a surgical device). The first electrode array 400 may include any suitable number of electrodes, which may be, for example, 60 electrodes arranged in 15 rows, i.e., a first row of electrodes 401a - 401o, a second row of electrodes 403a - 403o, a third row of electrodes 405a - 405o, and a fourth row of electrodes 407a - 407o. Although 60 electrodes are shown and described, any number of electrodes may be utilized. Each electrode of the first electrode array may be 3 mm in length and 1 mm in width. The second electrode array 500 may include 8 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 in length and 3 mm in width. Although described and shown as including an array of electrodes, the EIT system 450 may include any number of electrodes or groups of electrodes, e.g., one or more electrodes. For example, in some embodiments, one or more of the first electrode array 400 and / or the second electrode array 500 includes a number of electrodes in the range of 8 to 128 electrodes.

[0039] In some embodiments, the electrodes of the first electrode array 400 may be grouped into four separate sets of 10 electrodes (e.g., a first set 410, a second set 420, a third set 430, and a fourth set 440), and each set of 10 electrodes is paired with the 8 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 may be multiplexed to match the desired number of inputs.

[0040] The EIT system 450 is configured to apply a current across the first electrode array 400 and the second electrode array 500, or across the first electrode array 400 only, at a frequency, for example, in the range of about 10 kHz to about 80 kHz, although other frequencies, for example, in the range of 100 Hz to 1 MHz, are conceivable. A voltage difference across the first electrode array 400 and the second electrode array 500, or across the first electrode array 400 only, 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. Thus, the EIT system 450 can be configured to apply a current across the electrodes of a single electrode array (e.g., the first electrode array 400) and measure the voltage, or apply a current across the electrodes of two electrode arrays (e.g., the electrodes of the first electrode array 400 and the electrodes of the second electrode array 500 located on the opposing jaw) and measure the voltage.

[0041] The processor 451 then generates an electrical impedance tomography reconstruction 600 (FIG. 6) based on the calculated electrical impedance for display on the display 12 (FIG. 1) of the computing device 100 or for other processing (e.g., alerts and notifications) by the computing device 100. The generated electrical impedance tomography reconstruction can be visualized as a 3D image (FIG. 6) or as a 2D image, in which regions of high, low, or specific conductivity values are highlighted to indicate cancer regions, to clearly distinguish different tissues, to clearly distinguish health states, and / or to detect important structures. The EIT dataset or reconstruction can also include reactance inclusions (e.g., inclusions having a dielectric constant). In an aspect, the processor may detect noise in the impedance data and filter out noisy patterns before generating the electrical impedance tomography reconstruction 600.

[0042] Referring to FIG. 6, an electrical impedance tomography reconstruction 600 including conductive inclusions 605 and resistive inclusions 607 reconstructed based on electrical impedance data is shown. The conductive inclusions 605 can be optically distinguished from the resistive inclusions 607 by being displayed in different colors or shades in the electrical impedance tomography reconstruction 600. Additionally or alternatively, other non-optical or non-visual feedback can be incorporated. The data provided to form the electrical impedance tomography reconstruction 600 may also be used by a processor to detect tumor boundaries for display within the electrical impedance tomography reconstruction 600.

[0043] The following examples illustrate embodiments of the present disclosure. These examples are intended for illustration only and are not intended to limit the scope of the present disclosure.

Examples

[0044] Experiments and Simulations Simulated experiments were used to determine the ideal sensitivity threshold, evaluate modeling / noise factors (impedance noise, errors in assumed stapler separation), and assess the best way to analyze 3D EIT reconstructions. Additionally, both single / bottom-only electrode array structures (e.g., only the first electrode array 400) and dual / top and bottom electrode array structures (e.g., both the first electrode array 400 and the second electrode array 500) were evaluated in all experiments. Such a comparison between single-sided and double-sided electrode arrays is useful in developing clinically translatable stapler / EIT combined devices because the two configurations will have different depth sensitivities. The technique was evaluated in ex vivo bovine specimens for visualization and characterization of fat and muscle tissue. Accurate tissue reconstruction is a good indicator of the robustness of the method in practice.

[0045] To mimic the two sides of a stapler or grasping instrument, two circuit boards containing an array of plated electrodes were used. One side has 60 closely spaced 3×1 mm electrodes (bottom side), while the opposite (top) side has 8 more spaced 3×3 mm electrodes. A simulated grid mark 700 (Figure 7) using a 4 mm spacing was used as an aid in dividing the phantom. Although 60 electrodes are shown and described, any number of electrodes may be utilized. Both the first and second electrode arrays 400, 500 span a 59×8 mm area, which is a suitable size for incorporation onto the flat inner plate of a surgical stapler.

[0046] During the experiment, EIT data was collected using a 20-channel custom EIT system. Since the channel count was limited, data was collected from a subset of electrodes by multiplexing the 20 channels into 4 sets of 18 electrodes (e.g., the first set 410, the second set 420, the third set 430, and the fourth set 440 shown in Figure 4). Each set uses all 8 electrodes from the top side and 10 electrodes from a single row on the bottom side. Thus, only 48 out of the 60 bottom electrodes are used. The EIT system collects a comprehensive IIVV pattern of impedance data on the 18-electrode sets. Each measurement is called an IIVV pattern, where II represents the current injection electrode pair (I1, I2) and VV represents the differential voltage sensing electrode pair (V1, V2). To remove noisy patterns, all the acquired data was pre-filtered before image reconstruction. The data was recorded at four frequencies, namely 10, 20, 40, and 80 kHz.

[0047] Forward problem: The forward problem calculates the voltage on the electrodes when the current injected into the electrodes and the internal conductivity distribution are specified. The complete electrode model (CEM) was used. This realistically takes into account the contact impedance and shunting of the electrodes. This method utilized a 3D finite element method (FEM) implementation using linear basis elements on a tetrahedral mesh constructed for this scenario. For example, the mesh may be constructed via a DistMesh mesh generator for generating a 2D triangulation of the outer boundary using encoded electrodes and a Gmsh mesh generator for generating a complete 3D mesh. The staple separation is in the z - direction, and the short and long axes of the staple are given by the x - and y - axes respectively (see Figure 7). The circuit board was assumed to have a constant separation distance of 10 mm (at any x / y position). The open domain (open in the x and y directions) was modeled by extending the mesh until the impedance was no longer affected by the boundary. Overall, the mesh was 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 experimentally adjusted to produce accurate impedance values. The entire mesh had approximately 160k nodes and 830k elements. Abnormal - shaped elements were removed via Gmsh's element - shape optimization routine.

[0048] Inverse problem: A 3D conductivity image was generated using a standard Gauss - Newton algorithm with Laplacian smoothing Tikhonov regularization. The goal was to minimize the following objective function:

Equation

Number

[0049] A double-mesh method that maps a fine FEM mesh to a coarse inverse mesh is used. This step addresses numerical concerns and further enables a convenient framework for separating inverse voxels with sufficient sensitivity for imaging from images with insufficient sensitivity. The double mesh in this study is based on a linear grid of 36×40×8 voxels, resulting in voxels of size 3.0×3.0×1.3 mm. Thus, the size of the Jacobian J C on the coarse mesh is the product of the number of IIVV patterns (N iivv ) and the number of inverse voxels (N I ). The method depends on selecting a threshold S and calculating the vector of relative sensitivities over the entire set of all IIVV patterns:

Number

[0050] Subsequently, inverse voxels smaller than the threshold are grouped into so-called meganoodes to obtain 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 there are large regions with very limited sensitivity.

[0051] Simulated and measured phantom experiments were conducted to evaluate the ability to detect single inclusions of various sizes, contrasts, and positions. The inclusion positions are based on a grid visible on the electrode array. A complete list of the inclusion parameters considered is given in Table I, and the total number of simulated samples was 720. Twenty-five measured phantom tests, which are a subset from Table I, were conducted, and an explicit list of them is shown in Table II.

[0052]

Table 1

[0053]

Table 2

[0054] The measurement inclusion test was carried out by first fabricating an agar gel mold with a thickness of 10 mm extending in each direction beyond the electrodes. The recipe for the agar gel was 3% agar powder (Hoosier Hill Farm, Ft. Wayne, IN) and 1% sorbitol in a 0.1 S / m physiological saline solution. After mixing and heating, the liquid gel was poured into a test cell to obtain a gel conductivity and made into a 10-mm-thick mold. The resulting gel was measured to be 0.115 S / m. Metal tubes with diameters of 8, 12.5, and 16.5 mm were used to cut out inclusions from the gel and filled with physiological saline corresponding to the desired contrast. To ensure good electrode contact between the electrode array and the gel, droplets of physiological saline and a 700-g brass weight were used.

[0055] Two parameters, namely the Tikhonov / regularization parameter (λ) and the sensitivity threshold (S), needed to be selected to optimize the reconstruction. The Tikhonov parameter was selected to maximize the resolution while restricting artifacts and was selected heuristically through qualitative evaluation across different sets of reconstructions. The sensitivity threshold was chosen to maximize the area under the curve (AUC) from receiver operating characteristic (ROC) curve analysis across all samples of the simulated database. The AUC analysis was performed based on x / y slices. That is, all voxels from all reconstructions from a given slice were used. On these voxels, the EIT values were compared to the label (background or inclusion).

[0056] The simulated database of parameters also enabled the study of the effects of position, size, contrast, as well as varying voltage noise and reference height. Varying the reference height is a modeling error test to evaluate the effect of erroneously modeling the distance between the upper and bottom electrodes. In all voltage noise analyses, unbiased normally distributed noise at a specific percentage (0.1 - 5%) of the ideal voltage value was used, and 20 repetitions were sampled.

[0057] Throughout the analysis of simulated and measured inclusion reconstructions, reconstructions using only the upper and bottom electrodes or only the bottom electrode were considered. The upper side electrodes were included to improve the depth of sensitivity but added complexity to the system and could increase the sensitivity to the upper-bottom array spacing.

[0058] Simulated inclusion tests: Simulated inclusion tests were used to 1) determine the best sensitivity threshold and x / y slices for analysis and 2) evaluate the sensitivity / effect of voltage noise, reference height mismatch, inclusion contrast, size, and x offset. The reference height refers to the mesh height (or electrode array separation distance) used to calculate the reference voltage v Ref .

[0059] Results of AUC analysis for the x / y slice (z-layer) and sensitivity thresholds, for the top and bottom electrodes (Figure 8A) and bottom only (Figure 8B): 1) it was revealed that the best z-slice occurs in the second layer from the bottom, and 2) the 1 / 50 sensitivity threshold functions best regardless of which electrode is used. In the curves of Figures 8A and 8B, there are two interesting aspects related to the shape of the sensitivity region. First, in Figure 8A, the sensitivity region is large near the top and bottom electrodes but narrow in the center. This narrowing is a factor that increases with the increase in the sensitivity threshold, i.e., in Figure 8A, for the higher sensitivity thresholds of 1 / 50 and 1 / 100, there are two humps and it is minimized in the center. Similarly, in Figure 8B, when using only the bottom electrode, the sensitivity region is significantly reduced for higher thresholds, i.e., it should be noted that increasing the threshold reduces the z-layer. All subsequent reconstructions were analyzed at the second z-slice using the 1 / 50 threshold.

[0060] The influence on AUC from voltage noise (Figure 9A) and reference height (Figure 9B) reveals that the loss of accuracy is minimal for noise up to 1%, and the sensitivity to height mismatch is much smaller in the bottom-only reconstruction. Specifically, the AUC remains at approximately 0.98 up to a 1% voltage error regardless of which electrode is used, and only drops to 0.97 up to 2%. There is only a significant difference between the electrodes used at 5% noise (0.93 for the top and bottom, 0.90 for the bottom only). From the perspective of the reference height, in the case of an assumed separation with an error of 1 mm (in the case of 9 mm or 11 mm), compared to 0.94 - 0.95 for the bottom electrode only, it drops to 0.90 - 0.91 for the top and bottom electrodes, and the maximum AUC is 0.97 regardless of the electrode used and occurs when there is no reference height error.

[0061] The last factor considered is the AUC vs inclusion contrast, size, and distance (Figs. 10A - 10C). Here, the distance is the x / y distance from the electrode to the center of the inclusion. Contrast appears to be the factor with the most impact. The AUC for the bottom only, as well as for the top and bottom electrodes, was reduced to 0.91 and 0.94 respectively at 10% contrast compared to peak values of 0.99 achieved at 30% contrast. Variations in size and distance had a smaller impact, but in both cases, the bottom only results were slightly worse compared to the top and bottom electrodes. For size, the bottom only electrode yielded an AUC of 0.94 compared to 0.97, and for distance, there was a 1% decrease at distances of 4 and 8 mm.

[0062] Based on the simulation tests, the optimal region for analysis is within the second x / y slice (z - slice) (1.25 mm from the bottom electrode) and, when using a sensitivity threshold of 1 / 50, extends basically to the edge of the electrode. It is necessary to model the current flowing beyond the array / outside the array, but it is intuitive that the region that is imaged most accurately is directly between the arrays. The optimal z - slice is somewhat less intuitive. In EIT, electrode artifacts are often found, so it can be more challenging to image the layer closest to the sides of the 60 electrodes. Similarly, 1) the quality can degrade in the middle of the domain where the sensitivity is minimum, 2) the x / y resolution can be somewhat limited towards the upper side because there are only 8 electrodes. Finally, the bovine tests seem to imply that the region for analysis should be further reduced to approximately half of the full range in the y - direction. This was unexpected based on the simulated tests and the measured gel tests.

[0063] While 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 may also be applied, technically, to a robotic surgical system that does not include a handle assembly. The disclosed GUI approach may be adapted in a robotic surgery system for remote operation. It will be understood that various changes may be made to the stapler embodiments disclosed herein. Accordingly, the above description should not be construed as limiting, but should be construed merely as illustrative of embodiments. Those skilled in the art will envision other modifications within the scope and spirit of the present disclosure.

[0064] In one or more embodiments, the techniques described may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. The computer-readable medium may include a non-transitory computer-readable medium corresponding to a tangible medium such as a data storage medium (e.g., RAM, ROM, EEPROM, flash memory, or any other medium that can be used to store the desired program code in the form of instructions or data structures and that can be accessed by a computer).

[0065] The 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 logic circuits or discrete logic circuits. Accordingly, the term "processor" as used herein may refer to any of the foregoing structures, or any other physical structure suitable for implementation of the techniques described. Also, the techniques may be implemented entirely in one or more circuits or logic elements.

Claims

1. A surgical stapler comprising an end effector including a first jaw having an anvil and a second jaw having a stapler cartridge, and an electrical impedance tomography system, an electrode array including a plurality of electrodes operably coupled to the first jaw, and a processor configured to control application of a 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, the electrical impedance tomography system including a processor configured as such, and a surgical system comprising the same.

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

3. The surgical system according to claim 1, wherein each electrode of the electrode array has a length of about 3 mm and a width of about 1 mm.

4. The surgical system according to claim 1, wherein the electrodes of the electrode array are arranged in 4 columns and 15 rows.

5. The surgical system according to claim 1, wherein the electrodes of the electrode array are grouped into 4 separate sets of 10 electrodes.

6. The surgical system according to claim 1, wherein the processor is configured to filter the calculated electrical impedance by removing a noisy pattern before generating the electrical impedance tomography reconstruction.

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

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

9. The surgical system according to 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. A powered surgical instrument comprising an end effector including a first jaw and a second jaw, and an electrical impedance tomography system including a first electrode array including a plurality of electrodes operably coupled to the first jaw, ​ A second electrode array including a plurality of electrodes operably coupled to the second jaw portion, and a processor, controls the application of a current across the first electrode array and the second electrode array, measures a voltage difference across the first electrode array and the second electrode array, calculates an electrical impedance based on the measured voltage difference, generates an electrical impedance tomography reconstruction based on the calculated electrical impedance, a processor configured as such, an electrical impedance tomography system including, a powered surgical instrument comprising.

11. The powered surgical instrument according to claim 10, wherein the first electrode array includes 60 electrodes and the second electrode array includes 8 electrodes.

12. The powered surgical instrument according to claim 10, wherein each electrode of the first electrode array has a length of about 3 mm and a width of about 1 mm, and each electrode of the second electrode array has a length of about 3 mm and a width of about 3 mm.

13. The powered surgical instrument according to claim 10, wherein the electrodes of the first electrode array are arranged in 4 columns and 15 rows, and the electrodes of the second electrode array are arranged in 2 columns and 4 rows.

14. The powered surgical instrument according to claim 10, wherein at least a portion of the plurality of electrodes of the first electrode array are grouped into 4 separate sets of 10 electrodes, and each set of 10 electrodes is paired with 8 electrodes of the second electrode array.

15. The powered surgical instrument according to claim 10, wherein the processor is configured to filter the calculated electrical impedance by removing a noisy pattern before generating the electrical impedance tomography reconstruction.

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

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

18. The powered surgical instrument according to claim 10, wherein the processor is configured to control the 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 powered surgical instrument including a first jaw and a second jaw, an electrical impedance tomography system, a first electrode array including a plurality of electrodes operably coupled to the first jaw, a second electrode array including a plurality of electrodes operably coupled to the second jaw, and a processor configured to control application of a current across the first electrode array and the second electrode array, measure a voltage difference across the first electrode array and the second 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, the processor being so configured, an electrical impedance tomography system including the same, and a display operably coupled to the electrical impedance tomography system and configured to display the electrical impedance tomography reconstruction. A surgical system comprising the same.

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 from about 10 kHz to about 80 kHz.

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