Method of controlling a ventilation device to assess lung recruitability, ventilation system and ventilation device

Abstract

A method, ventilation system, and ventilation device for assessing lung re-expansion using a controlled ventilation device are disclosed. The method includes: ventilating a subject under first ventilation parameters and acquiring first impedance data; generating a first lung image, wherein each pixel corresponds to one first impedance data; determining a first target region having a preset alveolar opening state based at least on the first impedance data, and obtaining a first evaluation parameter based on the first target region; ventilating the subject under second ventilation parameters for enabling lung re-expansion and acquiring second impedance data; generating a second lung image, wherein each pixel corresponds to one second impedance data; determining a second target region having a preset alveolar opening state based at least on the second impedance data, and obtaining a second evaluation parameter based on the second target region; and obtaining an assessment result of lung re-expansion based on the first and second evaluation parameters. This application achieves an effective assessment of lung re-expansion.

Description

Technical Field

[0001] This application relates to the field of medical devices, and more specifically to a method for controlling a ventilation device to assess lung re-expansion, a ventilation system, and a ventilation device. Background Technology

[0002] Respiratory pathology and physiology often lead to alveolar collapse in patients with acute respiratory distress syndrome (ARDS), resulting in severe hypoxemia. To improve oxygenation, more alveoli need to be involved in ventilation. For moderate to severe ARDS patients, alveolar recruitment is commonly used clinically. However, the effectiveness of lung recruitment varies significantly among patients; patients with good lung re-expansion can open collapsed alveoli and improve oxygenation with relatively low pressure and intervention time; while patients with poor lung re-expansion struggle to open collapsed alveoli even with high pressure and intervention time, failing to improve oxygenation and potentially causing barotrauma. Therefore, lung re-expansion capability needs to be assessed before initiating lung recruitment intervention.

[0003] Computed tomography (CT) can quantitatively calculate the area of ​​alveolar collapse and re-expansion, making it an effective method for clinically evaluating lung re-expansion. However, CT scans involve radiation, posing certain risks to patients. Furthermore, CT scanners are relatively large and generally used in radiology departments, making bedside real-time monitoring and assessment difficult. Therefore, CT-based methods for evaluating lung re-expansion cannot be widely applied in clinical practice.

[0004] Electrical Impedance Tomography (EIT) can also be used to evaluate lung re-expansion in patients. It presents local lung ventilation in a two-dimensional image based on the distribution of pulmonary impedance, thus reflecting pulmonary ventilation heterogeneity and compensating for the limitations of one-dimensional global lung monitoring in respiratory mechanics. Unlike CT, EIT is a non-invasive, radiation-free measurement technique with a small footprint, allowing for real-time bedside monitoring. Currently, when assessing lung re-expansion based on EIT, changes in Positive End-Expiratory Pressure (PEEP) or changes in end-expiratory impedance (EELZ) and its derived parameters before and after lung re-expansion are evaluated. These methods still rely on one-dimensional global evaluation, treating the entire lung region as a whole and monitoring the combined effect of all alveoli. Global EELZ changes cannot reflect the re-expansion effect of a specific lung region. For ARDS patients with significant ventilation heterogeneity, some areas may overinflate, increasing the EELZ, while collapsed areas may not re-expand, leading to misjudgment and wasting the local ventilation information provided by EIT. Summary of the Invention

[0005] The summary section introduces a series of simplified concepts, which will be further explained in detail in the detailed description section. This summary section is not intended to limit the key and essential technical features of the claimed technical solution, nor is it intended to determine the scope of protection of the claimed technical solution.

[0006] A first aspect of this application provides a method for controlling a ventilation device to assess lung re-expansion, the ventilation device including a processor and a display, the method comprising: controlling the processor to perform the following steps: ventilating a subject under first ventilation parameters, and acquiring first impedance data corresponding to the first ventilation parameters during ventilation; generating a first lung image of the subject, the first lung image including a plurality of pixels, each of the plurality of pixels in the first lung image corresponding to a first impedance data; determining, at least based on the first impedance data, a first target region in the lung of the subject having a preset alveolar open state, and obtaining a first evaluation parameter based on the first target region; and using a method to re-expand the lungs of the subject... Ventilation is performed on the subject under the second ventilation parameter, and second impedance data corresponding to the second ventilation parameter is acquired during the ventilation process; a second lung image of the subject is generated, the second lung image including the plurality of pixels, each of the plurality of pixels in the second lung image corresponding to a second impedance data; a second target region in the lung having the preset alveolar opening state is determined at least based on the second impedance data, and a second evaluation parameter is obtained based on the second target region; and an evaluation result of the lung re-expansion of the subject is obtained based on the first evaluation parameter and the second evaluation parameter; and the display is controlled to display the first lung image, the second lung image and the evaluation result of the lung re-expansion.

[0007] In some embodiments, the first impedance data includes first impedance data during the inhalation phase and first impedance data during the exhalation phase; the second impedance data includes second impedance data during the inhalation phase and second impedance data during the exhalation phase; the lung includes multiple sub-regions; determining a first target region in the lung having a preset alveolar opening state based on the first impedance data includes: obtaining changes in the first impedance data based on the first impedance data during the inhalation phase and the first impedance data during the exhalation phase; obtaining changes in the first impedance data based on the changes in the first impedance data corresponding to each sub-region in the lung, and obtaining changes in the first impedance data during the inhalation phase corresponding to each sub-region in the lung. The first target region in the lung with a preset alveolar opening state is determined by the second impedance data and / or the first impedance data during the expiratory phase; the second target region in the lung with the preset alveolar opening state is determined by the second impedance data, which includes: obtaining the change of the second impedance data based on the second impedance data during the inhalation phase and the second impedance data during the expiratory phase; and determining the second target region in the lung with the preset alveolar opening state based on the change of the second impedance data corresponding to each sub-region in the lung, and based on the second impedance data during the inhalation phase and / or the second impedance data during the expiratory phase corresponding to each sub-region in the lung.

[0008] In some embodiments, the preset alveolar opening state includes at least one of the following: shear state, collapse state, overinflation state, normal state, or alveolar opening state derived from shear state, collapse state, or overinflation state.

[0009] In some embodiments, determining a first target region in the lung having the preset alveolar opening state based on changes in the first impedance data corresponding to each sub-region in the lung, and based on the first impedance data during the inspiratory phase and / or the expiratory phase corresponding to each sub-region in the lung, includes: determining a first target region having the collapsed state based on changes in the first impedance data and the first impedance data during the expiratory phase; determining a first target region having the sheared state based on changes in the first impedance data and the first impedance data during the expiratory phase; determining a first target region having the over-inflated state based on changes in the first impedance data and the first impedance data during the inspiratory phase; and / or determining a first target region having the normal state based on changes in the first impedance data, the first impedance data during the inspiratory phase, and the first impedance data during the expiratory phase. The target region; determining a second target region in the lung having the preset alveolar open state based on the changes in the second electrical impedance data corresponding to each region in the lung, and based on the second electrical impedance data of the inspiratory phase and / or the expiratory phase corresponding to each sub-region in the lung, includes: determining a second target region having the collapsed state based on the changes in the second electrical impedance data and the second electrical impedance data of the expiratory phase; determining a second target region having the sheared state based on the changes in the second electrical impedance data and the second electrical impedance data of the expiratory phase; determining a second target region having the over-inflated state based on the changes in the second electrical impedance data and the second electrical impedance data of the inspiratory phase; and / or determining a second target region having the normal state based on the changes in the second electrical impedance data, the second electrical impedance data of the inspiratory phase, and the second electrical impedance data of the expiratory phase.

[0010] In some embodiments, the first evaluation parameter is obtained at least based on the area of ​​the first target region, and the second evaluation parameter is obtained at least based on the area of ​​the second target region; or, the first evaluation parameter is obtained at least based on the ratio of the area of ​​the first target region to the area of ​​the lung, and the second evaluation parameter is obtained at least based on the ratio of the area of ​​the second target region to the area of ​​the lung; or, the first evaluation parameter is obtained at least based on the number of pixels in the first target region, and the second evaluation parameter is obtained at least based on the number of pixels in the second target region; or, the first evaluation parameter is obtained at least based on the ratio of the number of pixels in the first target region to the total number of pixels in the lung, and the second evaluation parameter is obtained at least based on the ratio of the number of pixels in the second target region to the total number of pixels in the lung.

[0011] In some embodiments, obtaining the lung re-expansion assessment result based on the first assessment parameter and the second assessment parameter includes: comparing the first assessment parameter and the second assessment parameter to obtain the lung re-expansion assessment result; further, in some embodiments, calculating the difference or ratio between the first assessment parameter and the second assessment parameter, and obtaining the lung re-expansion assessment result based on the difference or ratio.

[0012] In some embodiments, the lung includes multiple sub-regions; the method further includes: acquiring first ventilation pressure data under the first ventilation parameter and second ventilation pressure data under the second ventilation parameter; determining a first target region in the lung with a preset alveolar opening state based on the first impedance data includes: determining a first alveolar opening time corresponding to each sub-region based on the change of the first impedance data corresponding to each sub-region in the lung over time; determining a first opening pressure data corresponding to each sub-region based on the first alveolar opening time corresponding to each sub-region and the first ventilation pressure data corresponding to the first alveolar opening time; and determining a first opening pressure data corresponding to each sub-region based on the change of the first impedance data corresponding to each sub-region over time. The first alveolar opening pressure data is used to determine a first target region in the lung with a preset alveolar opening state; the second target region in the lung with a preset alveolar opening state is determined based on the second electrical impedance data corresponding to each sub-region in the lung over time, including: determining the second alveolar opening time corresponding to each sub-region; determining the second alveolar opening pressure data corresponding to each sub-region based on the second alveolar opening time corresponding to each sub-region and the second ventilation pressure data corresponding to the second alveolar opening time; and determining the second target region in the lung with the preset alveolar opening state based on the second opening pressure data corresponding to each sub-region.

[0013] In some embodiments, determining the first alveolar opening time corresponding to each sub-region based on the change of the first electrical impedance data corresponding to each sub-region in the lung over time includes: determining the first alveolar opening time corresponding to each sub-region based on the time when the first electrical impedance data corresponding to each sub-region reaches a preset electrical impedance threshold during the inspiratory phase of the respiratory cycle, wherein the preset electrical impedance threshold is determined based on the peak value reached by the first electrical impedance data corresponding to each sub-region during the respiratory cycle; determining the second alveolar opening time corresponding to each sub-region based on the change of the second electrical impedance data corresponding to each sub-region in the lung over time includes: determining the second alveolar opening time corresponding to each sub-region based on the time when the second electrical impedance data corresponding to each sub-region reaches an electrical impedance threshold during the inspiratory phase of the respiratory cycle, wherein the electrical impedance threshold is determined based on the peak value reached by the second electrical impedance data corresponding to each sub-region during the respiratory cycle.

[0014] In some embodiments, the preset alveolar opening state includes an easily opening state and / or a difficult-to-open state; determining a first target region in the lung with a preset alveolar opening state based on the first opening pressure data corresponding to each sub-region includes: determining a sub-region with the opening pressure data greater than a first preset pressure threshold as a first target region with the difficult-to-open state; determining a sub-region with the opening pressure data less than or equal to the first preset pressure threshold as a first target region with the easily opening state; determining a second target region in the lung with a preset alveolar opening state based on the second opening pressure data corresponding to each sub-region includes: determining a sub-region with the opening pressure data greater than the first preset pressure threshold as a second target region with the difficult-to-open state; determining a sub-region with the opening pressure data less than or equal to the first preset pressure threshold as a second target region with the easily opening state; wherein, the first preset pressure threshold is not greater than the inspiratory pressure under the first ventilation parameter and the inspiratory pressure under the second ventilation parameter.

[0015] In some embodiments, the ventilation pressure data includes at least one of the following: airway pressure data, esophageal pressure data, transpulmonary pressure data, and intrapulmonary pressure data.

[0016] A second aspect of the present invention provides a method for controlling a ventilation device to assess lung re-expansion, the ventilation device including a processor and a display, the method including: controlling the processor to perform the following steps: ventilating a ventilated subject under a first ventilation parameter, and acquiring first electrical impedance data corresponding to the first ventilation parameter during the ventilation process; generating a first lung image of the ventilated subject, the first lung image including a plurality of pixels, each of the plurality of pixels in the first lung image corresponding to a first electrical impedance data;

[0017] The process involves: determining the first alveolar apprehension state of multiple sub-regions in the lungs of the ventilated subject based at least on the first impedance data, each sub-region consisting of one or more pixels having the same first alveolar apprehension state; ventilating the subject under second ventilation parameters for lung recruitment, and acquiring second impedance data corresponding to the second ventilation parameters during ventilation; generating a second lung image of the ventilated subject, the second lung image including the multiple pixels, each of the multiple pixels in the second lung image corresponding to one second impedance data; determining the second alveolar apprehension state of the multiple sub-regions based at least on the second impedance data, each sub-region consisting of one or more pixels having the same first alveolar apprehension state; obtaining the re-expansionability of each sub-region based on the first alveolar apprehension state and the second alveolar apprehension state of each sub-region; obtaining an evaluation result of the lung re-expansionability of the ventilated subject based on the re-expansionability of the multiple sub-regions; and controlling the display to show the first lung image, the second lung image, and the evaluation result of the lung re-expansionability.

[0018] In some embodiments, the first impedance data includes first impedance data during the inspiratory phase and first impedance data during the expiratory phase; the second impedance data includes second impedance data during the inspiratory phase and second impedance data during the expiratory phase; determining the first alveolar opening state of multiple sub-regions in the lungs of the ventilated subject based at least on the first impedance data includes: obtaining changes in the first impedance data based on the first impedance data during the inspiratory phase and the first impedance data during the expiratory phase; and determining the first alveolar opening state based on the changes in the first impedance data corresponding to each of the sub-regions, and based on the first impedance data during the inspiratory phase corresponding to each of the sub-regions. The first alveolar opening state corresponding to each of the sub-regions is determined based on the first impedance data during the expiratory phase and / or the first impedance data during the expiratory phase. The determination of the second alveolar opening state of multiple sub-regions in the lungs of the ventilated subject, based at least on the second impedance data, includes: obtaining changes in the second impedance data based on the second impedance data during the inspiratory phase and the second impedance data during the expiratory phase; determining the second alveolar opening state corresponding to each sub-region based on the changes in the second impedance data corresponding to each sub-region, and based on the second impedance data during the inspiratory phase and / or the second impedance data during the expiratory phase corresponding to each sub-region.

[0019] In some embodiments, the first alveolar opening state includes at least one of the following: a shear state, a collapsed state, a hyperinflated state, a normal state, or an alveolar opening state derived from a shear state, a collapsed state, or a hyperinflated state, wherein the collapsed state is determined based on changes in the first impedance data and first impedance data during the expiratory phase; the shear state is determined based on changes in the first impedance data and first impedance data during the expiratory phase; the hyperinflated state is determined based on changes in the first impedance data and first impedance data during the inspiratory phase; the first alveolar opening state corresponding to a sub-region that does not belong to the hyperinflated state, the shear state, or the collapsed state is the normal state. The normal state; the second alveolar opening state includes at least one of the following: shear state, collapsed state, hyperinflated state, normal state, or alveolar opening state derived from shear state, collapsed state, or hyperinflated state, wherein the collapsed state is determined based on the change of the second electrical impedance data and the second electrical impedance data during the expiratory phase; the shear state is determined based on the change of the second electrical impedance data and the second electrical impedance data during the expiratory phase; the hyperinflated state is determined based on the change of the second electrical impedance data and the second electrical impedance data during the inspiratory phase; the second alveolar opening state corresponding to the sub-region that does not belong to the hyperinflated state, the shear state, or the collapsed state is the normal state.

[0020] In some embodiments, comparing the first alveolar opening state and the second alveolar opening state of each sub-region to obtain the re-expansionability of each sub-region includes: if the first alveolar opening state is a collapsed state and the second alveolar opening state is a sheared state, then the sub-region is determined to be re-expansionable; and / or if the first alveolar opening state is a collapsed state and the second alveolar opening state is a normal state, then the sub-region is determined to be re-expansionable; and / or if the first alveolar opening state is a collapsed state and the second alveolar opening state is an overinflated state, then the sub-region is determined to be re-expansionable.

[0021] In some embodiments, the method further includes: acquiring first ventilation pressure data under the first ventilation parameter and second ventilation pressure data under the second ventilation parameter; determining the first alveolar opening state of a plurality of sub-regions in the lungs of the ventilated object based at least on the first impedance data includes: determining the first alveolar opening time corresponding to each sub-region based on the change of the first impedance data corresponding to each sub-region over time; determining the first alveolar opening pressure data corresponding to each sub-region based on the first alveolar opening time corresponding to each sub-region and the first ventilation pressure data corresponding to the first alveolar opening time; determining the first alveolar opening pressure state of each sub-region based on the first opening pressure data corresponding to each sub-region. A first alveolar opening state, which includes an easily opening state or a difficult-to-open state; the step of determining the second alveolar opening state of the plurality of sub-regions based at least on the second impedance data includes: determining the second alveolar opening time corresponding to each sub-region based on the change of the second impedance data corresponding to each sub-region over time; determining the second opening pressure data corresponding to each sub-region based on the second alveolar opening time corresponding to each sub-region and the second ventilation pressure data corresponding to the second alveolar opening time; determining the second alveolar opening state of each sub-region based on the second opening pressure data corresponding to each sub-region, wherein the second alveolar opening state includes an easily opening state or a difficult-to-open state.

[0022] In some embodiments, the recoverability of each sub-region is obtained based on the first alveolar opening state and the second alveolar opening state of each sub-region, including: comparing the first alveolar opening state and the second alveolar opening state of each sub-region to obtain the recoverability of each sub-region; in some embodiments, if the first alveolar opening state is a difficult-to-open state and the second alveolar opening state is a easy-to-open state, then the sub-region is determined to be recoverable.

[0023] In some embodiments, obtaining the assessment result of the lung re-expansion of the ventilated object based on the re-expansion of the plurality of sub-regions includes: comparing the proportion of re-expansionable sub-regions in the plurality of sub-regions with a predetermined threshold; if the proportion exceeds the predetermined threshold, then determining that the lung re-expansion of the ventilated object meets a preset requirement.

[0024] A third aspect of this invention provides a ventilation system comprising a ventilation device, an impedance device, and a processor. The ventilation device includes a breathing circuit and a sensor. The breathing circuit delivers gas to the ventilated subject for ventilation. The sensor acquires ventilation data reflecting the ventilation status during mechanical ventilation of the ventilated subject. The impedance device includes an impedance data acquisition unit and an impedance data processing unit. The impedance data acquisition unit acquires impedance signals, and the impedance data processing unit processes the impedance signals to obtain impedance data. The processor executes the method for assessing lung re-expansion as described above.

[0025] A fourth aspect of this invention provides a ventilation device, comprising: a breathing circuit for delivering gas to the ventilated subject for mechanical ventilation; a sensor for acquiring ventilation data reflecting the ventilation status during the provision of mechanical ventilation to the ventilated subject; a communication module for communicating with an impedance device for acquiring impedance data during the provision of ventilation to the ventilated subject; and a processor for executing the method for assessing lung re-expansion as described above.

[0026] The method, ventilation system, and ventilation device for assessing lung re-expansion using controlled ventilation equipment according to embodiments of this application can effectively utilize local ventilation information from EIT to assess lung re-expansion. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] In the attached diagram:

[0029] Figure 1 A schematic flowchart illustrating a method for assessing lung re-expansion using a controlled ventilation device according to an embodiment of this application;

[0030] Figure 2 A schematic diagram showing the distribution of alveolar opening states according to an embodiment of this application;

[0031] Figure 3 A view showing alveolar opening time according to an embodiment of this application;

[0032] Figure 4 A schematic flowchart illustrating a method for assessing lung re-expansionability using a controlled ventilation device according to another embodiment of this application;

[0033] Figure 5 A schematic block diagram of a ventilation system according to an embodiment of this application is shown;

[0034] Figure 6 A schematic block diagram of a ventilation device according to an embodiment of this application is shown. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of this application more apparent, exemplary embodiments according to this application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein. Based on the embodiments of this application described herein, all other embodiments obtained by those skilled in the art without inventive effort should fall within the protection scope of this application.

[0036] The following description provides numerous specific details to offer a more thorough understanding of this application. However, it will be apparent to those skilled in the art that this application can be practiced without one or more of these details. In other instances, certain technical features well-known in the art have not been described to avoid confusion with this application.

[0037] It should be understood that this application can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. Rather, providing these embodiments will make the disclosure thorough and complete, and will fully convey the scope of this application to those skilled in the art.

[0038] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. When used herein, the singular forms “a,” “an,” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising” and / or “including,” when used in this specification, identify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups. When used herein, the term “and / or” includes any and all combinations of the associated listed items.

[0039] To fully understand this application, a detailed structure will be presented in the following description to illustrate the technical solution proposed in this application. Optional embodiments of this application are described in detail below; however, in addition to these detailed descriptions, this application may have other implementation methods.

[0040] The following is a reference. Figure 1This application describes a method for assessing lung re-expansion using a controlled ventilation device according to embodiments of the present application. The method of this application can be used in a ventilation device integrated with an EIT module, or in a ventilation system where the ventilation device and the EIT device are controlled collaboratively by the same processor. The ventilation device can be a ventilator, an anesthesia machine, or the like. Figure 1 This is a schematic flowchart of a method 100 for assessing lung re-expansion using a ventilation device according to an embodiment of this application, wherein the ventilation device includes at least a processor and a display, and the method 100 specifically includes controlling the processor to perform the following steps:

[0041] In step S110, the object is ventilated under the first ventilation parameter, and the first impedance data corresponding to the first ventilation parameter is acquired during the ventilation process.

[0042] In step S120, a first lung image of the ventilated object is generated. The first lung image includes a plurality of pixels, and each of the plurality of pixels in the first lung image corresponds to a first electrical impedance data.

[0043] In step S130, at least based on the first impedance data, a first target region with a preset alveolar opening state is determined in the lungs of the ventilated object, and a first evaluation parameter is obtained based on the first target region.

[0044] In step S140, the ventilated object is ventilated under the second ventilation parameter used to enable the lungs of the ventilated object to re-expand, and the second electrical impedance data corresponding to the second ventilation parameter is acquired during the ventilation process;

[0045] In step S150, a second lung image of the ventilated object is generated, the second lung image including the plurality of pixels, each of the plurality of pixels in the second lung image corresponding to a second electrical impedance data;

[0046] In step S160, a second target region in the lung having the preset alveolar opening state is determined at least based on the second electrical impedance data, and a second evaluation parameter is obtained based on the second target region; and

[0047] In step S170, the lung recoverability assessment result of the ventilated object is obtained based on the first assessment parameter and the second assessment parameter;

[0048] In step S180, the display is controlled to show the first lung image, the second lung image, and the assessment results of the lung's re-expansion capability.

[0049] The method 100 for assessing lung re-expansion using a controlled ventilation device according to the embodiments of this application determines a target area in the lung with a preset alveolar opening state based on electrical impedance data, and obtains the assessment result of lung re-expansion based on the changes in the target area before and after lung re-expansion, thereby effectively utilizing the local ventilation information of EIT to assess lung re-expansion.

[0050] The method 100 for assessing lung re-expansion according to embodiments of the present invention can be implemented in a ventilation device. The ventilation device is used to deliver gas supplied by a gas source to a ventilated subject for ventilation. Exemplarily, the ventilation device is communicatively connected to an electrical impedance imaging device, used to control the electrical impedance imaging device to acquire electrical impedance data during ventilation, and to obtain the acquired electrical impedance data from the electrical impedance imaging device. Alternatively, the ventilation device integrates an electrical impedance imaging device, which can serve as a functional module of the ventilation device. The method 100 for assessing lung re-expansion according to embodiments of the present invention can also be implemented in an electrical impedance imaging device, or in a third-party device communicatively connected to both the ventilation device and the electrical impedance imaging device.

[0051] The ventilation device is used to ventilate a patient under a first ventilation parameter and a second ventilation parameter. The first ventilation parameter can be a conventional ventilation parameter, and the second ventilation parameter can be a ventilation parameter used to induce lung recruitment in the patient. For example, the first ventilation parameter may include a first ventilation pressure, and the second ventilation parameter may include a second ventilation pressure, where the second ventilation pressure is greater than the first ventilation pressure. A higher ventilation pressure can, to some extent, reopen collapsed alveoli, but if lung recruitment is poor, even increasing the ventilation pressure may not effectively reopen collapsed alveoli. In other embodiments, the first ventilation parameter may include a first tidal volume, and the second ventilation parameter may include a second tidal volume, where the second tidal volume is greater than the first tidal volume. The ventilation device may also attempt to induce lung recruitment in the patient using other methods; this embodiment of the invention does not limit the specific lung recruitment method.

[0052] Before and after changing the ventilation parameters, electrical impedance imaging (EIA) was performed on the lungs of the ventilated subject using an EIA device. Specifically, before changing the ventilation parameters, a first lung image of the ventilated subject was generated, comprising multiple pixels, each corresponding to a first electrical impedance data point. After changing the ventilation parameters, a second lung image of the ventilated subject was generated, comprising multiple pixels, each corresponding to a second electrical impedance data point.

[0053] For example, the electrical impedance tomography (EIT) device includes multiple electrodes. During EIT imaging, a pair of electrodes is first powered, causing them to release current. The remaining electrodes then detect voltage changes on the human body surface, thereby obtaining the surface potential difference. Subsequently, a second pair of electrodes releases current, and the remaining electrodes again detect voltage changes, repeating this process continuously to obtain the conductivity distribution of the tissue. Multiple cross-sectional images can be obtained in one current cycle. Combining all the cross-sectional images yields electrical impedance data reflecting changes in lung impedance. For example, after acquiring the electrical impedance data, preprocessing can be performed, such as signal filtering and image filtering for noise reduction. For example, the contact impedance between the electrodes and the patient can also be acquired during EIT data acquisition. It can be determined whether the contact impedance exceeds a preset contact impedance threshold. If it exceeds the threshold, it indicates poor contact between the electrodes and the patient's skin, and the acquired electrical impedance data is discarded.

[0054] In the electrical impedance data acquired by the electrical impedance imaging device, the first electrical impedance data is used to provide local ventilation information under a first ventilation parameter, and the second electrical impedance data is used to provide local ventilation information under a second ventilation parameter. Based on the first and second electrical impedance data, a first target region and a second target region with a preset alveolar opening state in the lungs are determined, respectively. The difference between the first target region and the second target region can be used to reflect the lung's recoverability.

[0055] In some embodiments, the lung includes multiple sub-regions, and the first impedance data includes first impedance data during the inspiratory phase and first impedance data during the expiratory phase, and the second impedance data includes second impedance data during the inspiratory phase and second impedance data during the expiratory phase. Determining a first target region in the lung with a predetermined alveolar open state based on the first impedance data specifically includes: obtaining changes in the first impedance data based on the first impedance data during the inspiratory and expiratory phases; and determining the first target region in the lung with a predetermined alveolar open state based on the changes in the first impedance data corresponding to each sub-region in the lung, and the first impedance data during the inspiratory phase and / or the expiratory phase.

[0056] Specifically, the inspiratory and expiratory phases can be determined based on the changing trends of the impedance data, thereby obtaining the impedance data for the inspiratory and expiratory phases. Alternatively, the end-inspiratory and end-expiratory times can be obtained from the ventilation device, and the impedance data for the inspiratory and expiratory phases can be determined from the impedance data based on these times.

[0057] For example, the inspiratory impedance data may include one of the following: end-inspiratory impedance data, average end-inspiratory impedance data over multiple respiratory cycles, maximum inspiratory impedance data, maximum average inspiratory impedance data over multiple respiratory cycles, average inspiratory impedance data, average inspiratory impedance data over multiple respiratory cycles, median inspiratory impedance data, and median of average inspiratory impedance data over multiple respiratory cycles. The expiratory impedance data may include one of the following: end-expiratory impedance data, average end-expiratory impedance data over multiple respiratory cycles, maximum expiratory impedance data, maximum average expiratory impedance data over multiple respiratory cycles, average expiratory impedance data, average expiratory impedance data over multiple respiratory cycles, median in expiratory impedance data, and median of average expiratory impedance data over multiple respiratory cycles. The change in the first impedance data may be the difference between the first impedance data of the inspiratory phase and the first impedance data of the expiratory phase.

[0058] After determining the changes in the first impedance data, a first target region in the lung with a preset alveolar opening state is determined based on the changes in the first impedance data corresponding to each sub-region in the lung, as well as the first impedance data during the inspiratory phase and / or the expiratory phase. Each sub-region in the lung may correspond to one pixel or multiple adjacent pixels in the first lung image.

[0059] In some embodiments, the preset alveolar opening state includes at least one of the following: shear state, collapsed state, overinflated state, normal state, or an alveolar opening state derived from the shear state, collapsed state, or overinflated state. Specifically, if the alveoli in a certain region are not opened during ventilation, the alveolar opening state of that region is the collapsed state; if the alveoli in a certain region are not opened during expiration but open during inspiration, the alveolar opening state of that region is the shear state; if the alveoli in a certain region are effectively opened during both inspiration and expiration and the tidal volume is large, the alveolar opening state of that region is the normal state.

[0060] The characteristics of a collapsed state are small single-cycle ventilation and small end-expiratory lung volume, which is reflected in electrical impedance data as a region with small single-cycle impedance changes and low end-expiratory impedance values. Therefore, the first target region with a collapsed state can be determined based on the changes in the first electrical impedance data and the first electrical impedance data during the expiratory phase. Specifically, it can be determined whether the change ΔR of the first electrical impedance data in each sub-region of the lung is less than a first change threshold, and whether the first electrical impedance data R2 during the expiratory phase of each sub-region is less than a first impedance threshold C1. Sub-regions where the change ΔR of the first electrical impedance data is less than the first change threshold and the first electrical impedance data R2 during the expiratory phase is less than the first impedance threshold C1 are classified as having a collapsed state. The set of all sub-regions with a collapsed state is the first target region with a collapsed state. The first change threshold can be a fixed value or a value determined by the changes in electrical impedance data. When the latter is used, the first change threshold can be the product of the maximum value (or average value, median, etc.) of the changes in electrical impedance data and a preset first coefficient K1, where the first coefficient K1 ranges from 0 to 1.

[0061] The shear state is characterized by a certain single-cycle ventilation and a small end-expiratory lung volume. This is reflected in electrical impedance data as a region with a single-cycle impedance change greater than a certain value and a relatively small end-expiratory impedance value. Therefore, the first target region exhibiting the shear state can be determined based on the changes in the first electrical impedance data and the first electrical impedance data during the expiratory phase. Specifically, it is determined whether the change ΔR in the first electrical impedance data of each sub-region in the lung is greater than a second change threshold, and whether the first electrical impedance data R2 during the expiratory phase of each region is less than the second impedance threshold C2. Sub-regions where the change ΔR in the first electrical impedance data is greater than the second change threshold and the first electrical impedance data R2 during the expiratory phase is less than the second impedance threshold C2 are classified as shear regions. The set of all sub-regions exhibiting the shear state constitutes the first target region exhibiting the shear state. The second change threshold can be a fixed value or a value determined by the change in the first electrical impedance data. When the latter is used, the second change threshold can be the product of the maximum value (or average, median, etc.) of the change in electrical impedance data and a preset second coefficient K2. The first coefficient K2 ranges from 0 to 1.

[0062] Furthermore, a first target region exhibiting a normal state can be determined based on changes in the first impedance data, the first impedance data during inspiration, and the first impedance data during expiration. For example, a first target region exhibiting an overinflated state can be identified in the lungs, and regions not belonging to the collapsed, sheared, or overinflated states can be identified as first target regions exhibiting a normal state. An overinflated state is characterized by a small single-cycle ventilation and a large end-inspiratory lung volume, which is reflected in the impedance data as a region with a small single-cycle impedance change and a high end-inspiratory impedance value. Therefore, regions exhibiting an overinflated state can be determined based on changes in the first impedance data and the first impedance data during inspiration. Specifically, it is determined whether the change ΔR of the first electrical impedance data in each region of the lung is less than a preset third change threshold, and whether the first electrical impedance data R1 during the inspiratory phase in each region is greater than a preset third impedance threshold C3. Regions where the change ΔR of the first electrical impedance data is less than the preset third change threshold and the first electrical impedance data R1 during the inspiratory phase is greater than the preset third impedance threshold C3 are classified as having an over-inflated state. The set of all sub-regions with an over-inflated state is the first target region with an over-inflated state. The third change threshold can be a preset fixed value or a value determined by the change of the first electrical impedance data. When the latter is used, the third change threshold can be the product of the maximum value (or average value, median, etc.) of the change in electrical impedance data and a preset third coefficient K3. The value of the second coefficient K3 ranges from 0 to 1.

[0063] The method for determining the second target region is similar to that for determining the first target region. Specifically, it involves obtaining changes in the second impedance data based on the second impedance data during inhalation and exhalation. Then, based on the changes in the second impedance data corresponding to each region in the lungs, as well as the second impedance data during inhalation and / or exhalation, a second target region in the lungs with a predetermined alveolar opening state is determined. Specifically, a second target region with a collapsed state is determined based on the changes in the second impedance data and the second impedance data during exhalation; a second target region with a sheared state is determined based on the changes in the second impedance data and the second impedance data during exhalation; a region with an over-expanded state is determined based on the changes in the second impedance data and the second impedance data during inhalation; and a second target region with a normal state is determined based on the changes in the second impedance data, the second impedance data during inhalation, and the second impedance data during exhalation. For details, please refer to the above description, which will not be repeated here.

[0064] In some embodiments, a lung image may also be displayed, differentially showing one or more regions of normal, sheared, collapsed, and overinflated states. (See also...) Figure 2 , Figure 2 The lung image shows areas 210 in an overinflated state, 220 in a sheared state, and 230 in a collapsed state, with the remaining areas representing normal conditions. Different areas can be displayed with different colors; for example, yellow represents overinflated areas, blue represents sheared areas, gray represents collapsed areas, and black represents normal areas. This clearly and intuitively presents the ventilation status of different lung regions, as well as the distribution and size of the corresponding areas for each ventilation status.

[0065] After identifying a first target region in the lungs with a predetermined alveolar opening state, a first evaluation parameter can be obtained based on this first target region. Similarly, a second evaluation parameter can be obtained based on a second target region in the lungs with the same predetermined alveolar opening state. The first and second evaluation parameters are used to reflect specific properties of the regions corresponding to the predetermined alveolar opening states, such as their extent, so that the comparison between the first and second evaluation parameters can reflect lung re-expansion. For example, if, after changing from the first ventilation parameter to the second ventilation parameter, the region corresponding to the collapsed state significantly decreases, the region corresponding to the normal state significantly increases, or the region corresponding to the sheared state significantly increases, it indicates good lung re-expansion; conversely, it indicates poor lung re-expansion. Therefore, the difference or ratio between the first and second evaluation parameters can be calculated, and the evaluation result of lung re-expansion can be obtained based on the difference or ratio between the two. The assessment results of lung re-expansion can be qualitative, such as re-expansion or non-re-expansion, good re-expansion or poor re-expansion; or, the assessment results of lung re-expansion can be quantitative, such as the difference or ratio between the first assessment parameter and the second assessment parameter, or the result obtained by further calculation based on the difference or ratio.

[0066] For example, when the preset alveolar open state is a collapsed state, if the first assessment parameter is greater than the second assessment parameter, and the difference between the first and second assessment parameters is greater than a first threshold, then the assessment result of lung re-expansion is determined to meet the preset requirements, i.e., lung re-expansion is good. Conversely, if the difference between the first and second assessment parameters is less than or equal to the first threshold, then the assessment result of lung re-expansion is determined to not meet the preset requirements, i.e., lung re-expansion is poor. When the preset alveolar open state is a normal state or a sheared state, if the first assessment parameter is less than the second assessment parameter, and the difference between the first and second assessment parameters is greater than a second threshold, then the assessment result of lung re-expansion is determined to meet the preset requirements, i.e., lung re-expansion is good. Conversely, if the difference is greater than or equal to the first threshold, then lung re-expansion is determined to be poor.

[0067] The first evaluation parameter may include the area of ​​a first target region, and the second evaluation parameter may include the area of ​​a second target region. The difference between the first and second evaluation parameters represents the change in the area of ​​the region with a preset alveolar open state before and after lung recruitment. Alternatively, the first evaluation parameter may be the ratio of the area of ​​the first target region to the area of ​​the lung, and the second evaluation parameter may be the ratio of the area of ​​the second target region to the area of ​​the lung. Alternatively, the first evaluation parameter may be the number of pixels in the first target region, and the second evaluation parameter may be the number of pixels in the second target region. Alternatively, the first evaluation parameter may be the ratio of the number of pixels in the first target region to the total number of pixels in the lung, and the second evaluation parameter may be the ratio of the number of pixels in the second target region to the total number of pixels in the lung. In some embodiments, at least one of the target region's area, area ratio, number of pixels, and pixel ratio may be weighted or otherwise derived to obtain a comprehensive first and second evaluation parameter, thereby further improving the accuracy of the evaluation.

[0068] According to another aspect of the present invention, first ventilatory pressure data under a first ventilation parameter and second ventilatory pressure data under a second ventilation parameter can be acquired. Alveolar opening time corresponding to each sub-region in the lung can be determined based on impedance data. Opening pressure data can be determined based on the ventilation pressure data corresponding to the alveolar opening time. Target regions with a preset alveolar opening state can be determined based on the opening pressure data. During inhalation, gas enters the alveoli, and impedance gradually increases; during exhalation, gas is expelled from the alveoli, and impedance gradually decreases. That is, the magnitude of impedance is positively correlated with the amount of gas in the alveoli. Therefore, the time during which the alveoli have opened and effective ventilation has been achieved can be determined based on the impedance data, i.e., the alveolar opening time. The ventilation pressure data corresponding to the alveolar opening time can be called opening pressure data, which reflects the ease or difficulty of alveolar opening. The larger the opening pressure data, the slower the alveolar opening.

[0069] Specifically, determining a first target region in the lungs with a preset alveolar opening state based on first impedance data includes: determining the first alveolar opening time for each sub-region based on the change of first impedance data corresponding to each sub-region in the lungs over time; determining the first alveolar opening pressure data for each sub-region based on the first alveolar opening time and the first ventilation pressure data corresponding to the first alveolar opening time; and determining the first target region in the lungs with a preset alveolar opening state based on the first opening pressure data for each sub-region. Similarly, the second alveolar opening time for each sub-region can be determined based on the change of second impedance data corresponding to each sub-region in the lungs over time; the second alveolar opening time for each sub-region can be determined based on the second alveolar opening time and the second ventilation pressure data corresponding to the second alveolar opening time; and the second target region in the lungs with a preset alveolar opening state can be determined based on the second opening pressure data for each sub-region.

[0070] The ventilation pressure data includes at least one of the following: airway pressure data, esophageal pressure data, transpulmonary pressure data, and intrapulmonary pressure data. Intrapulmonary pressure (Plung) can be calculated from airway pressure (Paw) using respiratory mechanics equations, and the corresponding relationship between the two is as follows:

[0071]

[0072] In Formula 1, P lung (t) represents real-time intrapulmonary pressure, Peep is positive end-expiratory pressure, V(t) is volume signal, and P aw (t) represents real-time airway pressure, τ represents the patient's time constant, R is the patient's airway resistance, and T insp T total These represent inhalation time and total breathing time, respectively.

[0073] In some embodiments, determining the first alveolar opening time for each sub-region based on the change of first electrical impedance data corresponding to each sub-region in the lung over time includes: determining the first alveolar opening time for each sub-region based on the time it takes for the first electrical impedance data corresponding to each sub-region to reach a preset electrical impedance threshold during the inspiratory phase of the respiratory cycle. Similarly, the second alveolar opening time for each sub-region can be determined based on the time it takes for the second electrical impedance data corresponding to each sub-region to reach a preset electrical impedance threshold during the inspiratory phase of the respiratory cycle.

[0074] Reference Figure 3Each sub-region in the lung can refer to each pixel in the lung image, or multiple adjacent pixels can be considered as a sub-region. Local impedance maps can be generated based on the changes in impedance data of the same sub-region over time, while the curve of the impedance data of the entire lung over time can be called a global impedance map. Figure 3 The graph shows the variation curves of ventilation pressure data from top to bottom, along with the local electrical impedance plots of pixels A, B, and C. When the electrical impedance data of a certain sub-region reaches a preset electrical impedance threshold and continues to rise, it indicates that the alveoli in that sub-region have been opened, and the alveolar opening time of pixels A, B, and C is sequentially delayed.

[0075] The preset impedance threshold can be a relative threshold determined based on the peak value of the first or second impedance data corresponding to each region during a respiratory cycle. For example, the preset impedance threshold can be 40% of the maximum impedance within a respiratory cycle. In this embodiment, the expression for the opening pressure corresponding to pixel N is:

[0076] Popen pixelN =P,ΔZ=40%MaxΔZ (Formula 2)

[0077] In Formula 2, MaxΔZ is the maximum value of the impedance data of pixel N during the inspiratory phase, and P is the intrapulmonary pressure corresponding to the moment when the impedance data of pixel N reaches 40% of the maximum value.

[0078] Therefore, a local impedance map can be generated based on the curve of impedance data changing over time for each pixel in the lung image, thus each pixel represents a lung sub-region with a corresponding opening pressure. Marking the opening pressures corresponding to all sub-regions on the same image generates an opening pressure view, which is used to evaluate the ease of opening of different lung sub-regions and to present the temporal / spatial heterogeneity of lung ventilation. Based on the opening pressure view, the target region corresponding to a preset alveolar opening state can be determined.

[0079] In some embodiments, the preset alveolar opening state includes an easily opening state and / or a difficult-to-open state. That is, the first target region and the second target region can be regions with an easily opening state, and the first target region and the second target region can also be regions with a difficult-to-open state. For example, since a larger opening pressure indicates a later alveolar opening time and greater difficulty in opening, regions with opening pressure data less than or equal to a first preset pressure threshold can be defined as first target regions with an easily opening state, and regions with opening pressure data greater than the first preset pressure threshold can be defined as first target regions with a difficult-to-open state. Similarly, regions with opening pressure data greater than the first preset pressure threshold can be defined as second target regions with a difficult-to-open state; regions with opening pressure data less than or equal to the first preset pressure threshold can be defined as second target regions with an easily opening state. Wherein, if the opening pressure is greater than the inspiratory pressure, it indicates that the alveoli are continuously collapsing during ventilation; therefore, the first preset pressure threshold is not greater than the inspiratory pressure under the first ventilation parameter and the inspiratory pressure under the second ventilation parameter.

[0080] Based on the first target region, a first assessment parameter corresponding to a first ventilation parameter can be determined, and based on the second target region, a second assessment parameter corresponding to a second ventilation parameter can be determined. By comparing the first assessment parameter and the second parameter, an assessment result of lung recapitulation can be obtained. For example, the difference or ratio between the first assessment parameter and the second assessment parameter can be calculated, and the assessment result of lung recapitulation can be obtained based on the difference or ratio. The obtained assessment result of lung recapitulation can be a qualitative assessment result or a quantitative assessment result.

[0081] In some embodiments, the first evaluation parameter may include the area of ​​a first target region, and the second evaluation parameter may include the area of ​​a second target region. That is, the lung recoverability assessment result can be obtained based on the change in the size of the target region before and after changing the ventilation parameters. Alternatively, the first evaluation parameter may include the ratio of the area of ​​the first target region to the area of ​​the lung, and the second evaluation parameter may include the ratio of the area of ​​the second target region to the area of ​​the lung. That is, the lung recoverability assessment result can be obtained based on the change in the proportion of the target region in the lung before and after changing the ventilation parameters.

[0082] Alternatively, the first evaluation parameter may include the number of pixels in the first target region, and the second evaluation parameter may include the number of pixels in the second target region. This means that the lung recoverability can be assessed based on the change in the number of pixels in the target region before and after changing the ventilation parameters. Alternatively, the first evaluation parameter may include the ratio of the number of pixels in the first target region to the total number of pixels in the lungs, and the second evaluation parameter may include the ratio of the number of pixels in the second target region to the total number of pixels in the lungs. This means that the lung recoverability can be assessed based on the proportion of pixels in the target region within the total number of pixels in the lungs before and after changing the ventilation parameters.

[0083] In some embodiments, when the preset alveolar opening state is an easily opening state, if the target area exhibiting an easily opening state significantly increases after changing ventilation parameters, it indicates good lung re-expansion. Specifically, when the preset alveolar opening state is an easily opening state, if the second evaluation parameter is greater than the first evaluation parameter, and the difference between the second evaluation parameter and the first evaluation parameter is greater than a third threshold, then the assessment result of lung re-expansion is determined to meet the preset requirements. The third threshold is related to the types of the first and second evaluation parameters.

[0084] For example, when the first evaluation parameter is the area of ​​the first target region and the second evaluation parameter is the area of ​​the second target region, if the area of ​​the easily openable second target region is larger than the area of ​​the easily openable first target region, and the area difference between the two is greater than a third threshold, it indicates that the lung's re-expansion capability is good. Conversely, if the area of ​​the easily openable second target region is smaller than the area of ​​the easily openable first target region, or if the area of ​​the easily openable second target region is larger than the area of ​​the easily openable first target region, but the area difference is less than or equal to the third threshold, it indicates that the lung's re-expansion capability is poor.

[0085] Conversely, when the preset alveolar opening state is a difficult-to-open state, if the target area exhibiting a difficult-to-open state significantly decreases in size after changing ventilation parameters, it indicates good lung re-expansion. Therefore, when the preset alveolar opening state is a difficult-to-open state, if the second assessment parameter is less than the first assessment parameter, and the difference between the second assessment parameter and the first assessment parameter is greater than the fourth threshold, then the assessment result of lung re-expansion is determined to meet the preset requirements.

[0086] Continuing with the example of using the area of ​​the first target region as the first evaluation parameter and the area of ​​the second target region as the second evaluation parameter, if the area of ​​the second target region in the difficult-to-open state is smaller than the area of ​​the first target region in the difficult-to-open state, and the area difference between the two is greater than the fourth threshold, it indicates that the lung's re-expansion capability is good. Conversely, if the area of ​​the second target region in the difficult-to-open state is larger than the area of ​​the first target region in the difficult-to-open state, or although the area of ​​the second target region in the difficult-to-open state is smaller than the area of ​​the first target region in the difficult-to-open state, but the area difference is less than or equal to the fourth threshold, it indicates that the lung's re-expansion capability is poor.

[0087] Based on the above description, the method 100 for assessing lung re-expansion of the controlled ventilation device in this application embodiment determines the target area in the lung with a preset alveolar open state based on electrical impedance data, and obtains the assessment result of lung re-expansion based on the change of the target area before and after lung re-expansion, thereby effectively utilizing the local ventilation information of EIT to assess lung re-expansion.

[0088] The following is a reference. Figure 4 This application describes a method for assessing lung re-expansion using a controlled ventilation device according to another embodiment of the present application. Figure 4 This is a schematic flowchart of a method 400 for assessing lung re-expansion using a ventilation device according to an embodiment of this application. The ventilation device includes a processor and a display. The method specifically includes controlling the processor to perform the following steps:

[0089] In step S410, the object is ventilated under the first ventilation parameter, and the first impedance data corresponding to the first ventilation parameter is acquired during the ventilation process.

[0090] In step S420, a first lung image of the ventilated object is generated. The first lung image includes a plurality of pixels, and each of the plurality of pixels in the first lung image corresponds to a first electrical impedance data.

[0091] In step S430, the first alveolar opening state of a plurality of sub-regions in the lungs of the ventilated subject is determined at least based on the first impedance data;

[0092] In step S440, the ventilated object is ventilated under the second ventilation parameter used to enable the lungs of the ventilated object to re-expand, and the second electrical impedance data corresponding to the second ventilation parameter is acquired during the ventilation process;

[0093] In step S450, a second lung image of the ventilated object is generated, the second lung image including the plurality of pixels, each of the plurality of pixels in the second lung image corresponding to a second electrical impedance data;

[0094] In step S460, the second alveolar opening state of the plurality of sub-regions is determined at least based on the second electrical impedance data;

[0095] In step S470, the first alveolar opening state and the second alveolar opening state of each sub-region are compared to obtain the re-expansion capability of each sub-region; and

[0096] In step S480, the lung recapacity assessment result of the ventilated object is obtained based on the recapacity of the plurality of sub-regions;

[0097] In step S490, the display is controlled to show the first lung image, the second lung image, and the evaluation results of the lung re-expansion.

[0098] The main difference between this method and the method 100 for assessing lung re-expansion using controlled ventilation equipment is that the method 400 for assessing lung re-expansion in this embodiment calculates the alveolar opening state of multiple sub-regions before and after lung re-expansion. It determines the re-expansion of each sub-region based on the changes in alveolar opening state before and after lung re-expansion, and obtains the assessment result of the ventilated subject's lung re-expansion based on the re-expansion of multiple sub-regions. If the number of sub-regions with good re-expansion increases after lung re-expansion, it indicates that the overall lung re-expansion of the ventilated subject is good. Conversely, if the number of sub-regions with poor re-expansion increases after lung re-expansion, it indicates that the overall lung re-expansion of the ventilated subject is poor.

[0099] Each sub-region of the lung can correspond to a single pixel or multiple adjacent pixels in a lung image. In this embodiment, each sub-region has the same and unique alveolar opening state under each ventilation parameter. The method for determining the alveolar opening state of each sub-region is generally similar to the method for determining the alveolar opening state of different sub-regions of the lung in the method 100 for assessing lung re-expansion. Exemplarily, the method for determining the alveolar opening state includes, but is not limited to, the following two: one is to determine the alveolar opening state based on changes in electrical impedance data and electrical impedance data during the inspiratory and / or expiratory phases; the other is to determine the alveolar opening state based on the opening pressure.

[0100] When using the first method, the changes in the first impedance data are obtained based on the first impedance data during the inspiratory and expiratory phases. The first alveolar opening state for each sub-region is determined based on the changes in the first impedance data corresponding to each sub-region, as well as the first impedance data during the inspiratory and / or expiratory phases for each sub-region. Similarly, the changes in the second impedance data are obtained based on the second impedance data during the inspiratory and expiratory phases for each sub-region. The second alveolar opening state for each sub-region is determined based on the changes in the second impedance data corresponding to each sub-region, as well as the second impedance data during the inspiratory and / or expiratory phases for each sub-region.

[0101] The first alveolar opening state includes at least one of the following: shear state, collapsed state, overinflated state, normal state, or alveolar opening state derived from shear state, collapsed state, or overinflated state. If the alveoli in a subregion of the lung are not opened during ventilation, the alveolar opening state of that subregion is the collapsed state; if the alveoli in a subregion of the lung are not opened during expiration but open during inspiration, the alveolar opening state of that subregion is the shear state; if the alveoli in a subregion are effectively opened during both inspiration and expiration and the tidal volume is large, the alveolar opening state of that subregion is the normal state.

[0102] Therefore, the collapsed state is determined based on changes in the first impedance data and the first impedance data during the expiratory phase; the shear state is determined based on changes in the first impedance data and the first impedance data during the expiratory phase; the overinflated state is determined based on changes in the first impedance data and the first impedance data during the inspiratory phase; and the normal state is determined based on changes in the first impedance data, the first impedance data during the inspiratory phase, and the impedance data during the expiratory phase. Similarly, the second alveolar opening state includes the shear state, collapsed state, normal state, or overinflated state, wherein the collapsed state is determined based on changes in the second impedance data and the second impedance data during the expiratory phase; the shear state is determined based on changes in the second impedance data and the second impedance data during the expiratory phase; the overinflated state is determined based on changes in the second impedance data and the second impedance data during the inspiratory phase; and the second alveolar opening state corresponding to areas that do not belong to the overinflated state, shear state, or collapsed state is the normal state.

[0103] After determining the first and second alveolar opening states for each subregion, these states are compared to determine the re-expansion capability of each subregion. For example, if the first alveolar opening state is collapsed and the second alveolar opening state is sheared, normal, or overinflated, it indicates that lung re-expansion allows the alveoli in that subregion to open, thus confirming its re-expansion capability. If the first alveolar opening state is collapsed and the second alveolar opening state is normal, the subregion is confirmed to be re-expansionable. Similarly, if the first alveolar opening state is collapsed and the second alveolar opening state is overinflated, the subregion is confirmed to be re-expansionable.

[0104] When using a method to determine alveolar apnea based on opening pressure, it is also necessary to obtain first ventilatory pressure data under the first ventilation parameter and second ventilatory pressure data under the second ventilation parameter. Specifically, the first alveolar apnea status of multiple sub-regions is determined at least based on first impedance data, including: determining the first alveolar apnea time for each sub-region based on the change of first impedance data over time; determining the first opening pressure data for each sub-region based on the first alveolar apnea time and the first ventilatory pressure data corresponding to the first alveolar apnea time; and determining the first alveolar apnea status of each sub-region based on the first opening pressure data, wherein the first alveolar apnea status includes an easily apnea status or an uneasy apnea status. Determining the alveolar apnea status of multiple sub-regions based on at least the second electrical impedance data includes: determining the alveolar apnea time for each sub-region based on the change in the second electrical impedance data over time; determining the second alveolar apnea pressure for each sub-region based on the alveolar apnea time and the corresponding second ventilation pressure data; and determining the alveolar apnea status for each sub-region based on the second ventilation pressure data, whereby the alveolar apnea status includes an easily apnea state or an uneasy apnea state. Using this method, it is possible to determine whether the alveoli in each sub-region are easily apnea before and after lung recruitment.

[0105] After determining the alveolar opening state of each subregion before and after lung recruitment, the first alveolar opening state and the second alveolar opening state of each subregion are compared to obtain the recruitability of each subregion. Specifically, if the first alveolar opening state of a subregion is difficult to open, and the second alveolar opening state is easy to open, then the subregion is determined to be recruitable.

[0106] After determining the re-expansion of each sub-region using any of the methods described above, the assessment result of the lung re-expansion of the ventilated subject is obtained based on the re-expansion of multiple sub-regions. For example, the proportion of re-expansionable sub-regions among the multiple sub-regions can be compared with a predetermined threshold. If the proportion of re-expansionable sub-regions exceeds the predetermined threshold, it is determined that the lung re-expansion of the ventilated subject meets the preset requirements, i.e., the lung re-expansion of the ventilated subject is good. In some embodiments, the proportion of non-re-expansionable sub-regions can also be compared with a predetermined threshold. If the proportion of non-re-expansionable sub-regions exceeds the predetermined threshold, it is determined that the lung re-expansion of the ventilated subject does not meet the preset requirements, i.e., the lung re-expansion of the ventilated subject is poor. In some embodiments, the assessment result of the lung re-expansion of the ventilated subject can also be a quantitative assessment result; for example, the proportion of re-expansionable sub-regions can be used as the assessment result of lung re-expansion.

[0107] Based on the above description, the method 400 for assessing lung re-expansion in this application embodiment determines the alveolar opening state of multiple sub-regions in the lung before and after lung re-expansion based on electrical impedance data, obtains the re-expansion of multiple sub-regions, and obtains the assessment result of lung re-expansion based on the re-expansion of multiple sub-regions, thereby effectively utilizing the local ventilation information of EIT to assess the lung re-expansion of the target object.

[0108] Another embodiment of this application provides a ventilation system, see [link to previous document]. Figure 5 The ventilation system 500 includes a ventilation device 510, an electrical impedance imaging device 520, and a processor 530. The ventilation device 510 includes at least a breathing circuit and a sensor. The breathing circuit is used to deliver gas to the ventilated subject for ventilation. The sensor is used to acquire ventilation data reflecting the ventilation status during the process of providing mechanical ventilation to the ventilated subject. The electrical impedance imaging device 520 includes an electrical impedance data acquisition unit and an electrical impedance data processing unit. The electrical impedance data acquisition unit is used to acquire electrical impedance signals, and the electrical impedance data processing unit is used to process the electrical impedance signals to obtain electrical impedance data. The processor 530 is connected to the ventilation device 510 and the electrical impedance imaging device 520 and is used in the steps of the method 100 or the method 400 for assessing lung recapacity as described above.

[0109] For example, the ventilation device 510 can be implemented as a medical device with mechanical ventilation function, such as a ventilator, anesthesia machine, or oxygen therapy machine. The ventilation circuit of the ventilation device 510 is connected to a gas source interface and a ventilation control unit, and is used to deliver the gas provided by the gas source interface to the ventilated subject under the control of the ventilation control unit. The gas provided by the gas source interface to the ventilated subject can be oxygen or a mixture of air and oxygen. The sensors include at least a pressure sensor for acquiring ventilation pressure data during the process of providing ventilation to the ventilated subject; the sensors may also include a flow rate sensor for acquiring ventilation flow rate data during the process of providing ventilation to the ventilated subject.

[0110] The electrical impedance imaging device 520 includes an electrical impedance data acquisition unit and an electrical impedance data processing unit. The electrical impedance data acquisition unit is used to acquire electrical impedance signals, and the electrical impedance data processing unit is used to process the electrical impedance signals to obtain electrical impedance data. The electrical impedance data acquisition unit is connected to multiple electrodes. During electrical impedance imaging, power is first supplied to a pair of electrodes, causing them to release current. The remaining electrodes then detect the voltage change on the human body surface to obtain the surface potential difference. Subsequently, a second pair of electrodes releases current, and the remaining electrodes again detect the voltage change. This process is repeated continuously, ultimately obtaining the conductivity distribution of the tissue. Multiple cross-sectional images can be obtained in one current cycle. The electrical impedance data processing unit combines all the cross-sectional images to obtain electrical impedance data reflecting changes in lung impedance. In some embodiments, the electrical impedance imaging device 520 can be a plug-in module, an external module, or a built-in module of the ventilation device 510; that is, the ventilation system 500 can be a ventilation device integrating an electrical impedance imaging module. In other embodiments, the electrical impedance imaging device 520 can be a standalone device.

[0111] Processor 530 may be a processor of ventilation device 510, a processor of electrical impedance imaging device 520, or a processor of a third-party device communicatively connected to ventilation device 510 and electrical impedance imaging device 520. Processor 530 may be implemented using software, hardware, firmware, or any combination thereof, and may use circuits, one or more application-specific integrated circuits, one or more general-purpose integrated circuits, one or more microprocessors, one or more programmable logic devices, or any combination of the aforementioned circuits and / or devices, or other suitable circuits or devices. Furthermore, processor 530 may control other components in ventilation device 510, electrical impedance imaging device 520, or third-party devices to perform desired functions.

[0112] In one embodiment, the ventilation system 500 further includes a communication module for establishing a communication connection between the ventilation device 510 and the processor 530, or between the processor 530 and the electrical impedance imaging device 520, through which the processor 530 controls the electrical impedance imaging device and / or the ventilation device. For example, when the processor 530 is the processor of the ventilation device 510, the communication module 510 is used to establish a communication connection between the processor 530 and the electrical impedance imaging device 520, through which the processor 530 controls the electrical impedance imaging device 520.

[0113] The ventilation system 500 of this application embodiment is used to implement the method 100 or method 400 for assessing lung re-expansion as described above. Specific details of these methods can be found above and will not be repeated here. The ventilation system 500 of this application embodiment can effectively utilize local ventilation information from EIT to assess lung re-expansion.

[0114] Another aspect of this application provides a ventilation device that can implement the above-described method 100 for assessing lung re-expansion. See also Figure 6 The ventilation device 600 of this application embodiment includes: a breathing circuit 610 for delivering gas to a ventilated subject for mechanical ventilation; a sensor 620 for acquiring ventilation data reflecting the ventilation status during the process of providing mechanical ventilation to the ventilated subject; a communication module 630 for communicating with an electrical impedance imaging device 700; the electrical impedance imaging device 700 is used to acquire electrical impedance data of the target subject; and a processor 640 for executing the steps of the method 100 for assessing lung recapacity or the method 400 for assessing lung recapacity.

[0115] The ventilation device 600 can be a medical device with mechanical ventilation function, such as a ventilator, anesthesia machine, or oxygen therapy machine. The communication module 620 provides a wired or wireless communication connection. The processor 640 receives electrical impedance data acquired by the electrical impedance imaging device 700 through the communication connection provided by the communication module 620 and executes the steps of method 100 or method 400 for assessing lung re-expansion. Specific details of these methods can be found above and will not be repeated here.

[0116] The ventilation device 600 of this application can effectively utilize local ventilation information from EIT to assess lung re-expansion.

[0117] Although exemplary embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above exemplary embodiments are merely illustrative and are not intended to limit the scope of this application. Various changes and modifications can be made therein by those skilled in the art without departing from the scope and spirit of this application. All such changes and modifications are intended to be included within the scope of this application as claimed in the appended claims.

[0118] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0119] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed.

[0120] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0121] Similarly, it should be understood that, in order to streamline this application and aid in understanding one or more of the various inventive aspects, features of this application may sometimes be grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of this application. However, this approach should not be construed as reflecting an intention that the claimed application requires more features than are expressly recited in each claim. Rather, as reflected in the corresponding claims, its inventive point lies in solving the corresponding technical problem with features fewer than all features of a single disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of this application.

[0122] Those skilled in the art will understand that, apart from the mutual exclusion of features, all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or apparatus so disclosed can be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0123] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of this application and form different embodiments. For example, in the claims, any one of the claimed embodiments can be used in any combination.

[0124] The various component embodiments of this application can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some modules according to the embodiments of this application. This application can also be implemented as an apparatus program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such an implementation of this application can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0125] It should be noted that the above embodiments are illustrative of this application and not limiting of it, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. This application can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0126] The above description is merely a specific embodiment or illustration of the embodiments of this application. The scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. The scope of protection of this application shall be determined by the scope of the claims.

Claims

1. A method for controlling a ventilation device to assess lung re-expansion, the ventilation device comprising a processor and a display, characterized in that, The method includes: The processor is controlled to perform the following steps: Ventilation is performed on the object under the first ventilation parameter, and the first impedance data corresponding to the first ventilation parameter is acquired during the ventilation process; A first lung image of the ventilated object is generated, the first lung image including a plurality of pixels, each of the plurality of pixels in the first lung image corresponding to a first electrical impedance data; The method involves determining a first target region in the lungs of the ventilated subject that has a preset alveolar opening state based at least on the first impedance data, and obtaining a first evaluation parameter based on the first target region. The lungs include multiple sub-regions. The method of determining the first target region in the lungs of the ventilated subject that has a preset alveolar opening state based at least on the first impedance data includes: determining the first target region in the lungs that has a preset alveolar opening state based on the change in the first impedance data corresponding to each sub-region in the lungs. The ventilator is ventilated under a second ventilation parameter used to enable lung recruitment, and second electrical impedance data corresponding to the second ventilation parameter is acquired during the ventilation process. A second lung image of the ventilated object is generated, the second lung image including the plurality of pixels, each of the plurality of pixels in the second lung image corresponding to a second electrical impedance data; Determining a second target region in the lung having the preset alveolar opening state based at least on the second impedance data, and obtaining a second evaluation parameter based on the second target region, wherein determining the second target region in the lung having the preset alveolar opening state based at least on the second impedance data includes: determining the second target region in the lung having the preset alveolar opening state based on the changes in the second impedance data corresponding to each sub-region in the lung; and The lung recoverability assessment results of the ventilated subject are obtained based on the first assessment parameter and the second assessment parameter; And control the display to show the first lung image, the second lung image, and the assessment results of the lung's re-expansion.

2. The method according to claim 1, characterized in that, The first impedance data includes first impedance data during the inhalation phase and first impedance data during the exhalation phase; the second impedance data includes second impedance data during the inhalation phase and second impedance data during the exhalation phase. The step of determining the first target region in the lung with a preset alveolar open state based on the change of the first impedance data corresponding to each sub-region in the lung includes: obtaining the change of the first impedance data based on the first impedance data during the inhalation phase and the first impedance data during the exhalation phase; Based on the changes in the first impedance data corresponding to each sub-region in the lung, and based on the first impedance data of the inspiratory phase and / or the first impedance data of the expiratory phase corresponding to each sub-region in the lung, a first target region in the lung with a preset alveolar open state is determined. The step of determining a second target region in the lung with a preset alveolar opening state based on the changes in the second impedance data corresponding to each sub-region in the lung includes: obtaining the changes in the second impedance data based on the second impedance data during the inhalation phase and the second impedance data during the exhalation phase; Based on the changes in the second impedance data corresponding to each sub-region in the lung, and based on the second impedance data of the inspiratory phase and / or the second impedance data of the expiratory phase corresponding to each sub-region in the lung, a second target region in the lung with the preset alveolar open state is determined.

3. The method according to claim 2, characterized in that, The preset alveolar opening state includes at least one of the following: shear state, collapse state, overinflation state, normal state, or alveolar opening state derived from shear state, collapse state, or overinflation state.

4. The method according to claim 3, characterized in that, The step of determining the first target region in the lung having the preset alveolar open state based on the changes in the first impedance data corresponding to each sub-region in the lung, and based on the first impedance data of the inspiratory phase and / or the first impedance data of the expiratory phase corresponding to each sub-region in the lung, includes: The first target region having the collapsed state is determined based on the change in the first electrical impedance data and the first electrical impedance data during the exhalation phase; The first target region having the shear state is determined based on the change in the first electrical impedance data and the first electrical impedance data during the exhalation phase; A first target region having the over-expansion state is determined based on the change in the first impedance data and the first impedance data during the inhalation phase; A first target region having the normal state is determined based on the change in the first electrical impedance data, the first electrical impedance data during the inhalation phase, and the first electrical impedance data during the exhalation phase; The step of determining the second target region in the lung having the preset alveolar opening state based on the changes in the second impedance data corresponding to each sub-region in the lung, and based on the second impedance data of the inspiratory phase and / or the second impedance data of the expiratory phase corresponding to each sub-region in the lung, includes: The second target region having the collapsed state is determined based on the change in the second electrical impedance data and the second electrical impedance data during the exhalation phase; The second target region having the shear state is determined based on the change in the second electrical impedance data and the second electrical impedance data during the exhalation phase; A second target region having the over-expansion state is determined based on the change in the second electrical impedance data and the second electrical impedance data during the inhalation phase; A second target region having the normal state is determined based on the changes in the second impedance data, the second impedance data during the inhalation phase, and the second impedance data during the exhalation phase.

5. The method according to claim 1, characterized in that, The first evaluation parameter is obtained based at least on the area of ​​the first target region, and the second evaluation parameter is obtained based at least on the area of ​​the second target region; Alternatively, the first evaluation parameter is obtained at least based on the ratio of the area of ​​the first target region to the area of ​​the lung, and the second evaluation parameter is obtained at least based on the ratio of the area of ​​the second target region to the area of ​​the lung; Alternatively, the first evaluation parameter is obtained based at least on the number of pixels in the first target region, and the second evaluation parameter is obtained based at least on the number of pixels in the second target region; Alternatively, the first evaluation parameter is obtained at least based on the ratio of the number of pixels in the first target region to the total number of pixels in the lung, and the second evaluation parameter is obtained at least based on the ratio of the number of pixels in the second target region to the total number of pixels in the lung.

6. The method according to claim 5, characterized in that, The assessment result of lung recoverability obtained based on the first assessment parameter and the second assessment parameter includes: The first evaluation parameter and the second evaluation parameter are compared to obtain the evaluation result of lung recoverability.

7. The method according to claim 6, characterized in that, The comparison of the first evaluation parameter and the second evaluation parameter to obtain the evaluation result of lung recapillability includes: The difference or ratio between the first evaluation parameter and the second evaluation parameter is calculated, and the evaluation result of lung recoverability is obtained based on the difference or ratio.

8. The method according to claim 1, characterized in that, The lungs comprise multiple sub-regions; The method further includes: Acquire the first ventilation pressure data under the first ventilation parameter and the second ventilation pressure data under the second ventilation parameter; The step of determining a first target region in the lung with a preset alveolar open state based on the first electrical impedance data includes: Based on the change of the first electrical impedance data corresponding to each sub-region in the lung over time, the first alveolar opening time corresponding to each sub-region is determined; Based on the first alveolar opening time corresponding to each sub-region and the first ventilation pressure data corresponding to the first alveolar opening time, determine the first opening pressure data corresponding to each sub-region; The first target region in the lung with a preset alveolar opening state is determined based on the first opening pressure data corresponding to each sub-region; The step of determining a second target region in the lungs with a preset alveolar opening state based on the second electrical impedance data includes: Based on the change of the second electrical impedance data corresponding to each sub-region in the lung over time, the second alveolar opening time corresponding to each sub-region is determined; Based on the second alveolar opening time corresponding to each sub-region and the second ventilation pressure data corresponding to the second alveolar opening time, determine the second opening pressure data corresponding to each sub-region; The second target region in the lung with the preset alveolar opening state is determined based on the second opening pressure data corresponding to each sub-region.

9. The method according to claim 8, characterized in that, The step of determining the first alveolar opening time for each sub-region based on the change of the first electrical impedance data over time in each sub-region of the lung includes: The first alveolar opening time for each sub-region is determined based on the time when the first impedance data corresponding to each sub-region reaches a preset impedance threshold during the inspiratory phase of the respiratory cycle. The preset impedance threshold is determined based on the peak value reached by the first impedance data corresponding to each sub-region during the respiratory cycle. The determination of the second alveolar opening time for each sub-region based on the change of the second electrical impedance data over time in each sub-region of the lung includes: The second alveolar opening time for each sub-region is determined based on the time it takes for the second electrical impedance data corresponding to each sub-region to reach an electrical impedance threshold during the inspiratory phase of the respiratory cycle, wherein the electrical impedance threshold is determined based on the peak value reached by the second electrical impedance data corresponding to each sub-region during the respiratory cycle.

10. The method according to claim 8, characterized in that, The preset alveolar opening state includes an easily opening state and / or a difficult-to-open state; determining the first target region in the lung with the preset alveolar opening state based on the first opening pressure data corresponding to each sub-region includes: The sub-regions whose open pressure data is greater than the first preset pressure threshold are identified as the first target regions with the difficult-to-open state; The sub-regions whose open pressure data is less than or equal to the first preset pressure threshold are identified as the first target regions with the easy-to-open state; The step of determining the second target region in the lung with a preset alveolar opening state based on the second opening pressure data corresponding to each sub-region includes: The sub-regions whose opening pressure data is greater than the first preset pressure threshold are identified as the second target regions with the difficult-to-open state; The sub-regions whose open pressure data is less than or equal to the first preset pressure threshold are identified as the second target regions with the easy-to-open state; Wherein, the first preset pressure threshold is not greater than the inspiratory pressure under the first ventilation parameter and the inspiratory pressure under the second ventilation parameter.

11. The method according to claim 10, characterized in that, The first evaluation parameter is obtained based at least on the area of ​​the first target region, and the second evaluation parameter is obtained based at least on the area of ​​the second target region; Alternatively, the first evaluation parameter is obtained at least based on the ratio of the area of ​​the first target region to the area of ​​the lung, and the second evaluation parameter is obtained at least based on the ratio of the area of ​​the second target region to the area of ​​the lung; Alternatively, the first evaluation parameter is obtained based at least on the number of pixels in the first target region, and the second evaluation parameter is obtained based at least on the number of pixels in the second target region; Alternatively, the first evaluation parameter is obtained at least based on the ratio of the number of pixels in the first target region to the total number of pixels in the lung, and the second evaluation parameter is obtained at least based on the ratio of the number of pixels in the second target region to the total number of pixels in the lung.

12. The method according to claim 8, characterized in that, The ventilation pressure data includes at least one of the following: airway pressure data, esophageal pressure data, transpulmonary pressure data, and intrapulmonary pressure data.

13. A method for controlling a ventilation device to assess lung re-expansion, the ventilation device comprising a processor and a display, characterized in that, The method includes: The processor is controlled to perform the following steps: Ventilation is performed on the object under the first ventilation parameter, and the first impedance data corresponding to the first ventilation parameter is acquired during the ventilation process; A first lung image of the ventilated object is generated, the first lung image including a plurality of pixels, each of the plurality of pixels in the first lung image corresponding to a first electrical impedance data; The first alveolar opening state of a plurality of sub-regions in the lungs of the ventilated object is determined at least based on the first impedance data, wherein the sub-regions are composed of one or more pixels having the same first alveolar opening state; The ventilator is ventilated under a second ventilation parameter used to enable lung recruitment, and second electrical impedance data corresponding to the second ventilation parameter is acquired during the ventilation process. A second lung image of the ventilated object is generated, the second lung image including the plurality of pixels, each of the plurality of pixels in the second lung image corresponding to a second electrical impedance data; The second alveolar opening state of the plurality of sub-regions is determined at least based on the second electrical impedance data, wherein the sub-regions are composed of one or more pixels having the same second alveolar opening state; The re-expansion capability of each sub-region is obtained based on the first alveolar opening state and the second alveolar opening state of each sub-region; and The lung recapacity assessment result of the ventilated object is obtained based on the recapacity of the multiple sub-regions; And control the display to show the first lung image, the second lung image, and the assessment results of the lung's re-expansion.

14. The method according to claim 13, characterized in that, The first impedance data includes first impedance data during the inhalation phase and first impedance data during the exhalation phase; the second impedance data includes second impedance data during the inhalation phase and second impedance data during the exhalation phase. The step of determining the first alveolar opening state of multiple sub-regions in the lungs of the ventilated subject based at least on the first impedance data includes: The change in the first electrical impedance data is obtained based on the first electrical impedance data during the inhalation phase and the first electrical impedance data during the exhalation phase; The first alveolar opening state of each sub-region is determined based on the change of the first impedance data corresponding to each sub-region, and based on the first impedance data of the inspiratory phase and / or the first impedance data of the expiratory phase corresponding to each sub-region. The step of determining the second alveolar opening state of multiple sub-regions in the lungs of the ventilated subject, at least based on the second electrical impedance data, includes: The change in the second electrical impedance data is obtained based on the second electrical impedance data during the inhalation phase and the second electrical impedance data during the exhalation phase; The second alveolar opening state corresponding to each sub-region is determined based on the change in the second electrical impedance data corresponding to each sub-region, and based on the second electrical impedance data of the inspiratory phase and / or the second electrical impedance data of the expiratory phase corresponding to each sub-region.

15. The method according to claim 14, characterized in that, The first alveolar open state includes at least one of the following: shear state, collapsed state, overinflated state, normal state, or an alveolar open state derived from the shear state, collapsed state, or overinflated state. The collapsed state is determined based on the changes in the first impedance data and the first impedance data during the expiratory phase; the shearing state is determined based on the changes in the first impedance data and the first impedance data during the expiratory phase; the over-inflation state is determined based on the changes in the first impedance data and the first impedance data during the inspiratory phase; the first alveolar opening state corresponding to the sub-region that does not belong to the over-inflation state, the shearing state, or the collapsed state is the normal state; The second alveolar open state includes at least one of the following: shear state, collapsed state, overinflated state, normal state, or an alveolar open state derived from the shear state, collapsed state, or overinflated state. The collapsed state is determined based on the change in the second impedance data and the second impedance data during the expiratory phase; the shearing state is determined based on the change in the second impedance data and the second impedance data during the expiratory phase; the over-inflation state is determined based on the change in the second impedance data and the second impedance data during the inspiratory phase; the second alveolar opening state corresponding to the sub-region that does not belong to the over-inflation state, the shearing state, or the collapsed state is the normal state.

16. The method according to claim 13, characterized in that, The method further includes: Acquire the first ventilation pressure data under the first ventilation parameter and the second ventilation pressure data under the second ventilation parameter; The step of determining the first alveolar opening state of multiple sub-regions in the lungs of the ventilated subject based at least on the first impedance data includes: Based on the change of the first electrical impedance data corresponding to each sub-region over time, the first alveolar opening time corresponding to each sub-region is determined; Based on the first alveolar opening time corresponding to each sub-region and the first ventilation pressure data corresponding to the first alveolar opening time, determine the first opening pressure data corresponding to each sub-region; The first alveolar opening state of each sub-region is determined based on the first opening pressure data corresponding to each sub-region, and the first alveolar opening state includes an easy-to-open state or an difficult-to-open state. The determination of the second alveolar opening state of the plurality of sub-regions based at least on the second electrical impedance data includes: Based on the change of the second electrical impedance data corresponding to each sub-region over time, the second alveolar opening time corresponding to each sub-region is determined; Based on the second alveolar opening time corresponding to each sub-region and the second ventilation pressure data corresponding to the second alveolar opening time, determine the second opening pressure data corresponding to each sub-region; The second alveolar opening state of each sub-region is determined based on the second opening pressure data corresponding to each sub-region, and the second alveolar opening state includes an easy-to-open state or an difficult-to-open state.

17. The method according to claim 16, characterized in that, Comparing the first alveolar opening state and the second alveolar opening state of each sub-region to obtain the re-expansionability of each sub-region includes: If the first alveolar opening state is difficult to open, and the second alveolar opening state is easy to open, then the sub-region is determined to be re-expandable.

18. The method according to claim 13, characterized in that, The step of obtaining the lung re-expansion assessment result of the ventilated object based on the re-expansion of the multiple sub-regions includes: comparing the proportion of re-expansionable sub-regions in the multiple sub-regions with a predetermined threshold; if the proportion exceeds the predetermined threshold, then determining that the lung re-expansion of the ventilated object meets the preset requirements.

19. A ventilation system, characterized in that, The ventilation system includes ventilation equipment, impedance equipment, and a processor, wherein, The ventilation device includes a breathing circuit and a sensor. The breathing circuit is used to deliver gas to the person being ventilated for ventilation. The sensor is used to acquire ventilation data reflecting the ventilation status during the process of providing mechanical ventilation to the person being ventilated. The impedance device includes an impedance data acquisition unit and an impedance data processing unit. The impedance data acquisition unit is used to acquire impedance signals, and the impedance data processing unit is used to process the impedance signals to obtain impedance data. A processor for performing the method for assessing lung re-expansion as claimed in any one of claims 1-18.

20. A ventilation device, characterized in that, The ventilation equipment includes: A breathing circuit for delivering gas to the person being ventilated for mechanical ventilation; A sensor, wherein the sensor is used to acquire ventilation data reflecting the ventilation status during the process of providing mechanical ventilation to a ventilated object; A communication module is used to communicate with an impedance device, which is used to collect impedance data during the process of providing ventilation to the ventilated object; A processor for performing the method for assessing lung re-expansion as claimed in any one of claims 1-18.

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