Method for non-invasively determining physical data from a living organism using an EIT measuring device

Abstract

A method for the non-invasive determination of physical data from a living organism using an EIT measuring device for measuring a measure of blood flow through at least one organ within the organism is described, comprising the following method steps: a) Creating an EIT image series comprising a multitude of EIT images generated sequentially by means of the EIT measuring device attached to an extracorporeal area of ​​the organism, each consisting of image pixels, each of which is assigned a signal value corresponding to an electrical impedance, b) Selecting organ-specific EIT image sections from all EIT images that are identical in position, c) Determining a regional impedance curve based on all selected EIT image sections, d) Determining times at which the regional impedance curve has a local minimum, e) Selecting those EIT images from all generated EIT images that can each be assigned to one of the specific time points, f) Determine a reference image for each of the selected EIT images, g) Subtracting the reference image determined for each selected EIT image from it to obtain a difference image, or instead of the procedure steps e) to g), the following procedure steps e') to g'). e') Selecting those selected EIT image sections from all selected EIT image sections that can each be assigned to one of the specified time points, f') Determine a reference image for each of the selected EIT image sections, g') Subtracting the reference image determined for a selected EIT image section from it to obtain a difference image in each case, h) Selecting at least one difference image to obtain an EIT result image or averaging at least two difference images to obtain an EIT result image and i) Correlating the signal value assigned to each pixel of the result image with a measure of blood flow through at least one organ within the organism.

Description

Technical field

[0001] The invention relates to a method for non-invasively determining physical data from a living organism using an EIT measuring device for measuring a measure of blood flow through at least one organ within the organism.

[0002] Acute organ failure due to insufficient blood supply is a central problem in anesthesiology during and after prolonged surgical procedures involving large fluid shifts, as well as in major cardiac and vascular surgeries. Intensive care physicians, in particular, are confronted with regional and global circulatory disturbances in the context of systemic inflammatory responses, which can lead to multiple organ failure—the loss of all bodily functions and ultimately the patient's inevitable death. The kidneys are of particular concern, as they are especially sensitive to insufficient blood supply, which is why renal failure is often the first sign of general organ failure postoperatively and in intensive care. However, other organs, such as the liver or intestines, can also be damaged as a result of insufficient blood supply.Due to the kidneys' particular susceptibility to organ failure caused by insufficient supply, they will be primarily considered in the following discussion; however, the following considerations and descriptions are of course also applicable to other organs.

[0003] Ensuring a patient's hemodynamic stability is therefore a crucial task for the attending anesthesiologist during perioperative and postoperative care, as well as in the treatment of patients in the intensive care unit (ICU). Hemodynamic monitoring is typically limited to intermittent blood pressure measurements. While continuous arterial blood pressure and cardiac output are monitored more frequently in the ICU, the former is monitored only in specific cases and the latter only rarely in anesthesia due to the considerable additional measurement effort and associated invasiveness. However, even when patient management is guided by monitoring extended hemodynamic variables, adhering to various threshold values ​​has not yet improved the risk of postoperative organ failure (see Wanner PM, et al.)., Targeting Higher lntraoperative BIood Pressures Does Not Reduice Adverse Cardiovascular Events Following Noncardiac Surgery.; J Am Goll Cardiol. 2021 Nov 2;78(18); 1753-1764. doi: 10.1016 / j.jacc.2021.08.048. .

[0004] PMID: 34711333 and Messina A, et al., Perioperative liberal versus restrictive fluid strategies and postoperative outcomes: a systematic review and meta-analysis on randomised-controlled trials in major abdominal elective surgery; Crit Care. 2021 Jun 11;25(1):205. doi: 10.1186 / s13054-021-03629-y. PMID: 34116707; PMCID: PMC8194047. This may be related to the fact that the monitored hemodynamic variables primarily capture the functionality of the "generator" in the hemodynamic system, i.e., the heart, and less so the blood supply to the organs. However, with the exception of the brain, continuous information about local blood pressure or perfusion of organs at risk of undersupply is not clinically available using near-infrared spectroscopy, and the actual problem of early detection of organ undersupply remains unsolved. State of the art

[0005] Currently, there are no regularly or continuously applicable methods available for monitoring the blood supply to organs in the abdominal region. While ultrasound can visualize blood flow in larger vessels and Doppler ultrasound can measure blood flow velocity, these methods cannot be used continuously due to the personnel requirements, especially since, in the case of the kidneys, they require a specific lateral positioning of the patient, which is generally incompatible with perioperative, postoperative, or intensive care treatment.

[0006] Electrical impedance tomography, or EIT for short, has become a powerful tool for functional lung imaging. The strengths of EIT lie in its flexible application at the bedside or operating table and the combination of spatial information with a high temporal resolution of 50 frames per second and more.

[0007] The images are displayed according to the general convention of imaging, meaning they represent the image plane from a caudal perspective. Outside of research, EIT is currently used clinically primarily for lung imaging, and the intended use of available medical devices is limited to the thorax. For technical reasons, EIT imaging is generally designed as a relative measurement method; that is, EIT measurements always refer to an arbitrary reference point. Therefore, absolute imaging, which would allow for the visualization of organs due to their differing impedances in patients, is not feasible outside of experimental settings. By far the largest application of EIT relates to the analysis of functional lung ventilation; see also Lobo B., et al., Electrical impedance tomography, Ann TranslMed. 2018 Jan;6(2):26. doi: 10.21037 / atm.2017.12.06.PMID: 29430443; PMCID: PMC5799136 sowie Sella N, et al., Electrical impedance tomography: A compass for the safe route to optimal PEEP. Respir Med. 2021 Oct; 187: 106555. doi:10.1016 / j.rmed.2021.106555. Epub 2021 Jul 30. PMID: 34352563.

[0008] The representation of the global impedance curve is state of the art, but since it plays a role in understanding the following, it will be briefly described: The global impedance curve is created by calculating the mean or sum of the impedances of all pixels in each image of a series. This results in a time series of (arbitrary) impedance values, which, in the case of the lungs, depicts the temporal course of respiration / ventilation, since with increasing lung filling during inspiration, the electrical impedance in the ventilated areas of the lungs, and thus in the mean (or pixel sum), increases and decreases again with expiration. Several research groups are working on imaging hemodynamic processes in the lungs using EIT; see Fossali T, et al., Effects of Prone Position on Lung Recruitment and Ventilation-Perfusion Matching in Patients With COVI D-19 Acute Respiratory Distress Syndrome: A Combined CT Scan / Electrical Impedance Tomography Study. Crit Care Med. 2022 May 1 ;50(5):723-732. doi: 10.1097 / CCM.0000000000005450. Epub 2022 Apr 11. PMID: 35200194; PMCID: PMC9005091 and Xu M, He H, Long Y., Lung Perfusion Assessment by Bedside Electrical Impedance Tomography in Critically III Patients. Front Physiol. 2021 Oct 13;12:748724. doi:10.3389 / fphys.2021. 748724. PMID: 34721072; PMCID: PMC8548642. These aim to determine the ventilation-perfusion ratio of the lungs non-invasively, which is almost always based on the application of an electrical contrast agent, e.g. saline solution, into vessels leading to the lungs and the observation of the subsequent distribution in the lungs over time.

[0009] In a scientific case report, EIT is used to monitor renal bleeding; see You F., et al., Applying electrical impedance tomography to dynamically monitor retroperitoneal bleeding in a renal trauma patient. Intensive Care Med. 2013 Jun;39(6): 1159-60. doi: 10.1007 / s00134-013-2895-y. Epub 2013 Mar 29. PMID: 23539146; PMCID:PMC3653033. Furthermore, a conference paper reports on the assessment and early detection of chronic kidney disease using EIT; see Yap DYH, et al., Bio-conductivity characteristics of chronic kidney disease stages examined by portable frequencydifference electrical impedance tomography. Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:3378-3381. doi:10.1109 / EM8C48229.2022.9871377. PMID:36086019. Furthermore, the detection of ureteral reflux using EIT is described; see Dunne E, et al., Detection of Vesicoureteral Reflux Using Electrical Impedance Tomography. IEEE Trans Biomed Eng. 2019 Aug;66(8):2279-2286; doi: 10.1109 / T8ME.2018.2886830. Epub 2018 Dec 14. PMID: 30571612. The three aforementioned scientific articles contain evaluations in the sense of known analyses of impedance distributions in the image as such.

[0010] Publication WO 2023 / 143524 A1 describes a computer-implemented method for EIT image-based health assessment of the kidney, which is based on processing at least one kidney-related conductivity characteristic and at least one anthropometric characteristic of the subject using a machine learning-based processing model.

[0011] Publication WO 2022 / 199621 A1 discloses an algorithm for analyzing the health status of the liver from multifrequency EIT data, describing a segmentation of organs based on differences in impedance behavior at different frequencies.

[0012] Electrode belts are known for carrying out EIT, as described, for example, in the publications DE 103 15 868 B4 and DE103 39 084 B4.

[0013] Publications EP 2 228 009 B1, EP 2 762 061 B1 and EP 3 957 241 B1 disclose further electrical impedance tomography devices and methods for recording a sequence of EIT images of a cross-sectional plane of the thorax of a patient.

[0014] Patent application US 2024 / 0008759 A1 discloses a device and a method for recording and monitoring cardiopulmonary functions using electrical impedance tomography (EIT), which is applicable to virtually any area of ​​the body with blood flow. The EIT images acquired of a body region are coded pixel by pixel or pixel by pixel group by assigning brightness or color values. Subsequently, temporally occurring differences in brightness or color values ​​in all acquired and coded EIT images are analyzed and ultimately correlated with organ-specific blood flow patterns.

[0015] Patent application US 2023 / 0337921 A1 discloses a device and a method for calculating a hemodynamic parameter using electrical impedance tomography in the human chest area. The calculation of the hemodynamic parameter is based on time-synchronized pixel information that can be attributed to the heart and the lungs. Description of the invention

[0016] The invention is based on the objective of providing a novel approach for monitoring the organ supply with blood, which is intended to open up a new field for the recording and monitoring of organ-specific hemodynamics by means of electrical impedance tomography.

[0017] The solution to the problem underlying the invention is specified in claim 1. Advantageously developing features of the invention are the subject of the dependent claims and the further description.

[0018] The solution-oriented method for non-invasively determining physical data from a living organism, preferably a human being, using an EIT measuring device for measuring a measure of blood flow through at least one organ within the organism, is characterized by the following process steps: First, an EIT image series is generated using a known EIT measuring device, preferably positioned in the abdominal region of a person. This series comprises a multitude of sequentially generated EIT images, each composed of preferably array-arranged image pixels, each pixel assigned a signal value corresponding to a measured electrical impedance. Subsequently, organ-specific EIT image sections are selected from the multitude of generated EIT images, representing the same location. The image section within the multitude of individual EIT images that depicts the electrical impedance signal values ​​originating from the kidney is preferably of particular interest. Of course, other image sections from the EIT image series can also be freely selected, depending on which organ(s) are of interest.

[0019] In a further step, an impedance curve, the so-called regional impedance curve, is determined based on all selected EIT image sections. For this purpose, an average value is calculated for each selected EIT image section, which results from the mathematical mean of the electrical impedances measured by each individual pixel of the EIT image section. The electrical impedances of each individual pixel represent signal values ​​that are reflected in a visually perceptible representation of each EIT image section by the pixel brightness. Therefore, the average value assignable to each individual EIT image section corresponds to the average brightness value of that selected EIT image section. Instead of determining an average value for each selected EIT image section, the sum of all pixel values ​​contained in the selected EIT image section could also be used as the basis for further calculations.

[0020] All EIT images, as well as the EIT image sections selected from them, each consist of an array-like arrangement of individual image pixels. The number of image pixels per EIT image section is the same and depends both on the size of the positionally identical and organ-specific EIT image sections selected, and on the image resolution, i.e., the image pixel density or image pixel size.

[0021] Since the numerous selected, positionally identical EIT image sections were recorded in a temporal sequence using the EIT measuring device, the regional impedance curve reflects the temporal change of the image brightness mean values ​​assigned to the individual selected EIT image sections.

[0022] In a further step, the regional impedance curve is used to determine the time points at which it exhibits a local minimum. At precisely these selected time points, in a preferred first solution-oriented variant, the corresponding EIT images are chosen from all available EIT images.

[0023] For each selected EIT image, a reference image is determined. Preferably, two or more EIT images are chosen that were taken before or after a selected EIT image. These EIT images are then averaged pixel by pixel to determine the reference image. Alternatively, a single EIT image, taken before or after a selected EIT image, can serve as the reference image.

[0024] In the next step, the reference images are subtracted from the respective selected EIT images to obtain so-called difference images.

[0025] The resulting difference images can either be used individually for further analysis, e.g., for diagnostic purposes, or subjected to further averaging to obtain an EIT result image. During averaging, at least two, preferably all, difference images from a measurement period are averaged pixel by pixel to obtain a meaningful EIT result image.

[0026] The resulting image can be visualized using suitable display techniques. Each pixel of the resulting image is assigned a signal value, which corresponds to an electrical impedance. For visual representation and differentiation, the individual signal values ​​are encoded by different brightness levels and / or colors, which are correlated with a measure of blood flow through at least one organ within the organism.

[0027] As an alternative to selecting one EIT image at each of the identified time points where the regional impedance curve has a minimum, and subsequently processing the selected EIT images to obtain a final EIT image, the selected EIT image sections can be chosen that coincide with the time points where the regional impedance curve has a local minimum. The procedural steps of determining a reference image for each of the selected EIT image sections, subtracting the reference image obtained for each selected EIT image section from it to obtain a difference image, and selecting at least one difference image to obtain a final EIT image, or averaging at least two difference images to obtain a final EIT image, are performed similarly.

[0028] The correlation between EIT images acquired from a human using the EIT measuring device and a measure of blood flow through at least one organ, which is reflected in the EIT image, is based on the fact that the different transit times of a blood pulse wave from the heart to the respective organs, for example, the kidneys, are reflected in correspondingly time-shifted minima in the respective regional impedance curves. Thus, in the context of electrical impedance measurement, an area at the time of maximum blood volume is characterized by a low electrical impedance value. This allows the impedance changes in the individual organs, resulting from the time-shifted pulsatile activity, to be isolated or segmented using imaging techniques.

[0029] In a preferred embodiment of the solution, the EIT images acquired with the aid of the EIT measuring device, or the already positionally identical, organ-specific EIT image sections, are subjected to filtering in which low- and high-frequency signal components within the EIT images of the EIT image series are eliminated in order to obtain essentially only pulsatile cardiogenic signal components in the EIT images or EIT image sections. For the filtering, a lower cutoff frequency serves primarily to eliminate low-frequency signals originating from respiration, and an upper cutoff frequency serves to eliminate high-frequency interference signals. Butterworth bandpass filters or Kalman filters are preferably suitable for the filtering.

[0030] After determining the regional impedance curve based on all selected EIT image sections, preferably cleaned of low- and high-frequency interference, and selecting those EIT images or EIT image sections acquired at times when the regional impedance curve exhibits a local minimum (i.e., a negative signal peak), only those EIT images or EIT image sections depicting cardiogenic pulsations of the organ shown within the EIT image or EIT image section are selected. In the case of the kidneys, the selected EIT images or EIT image sections represent the state in which the kidneys are exposed to systolic blood pressure.

[0031] To eliminate further pulsatile activities that are not temporally synchronous with the main pulsation in the target area, such as the kidney, a reference image is generated for each selected EIT image or image section, and this reference image is then subtracted from the corresponding selected EIT image or image section. The resulting difference images represent the pulsatile activity of a given organ, such as the kidney. Other organs within the EIT image or image section that pulsate coincidentally can also be depicted accordingly.

[0032] Naturally, the proposed method can be adapted by selecting suitable alternative, organ-specific EIT image sections with identical positions to examine the pulsatile activity of various organs located in the image plane of the EIT measuring device. In this way, the blood supply to different organs can be assessed both qualitatively and quantitatively in isolation.

[0033] The solution-oriented procedure provides the basis for examining and monitoring the blood supply of various organs within the image plane of an EIT measuring device, so that monitoring procedures and alarm systems based on this can be used to indicate an impending undersupply of, for example, the kidneys intraoperatively, postoperatively or in the intensive care context at an early stage, thus offering a treating physician the possibility of early intervention.

[0034] In the following, a specific theoretical measurement example is explained, which is not able to restrict the general concept of the invention: Brief description of the invention

[0035] The invention is described below by way of example, without limiting the general concept of the invention, with reference to the drawings. The drawings show: Fig. 1a to i Flowchart for carrying out the procedure according to the solution for the non-invasive determination of physical data from a living organism using an EIT measuring device with alternative see Fig. 1f' to i'. Ways to implement the invention, industrial applicability

[0036] The Fig. Figure 1 shows a sequence image representation to illustrate the solution procedure.

[0037] Using an EIT measuring device 1, which is attached extracorporeally to the abdominal region of a human M, see Fig. 1a, an EIT measurement is performed with a measurement duration of 10 seconds, in which an EIT image series is created that includes n = 500 EIT images 2, see Fig. 1b, each showing a cross-sectional image of the abdomen with a resolution of 32 x 32 image pixels 3, see Fig. 1c.

[0038] In a specific image area of ​​each of the 500 EIT images 2, the kidneys 4 are depicted, for example, within a positionally identical image section 5 that comprises only 20 x 8 image pixels 3. In the following, for each of the selected EIT image sections 5, see Fig. 1d an average impedance value is determined, representing an image brightness value determined for each EIT image section 5. The signal values ​​of each individual image pixel 3, whose amplitudes correspond to a measured electrical impedance, are summed and divided by the number of image pixels of the EIT image sections 5. Based on the 500 EIT image sections 5 recorded in temporal sequence and the resulting averaged image brightness values, a regional impedance curve 6 is created, see Figure 1. Fig. 1e, from which the cardiogenic pulsatility of that organ, for example the kidneys, which are shown in isolation in the 500 image sections 5, can be extracted. Thus, the local minima of the regional impedance curve 6 represent the cardiogenic pulsatility of the dominantly pulsating organ located within the EIT image section 5, e.g., the kidneys 4. For example, let it be assumed that in the above example, from the 500 recorded EIT images 2 and the 500 selected EIT image sections 5* obtained from them, those EIT image sections 5* with image sequences No. 80, 120, and 160 are selected that correspond to the local minima of the regional impedance curve, see Fig. 1f. Subsequently, a reference image R5* is determined for each of the selected EIT image sections 5*. For example, for EIT image section 5* with image number 80, image sections 79 and 81 are selected, both of which are averaged pixel by pixel, and the resulting reference image R5* is subtracted pixel by pixel from image section 5 with sequence number n=80. Fig. 1g. In this way, for each of the selected EIT image sections 5 n=80, n=120 and n=160, a difference image D5* is obtained, on which the kidneys 4 are depicted, each at the time of a blood pulse wave passing through the kidneys 4, see Fig. 1h. All three difference images D5* are subsequently averaged pixel by pixel to obtain an EIT result image 6, which in the case of the example explained reflects the cardiogenic pulsatile activity at the site of the kidneys, see Fig. 1i.

[0039] As an alternative to the selection of EIT image sections 5* described above, specifically at times when the relative impedance curve 6 exhibits a minimum, it is also possible to perform the selection on the n=500 EIT images 2. It is assumed that the EIT images 2 are used for further evaluation in the temporal sequence n=80, n=120, and n=160, see [reference]. Fig. 1f'. For each of the selected EIT images 2*, a reference image R2* is determined, see Fig. 1g', for example, EIT images 79 and 81 are selected for EIT image 2* with image number 80. These images are both averaged pixel by pixel, and the resulting reference image R2* is subtracted pixel by pixel from the selected EIT image 2* with sequence number n=80. In this way, a difference image D2* is obtained for each of the selected EIT images 2* n=80, n=120, and n=160, see [reference]. Fig. 1h', on which all blood vessels, including the kidneys 4, are depicted, at the time of a blood pulse wave passing through the kidneys 4. All three difference images D2* are subsequently averaged pixel by pixel to obtain an EIT result image 7', see Fig. 1i', which in the case of the alternative example explained represents the cardiogenic pulsatile activity of all organs detectable in the EIT result image 7' at the time when the kidneys experience maximum blood flow.

[0040] Using the same dataset, i.e., based on the 500 EIT images explained above, the cardiogenic pulsatile activity of other organs can be investigated and visualized by appropriately selecting an alternative EIT image section. Reference symbol list 1 EIT measuring device 2 EIT images 2* selected EIT image 3 image pixels 4 kidneys, organ 5 EIT image section 5* selected image section R2*, R5* Reference image D2*, D5* Difference image 6 regional impedance curve 7.7' EIT result image M Mensch n temporal sequence of EIT images in a recorded EIT image series

Claims

Method for non-invasively determining physical data from a living organism using an EIT measuring device (1) for measuring a measure of blood flow through at least one organ (4) within the organism, comprising the following method steps: a) generating an EIT image series comprising a plurality of EIT images (2) generated sequentially by means of the EIT measuring device (1) attached to an extracorporeal area of ​​the organism, each image consisting of image pixels (3) whose image pixels (3) are each assigned a signal value corresponding to an electrical impedance, b) selecting organ-specific EIT image sections (5) from all EIT images (2) that are identical in position, c) determining a regional impedance curve (6) based on all selected EIT image sections (5), d) determining time points at which the regional impedance curve (6) has a local minimum,e) Selecting those EIT images (2*) from all generated EIT images (2) that can be assigned to one of the specified time points, f) Determining one reference image R2* for each of the selected EIT images (2*), g) Subtracting the reference image (R2*) determined for each selected EIT image (2*) from it to obtain one difference image (D2*), or instead of steps e) to g), the following steps e') to g'), e') Selecting those EIT image sections (5*) from all selected EIT image sections (5) that can be assigned to one of the specified time points, f') Determining one reference image (R5*) for each of the selected EIT image sections (5*), g') Subtracting the reference image (R5*) determined for each selected EIT image section (5*) from this to obtain one difference image each (D5*),h) Selecting at least one difference image (D2*,D5*) to obtain an EIT result image (7, 7*) or averaging at least two difference images (D2*, D5*) to obtain an EIT result image (7, 7*) and i) correlating the signal value assigned to each image pixel (3) of the result image (7, 7*) with a measure of the blood flow through the at least one organ within the organism. Method according to claim 1, characterized in that the generated EIT images (2) are filtered to eliminate low and high frequency signal components to obtain purified EIT images, and that the purified EIT images are subjected to the method steps b) to g) and h) and i). Method according to claim 1, characterized in that the selected EIT image sections (5) are filtered to eliminate low and high frequency signal components to obtain purified EIT image sections, and that the purified EIT image sections are subjected to the method steps c), d), e') to g') as well as h) and i). Method according to claim 2 or 3, characterized in that the filtering is carried out using Butterworth bandpass filters based on a lower and / or upper cutoff frequency or Kalman filtering. Method according to one of claims 1 to 4, characterized in that the selection of the respective positionally identical, organ-specific EIT image sections (5) from all EIT images (2) is carried out by means of static image pattern recognition and / or by means of detection of dynamically changing image content in a sequence of temporally successively generated EIT images (2). Method according to one of claims 1 to 5, characterized in that, to determine the regional impedance curve (6) for each selected EIT image section (5), an image brightness mean value is calculated, and that the image brightness mean values ​​of all EIT image sections (5) in their temporal sequence form the regional impedance curve (6). Method according to one of claims 1, 2, 4 to 6, characterized in that the determination of a reference image (R2*) attributable to a selected EIT image (2*) is carried out by selecting an EIT image (2) that is created before or after the selected EIT image (2), or that the determination of a reference image (R2*) attributable to a selected EIT image (2*) is carried out by averaging at least two EIT images (2) that are created before or after the selected EIT image (2*). Method according to one of claims 1, 3, 4 to 6, characterized in that the determination of a reference image (R5*) attributable to a selected EIT image section (5*) is carried out by selecting a selected EIT image section (5*) that was created before or after the selected EIT image section (5*), or that the determination of a reference image (R5*) attributable to a selected EIT image section (5*) is carried out by averaging at least two selected EIT image sections (5) that were created before or after the selected EIT image section (5*). Method according to claim 7 or 8, characterized in that the averaging of the at least two EIT images (2) or EIT image sections (5*) is carried out pixel by pixel. Method according to one of claims 1 to 9, characterized in that the subtraction of the reference image (R2*, R5*) from the respective assigned selected EIT image (2*) or the selected selected EIT image section (5*) is carried out pixel by pixel. Method according to one of claims 1 to 10, characterized in that the result image (7, 7') is brought to visual display, wherein each signal value which is assigned to an image pixel (3) is encoded by a visually perceptible brightness and / or color.

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