WO2024003413A1

WO2024003413A1 - Method for controlling spontaneously triggered mechanical ventilation of a patient

Info

Publication number: WO2024003413A1
Application number: PCT/EP2023/068192
Authority: WO
Inventors: Serge Jan Hubert HEINES; Sebastiaan Andreas Maria DE JONGH; Dennis Christiaan Johan Jozef BERGMANS
Original assignee: Academisch Ziekenhuis Maastricht; Universiteit Maastricht
Priority date: 2022-07-01
Filing date: 2023-07-03
Publication date: 2024-01-04

Abstract

A computer-implemented method for controlling spontaneously triggered mechanical ventilation of a patient, the method comprising: obtaining electrical impedance tomography, EIT, data recorded during a PEEP trial; detecting at least one aerated region among the of lung-related tissue regions in the PEEP trial, based on the obtained EIT data; determining at least one regional peak flow, RPF, corresponding with the at least one aerated region, based on the obtained EIT data; calculating at least one set of regional lung mechanics parameters for the at least one aerated region, based on the at least one RPF; and outputting the at least one set of regional lung mechanics parameters for the at least one aerated region or a parameter derived therefrom, in a format suitable for direct input into a spontaneously triggered mechanical ventilator.

Description

Method for controlling spontaneously triggered mechanical ventilation of a patient

TECHNICAL FIELD

The present disclosure relates to controlling mechanical ventilation of patients. Particular embodiments relate to a computer-implemented method for controlling spontaneously triggered mechanical ventilation of a patient, to a computer program, to a computer-readable storage medium, to a data processing apparatus, and to a system for controlling spontaneously triggered mechanical ventilation of a patient.

BACKGROUND

A conventional approach for determining regional lung mechanics is based on a plateau pressure phase. This phase is achieved shortly after the end of the inspiration phase, and involves a pressure equilibrium in the lungs. Based on the difference in pressure equilibrium AP, and based on electrical impedance tomography (EIT) measurements of regional impedance Az, a regional lung compliance is calculated as Cregion = Az/AP. In this expression, Az represents the measured change in impedance which is highly correlated with change in volume of the lungs during a breath.

Spontaneous efforts during invasive mechanical ventilation in acute respiratory distress syndrome (ARDS) are widely recognized for improving oxygenation and preserving muscle function. Weaning from mechanical ventilation can be conducted through spontaneous mechanical ventilation (SMV), where spontaneous breathing efforts are allowed. These efforts may be gentle or vigorous depending on the severity of ARDS. Vigorous efforts are more likely to occur in moderate to severe ARDS and are linked to worsening of the lung and diaphragm injury. Higher positive end expiratory (PEEP) levels are linked to a decreased magnitude of these vigorous efforts. Positive end-expiratory pressure (PEEP) is the maintenance of positive pressure (above atmospheric) at the airway opening at the end of expiration. Electrical impedance tomography (EIT) is a non-invasive type of medical imaging in which the electrical conductivity, permittivity, and impedance of a part of the body is inferred from surface electrode measurements and used to form a tomographic image of that part. Compared to the tissue conductivities of most other soft tissues within the human thorax, lung tissue conductivity is approximately five-fold lower, resulting in high absolute contrast.

SUMMARY

It is an insight of the inventors that the above-described conventional approach for determining regional lung mechanics cannot be applied for patients undergoing spontaneous mechanical ventilation (SMV), because in this case a plateau pressure phase is usually not reached. This is because, on the one hand, these patients pull more strongly on their posterior lung fields with their diaphragm during inspiration, causing greater pressure differences on inspiration than with controlled ventilation (in controlled ventilation, patients are sedated and (sometimes) neuro-muscularly blocked by medication, such that the patient’s muscular function is suppressed and the patient’s diaphragm does not pull on the lungs), and because, on the other hand, most of these patients enter an expiration phase too quickly. When the conventional approach is applied for these patients, there is a risk of overestimation or underestimation of regional lung mechanics, which will impact clinical decisions made for the patient when using EIT.

It is an aim of at least some embodiments according to the present disclosure to address the above-described problem.

Accordingly, there is provided in a first aspect of the present disclosure a computer- implemented method for controlling spontaneously triggered mechanical ventilation of a patient. The method comprises the following steps. Obtaining electrical impedance tomography, EIT, data recorded during a positive end-expiratory pressure, PEEP, trial imposed on the patient, wherein the EIT data represents a plurality of electrical impedances over a plurality of lung-related tissue regions of the patient over a duration of the PEEP trial. Detecting at least one aerated region among the plurality of lung- related tissue regions, based on the obtained EIT data. Determining at least one regional peak flow, RPF, corresponding with the at least one aerated region, based on the obtained EIT data. Calculating at least one set of regional lung mechanics parameters for the at least one aerated region, based on the at least one RPF. Outputting the at least one set of regional lung mechanics parameters for the at least one aerated region or at least one parameter derived from the at least one set of regional lung mechanics parameters, in a format suitable for direct input into a spontaneously triggered mechanical ventilator.

The method requires access to EIT data. The EIT data should have been recorded during a PEEP trial imposed on the patient. The EIT data may be fed to the computer implementing the computer-implemented method directly via a machine-to-machine connection between the computer and a PEEP apparatus as output from the PEEP apparatus, or the EIT data may be made available to the computer in some other way, for example via a memory to which both the computer and the PEEP apparatus share access, or via a computer network connection, for example allowing internet access, or via a computer-readable data carrier, such as a USB stick or an optical disc.

The method involves detecting at least one aerated region, because only aerated regions, i.e. regions of the lung in which (an appreciable amount of) air enters, are relevant for determining regional lung mechanics in the context of mechanical ventilation. Other regions of the thorax into which air does not enter are not or much less relevant.

The method further involves determining at least one regional peak flow (RPF), because RPF corresponds well with regional pulmonary compliance, i.e. RPF is a good indicator of how good regional lung mechanics are, i.e. how well a region of the lung operates during breathing.

The method also involves calculating and outputting at least one set of regional lung mechanics parameters (or outputting a parameter derived therefrom), in a format suitable for direct input into a spontaneously triggered mechanical ventilator. The reason for this output format, is to ensure that the output of the method can directly be used to control the spontaneously triggered mechanical ventilator, which thus ensures that the method serves for controlling spontaneously triggered mechanical ventilation of a patient. As an example, the output may be directly fed into the spontaneously triggered mechanical ventilator, e.g. as a control input, or the output may be provided to a human operator who subsequently enters the output (or a value derived from the output) as a control input to the spontaneously triggered mechanical ventilator.

In some embodiments, the step of calculating at least one set of regional lung mechanics parameters for the at least one aerated region, based on the at least one RPF, comprises:

- determining a reference point in the EIT data, the reference point representing a reference pressure stage of the PEEP trial coupled with a highest RPF among the at least one RPF;

- determining a plurality of overdistension parameters for the at least one aerated region, each overdistension parameter representing an RPF lower than the highest RPF and corresponding with a higher pressure stage of the PEEP trial than the reference pressure stage; and

- determining a plurality of collapse parameters for the at least one aerated region, each collapse parameter representing an RPF lower than the highest RPF and corresponding with a lower pressure stage of the PEEP trial than the reference pressure stage.

In some embodiments, the method comprises filtering the obtained EIT data using a low-pass filter, preferably a Butterworth filter having a filter order of at least four, preferably having a cut-off frequency between an average human respiratory rate and an average human heart rate, more preferably having a cut-off frequency between 0.67 Hz and 1 Hz, most preferably having a cut-off frequency of approximately 0.83 Hz.

In this context, “approximately 0.83 Hz” may be taken to mean any frequency value whose effect is indistinguishable from the effect at 0.83 Hz. In particular, frequency values between 0.80 Hz and 0.85 Hz are all believed to be “approximately 0.83 Hz”.

Note that 0.67 Hz corresponds approximately with a rate of 40 BPM, which is lower than average for a human heart rate and higher than average for a human respiratory rate. The skilled person will appreciate that if the heart rate of a patient should drop lower than 40 BPM and/or if the respiratory rate of a patient should rise higher than 40 times per minute, a medical intervention may be required. Therefore, it can be presumed safe to choose 0.67 Hz as a cut-off value.

In some embodiments, the step of detecting at least one aerated region among the plurality of lung-related tissue regions, based on the obtained EIT data, comprises:

- determining a maximum impedance of the tissue regions;

- setting a threshold value based on the determined maximum impedance, wherein the threshold value preferably lies in a range of 7.5 to 20 percent of the determined maximum impedance, and more preferably represents approximately 7.5 percent of the determined maximum impedance; and

- selecting any tissue regions having an impedance greater than or equal to the threshold value.

In this context, “approximately 7.5 percent” may be taken to mean any percent value in the range of 7.4 percent to 7.6 percent. Other than the preferred value of approximately 7.5 percent, it is currently believed that values in the range of 7.5 to 20 percent are also suitable.

In some embodiments, the ratio of the at least one aerated region to the plurality of lung-related tissue regions is used to correct or weight the at least one regional lung mechanics parameter or the at least one parameter derived therefrom.

In some embodiments, the at least one parameter derived from the at least one set of regional lung mechanics parameters is based on a weighted average of the at least one set of regional lung mechanics parameters, over all aerated regions among the at least one aerated region.

In some further developed embodiments, the at least one parameter derived from the at least one set of regional lung mechanics parameters is based on a weighted average of the overdistension parameters and a weighted average of the collapse parameters over all aerated regions among the at least one aerated region. In some embodiments, the method comprises detecting a number of breaths for the at least one aerated region, based on the obtained EIT data. Herein, determining at least one RPF, for the at least one aerated region, comprises determining the at least one RPF for the or each breath for the at least one aerated region.

In some embodiments, the number of breaths is detected for the at least one aerated region over descending pressure steps of the PEEP trial.

In some embodiments, the step of determining at least one RPF, for the or each breath for the at least one aerated region, comprises:

- determining a plurality of slopes of each particular breath among the or each breath, for the at least one aerated region; and

- determining a maximum slope among the plurality of slopes as the RPF for each particular breath.

In some embodiments, wherein slopes of breaths are detected over descending pressure steps of the PEEP trial, the method further comprises, for the at least one aerated region, determining a statistical value, preferably the median, based on the maximum slopes for all breaths among the or each breath of said aerated region over each pressure step of the PEEP trial, and using the determined statistical value, preferably the median, as the RPF.

In some embodiments, a slope of a breath is a first-order derivative based on at least three samples of a slope of said breath.

In some embodiments, each set of regional lung parameters of the at least one set of regional lung parameters comprises an overdistension parameter and a collapse parameter for a corresponding aerated region of the at least one aerated region, wherein an overdistension of an aerated region relates to a measure of hyperinflation of lung tissue, and wherein a collapse of an aerated region relates to a measure of atelectasis of lung tissue. In this context, the skilled person will appreciate that overdistension stems from some lung tissue suffering from collapse (atelectasis) and thus being underinflated, which leads to other lung tissue being overinflated, i.e. overdistended.

In some embodiments, direct input into the spontaneously triggered mechanical ventilator comprises:

- a machine-to-machine coupling between the computer implementing the method and the spontaneously triggered mechanical ventilator; or

- receiving configuration input from a human operator into the spontaneously triggered mechanical ventilator, in case the spontaneously triggered mechanical ventilator disallows a machine-to-machine coupling with the computer implementing the method.

In this way, the input can be made as directly as is possible or allowed into the ventilator. In a particular example, the machine-to-machine coupling may comprise a serial interface.

There is provided in a second aspect of the present disclosure a computer program comprising instructions configured for, when executed by at least one processor, causing the at least one processor to perform the steps of the method of any of the previous claims.

There is provided in a third aspect of the present disclosure a computer-readable storage medium storing the above-described computer program embodiment.

There is provided in a fourth aspect of the present disclosure a data processing apparatus comprising at least one processor and at least one memory, the at least one memory storing the above-described computer program embodiment.

There is provided in a fifth aspect of the present disclosure a system for controlling spontaneously triggered mechanical ventilation of a patient. The system comprises: an electrical impedance tomography scanner; a patient ventilator; and a data processing apparatus according to the above-described embodiment. The skilled person will understand that considerations and advantages described with respect to embodiments of the method according to the present disclosure may also apply to embodiments of the computer program, the data processing apparatus, and the system according to the present disclosure.

The above-described embodiments are illustrative and are not limiting to the present invention. The skilled person will understand that additional features may be added to the illustrative embodiments described herein, while still falling within the scope determined by the independent claims.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following description, a number of exemplary embodiments will be described in more detail, to improve understanding, with reference to the appended drawings:

Figure 1 schematically illustrates an embodiment of a system 10 according to the present disclosure.

Figure 2 schematically illustrates a flowchart of an embodiment of a method 20 according to the present disclosure.

Figure 3 schematically illustrates an example graph 30 of global impedance values 31 over sampling time 32 during a positive end-expiratory pressure, PEEP, trial.

Figure 4 schematically illustrates an example of regional EIT data for use with various embodiments according to the present disclosure.

Figure 5 schematically illustrates an example of detecting at least one aerated region among the plurality of lung-related tissue regions, based on the obtained EIT data, as performed in or with various embodiments according to the present disclosure.

Figure 6 schematically illustrates an example of a statistical procedure for detecting at least one aerated region among the plurality of lung-related tissue regions, based on the obtained EIT data, as performed in or with various embodiments according to the present disclosure.

Figure 7 schematically illustrates an example of detecting a number of breaths for the at least one aerated region, based on the obtained EIT data, as performed in or with various embodiments according to the present disclosure. Figure 8 schematically illustrates an example showing how a slope of a breath can be determined as a first-order derivative based on at least three samples of a slope of said breath.

Figure 9 schematically illustrates an example showing how to calculate at least one set of regional lung mechanics parameters for the at least one aerated region, based on the at least one RPF.

Figure 10 schematically illustrates an output of a parameter derived from the at least one set of regional lung mechanics parameters, in a format suitable for direct input into a spontaneously triggered mechanical ventilator.

DETAILED DESCRIPTION OF THE DRAWINGS

Figure 1 schematically illustrates an embodiment of system 10 according to the present disclosure. System 10 comprises an electrical impedance tomography, EIT, scanner 11. Any suitable EIT scanner may be used, e.g. any of various commercially available EIT scanners. System 10 further comprises a data processing apparatus 12, such as a computer (e.g. a laptop, a general purpose desktop, a notebook, a sufficiently performant smartphone, or a dedicated computer hardware setup). EIT scanner 11 may be coupled to data processing apparatus 12 via a data connection, e.g. a serial cable interface.

Data processing apparatus 12 comprises at least one processor and at least one memory, the at least one memory storing a computer program comprising instructions configured for, when executed by the at least one processor, causing the at least one processor to perform the steps of a method according to the present disclosure.

System 10 further comprises an output interface 13, preferably integrated into data processing apparatus 12 although output interface 13 may be embodied on a separate device), in order to output the at least one set of regional lung mechanics parameters for the at least one aerated region or at least one parameter derived from the at least one set of regional lung mechanics parameters, in a format suitable for direct input into a spontaneously triggered mechanical ventilator 14 of system 10. Ventilator 14 may be coupled to output interface 13 directly, e.g. via a machine-to-machine connection, or indirectly, which is represented in the figure via a dotted line, e.g. in case ventilator 14 disallows, i.e. is not configured for or even forbids, direct input from another device, in particular data processing apparatus 12. Indirect input from output interface 13 may for example comprise receiving configuration input from a human operator into the spontaneously triggered mechanical ventilator, in case the spontaneously triggered mechanical ventilator disallows a machine-to-machine coupling with the computer implementing the method. In this case, output interface 13 may simply comprise a visual output display, or even a printer device, such that a human operator of ventilator 14 may inspect output interface 13 in order to suitable configure ventilator 14. Thus, data processing apparatus 12 directly or indirectly controls ventilator 14.

Figure 2 schematically illustrates a flowchart of an embodiment of a method 20 according to the present disclosure. The method 20 is computer-implemented and may serve for controlling spontaneously triggered mechanical ventilation of a patient. The method 20 starts at SO and comprises steps S1-S5.

Step S1 is obtaining electrical impedance tomography, EIT, data recorded during a positive end-expiratory pressure, PEEP, trial imposed on the patient, wherein the EIT data represents a plurality of electrical impedances over a plurality of lung-related tissue regions of the patient over a duration of the PEEP trial.

Step S2 is detecting at least one aerated region among the plurality of lung-related tissue regions, based on the obtained EIT data.

Step S3 is determining at least one regional peak flow, RPF, corresponding with the at least one aerated region, based on the obtained EIT data.

Step S4 is calculating at least one set of regional lung mechanics parameters for the at least one aerated region, based on the at least one RPF.

Step S5 is outputting the at least one set of regional lung mechanics parameters for the at least one aerated region or at least one parameter derived from the at least one set of regional lung mechanics parameters, in a format suitable for direct input into a spontaneously triggered mechanical ventilator. The skilled person will appreciate that additional steps may be added to further develop the embodiment of the method 20, based on features described in the present disclosure, as long as these combinations are not internally incoherent.

Figure 3 schematically illustrates an example graph 30 of global impedance values 31 over sampling time 32 during a positive end-expiratory pressure, PEEP, trial. In the graph, every data point along the horizontal axis represents a breath of the patient and the vertical extent of the signal represents the amplitude of that breath. The global impedance change values 31 may be the sums of impedances for all regions under consideration. The graph 30 shows a baseline 33, wherein no PEEP trial is imposed on the patient. The graph 30 also shows an ascending pressure stage 34 of the PEEP trial, wherein pressure is gradually increased. Due to increased PEEP, more air is introduced into the lungs of the patient at end-expiration. Due to the increased end- expiratory volume of air in the patient’s lungs, a higher impedance change value is registered via EIT. At some point, a maximum impedance value is reached, indicating a maximum pressure of the PEEP trial. From a medical perspective, this maximum impedance value shows a good or even a maximum recruitment of lung capacity. In practice, the skilled person may use well-known medical safety protocols to determine the maximum pressure allowed in the PEEP trial. Moreover, it is preferred to concomitantly monitor the patient’s blood oxygen saturation in order to limit the ascending pressure stage 34.

After the point 35 with maximum pressure, the graph 30 shows a descending pressure stage 36 of the PEEP trial, wherein pressure is gradually decreased, preferably until the PEEP level that shows a decrease of dynamic compliance, or else to or close to baseline again. By having more individual ascending and/or descending pressure steps in the PEEP trial, it is possible to more accurately differentiate between regional lung mechanics of separate regions. For example, some regions may only open at relatively high pressure, whereas other regions may experience overdistension at that same high pressure.

Figure 4 schematically illustrates an example of EIT data for use with various embodiments according to the present disclosure. The figure shows an image frame 40 having multiple individual pixels (i.e., regions), each pixel representing a lung- related tissue region. The tissue regions are comprised of physical tissue of the patient within the scope of the EIT electrode belt and are lung-related in the sense that they either are lung tissue or are situated close to lung tissue in the patient’s thorax and are thus also measured by the EIT. Each region actually represents a complex variety of tissues of the patient’s thorax, but the EIT compacts this variety of tissues into one single region, as a pixel. The colour intensity of the pixel represents the change in impedance 41 measured by the EIT: lighter-coloured regions indicate a higher positive change in impedance (i.e. an increased amount of air is present in lung-related tissues compacted into that pixel), whereas darker-coloured regions indicate a zero or higher negative change in impedance (i.e. no air or less air is present in lung-related tissues compacted into that pixel).

For one pixel 45, its individual change 42 in impedance 43 over time 44 is shown in the bottom graph, indicating change in impedance Az. This may be interpreted as a measure for the amount of air in a particular lung-related tissue region of the patient.

In Figures 4, 5, 7 and 8, changes in impedance Az are expressed in arbitrary units, AU, intended as an illustrative example only.

Figure 5 schematically illustrates an example of detecting at least one aerated region among the plurality of lung-related tissue regions, based on the obtained EIT data, as performed in or with various embodiments according to the present disclosure. The figure shows an image frame 50 at an arbitrary time point, corresponding with image frame 40 of Figure 4, expressing change in impedance 51 for a plurality of lung-related tissue regions. Three individual regions have been marked 52A, 53A and 54A in the image frame 50. Similarly to Figure 4, the individual changes 52B, 53B and 54B in impedance 51 over time 55 are shown in the bottom graph, for the individual regions 52A, 53A and 54A.

A maximum impedance change value 56 may be determined in a particular pressure level of the PEEP trial. A distinction may be made between regions that are aerated 58 and regions that are not aerated 59, by calculating a threshold value 57 (in this example a threshold value of approximately 7.5% of the maximum impedance value 56, but any value within the range of 7.5% to 20% is believed to be suitable, depending on circumstances) and by comparing an average impedance change of a region with the threshold value 57. In this case, regions 52B and 53B are aerated (53B more than 52B), and 54B is not in a particular pressure level of the PEEP trial.

Preferably, as soon as a region is considered aerated once, i.e. at at least one time sample, then this region may be considered ventilated throughout.

Figure 6 schematically illustrates an example of a statistical procedure for detecting at least one aerated region among the plurality of lung-related tissue regions at multiple pressure levels of the PEEP trial, based on the obtained EIT data, as performed in or with various embodiments according to the present disclosure. In this example, all aerated regions in multiple PEEP pressure levels (numbered 1-6) of a set of aerated regions frames 61 may be combined into a single overall aerated regions frame 62 showing all aerated regions during the entire PEEP trial. In other words, aerated regions at separate PEEP levels may be stacked into a single, cumulative frame that considers any region aerated if it was aerated at least once during the PEEP trial.

Figure 7 schematically illustrates an example of detecting a number of breaths for one of the at least one aerated region, based on the obtained EIT data, as performed in or with various embodiments according to the present disclosure. The figure shows a graph of change 70 in impedance 71 over time 72 for an individual aerated region. By identifying peaks 73 and troughs 74 of the change 70 in impedance 71 for an individual aerated region, individual breaths within an individual aerated region may be detected, because the impedance 71 changes for an individual aerated region as air is inhaled and exhaled in individual breaths.

Figure 8 schematically illustrates an example showing how a slope of a breath can be determined as a first-order derivative based on at least three samples of a slope of said breath. The figure shows a breath 80, which is a rising and falling part of a change in impedance for an individual aerated region. The breath 80 rises from a trough 81 at the start of the breath, i.e. inspiration (denoted Startup) to a peak 82 at the end of the breath, i.e. expiration (denoted End_exp). In order to determine the slope of the breath at time t, a mathematical first-order derivative Az_t,_n 83 can be determined. In order to calculate Az_t,_n 83, neighbouring sample points Az_t,_n-i 84 and Az_t,_n+i 85 can be taken into account. In this manner, Az_t,_n represents a slope of the breath. Of course, the slope may be determined for the rising part of the breath (as is the case in this example), but alternatively or additionally may be determined for the falling part of the breath.

Subsequently, it is possible to compare all slopes of the breath to each other, and to consider the greatest (i.e. steepest) slope as the regional peak flow (RPF) for that breath.

Figure 9 schematically illustrates an example showing how to calculate at least one set of regional lung mechanics parameters for the at least one aerated region, based on the at least one RPF. The figure shows a number of regional peak flows (also denoted as Regional Qpeak), expressed in Az/sec, over decremental PEEP stages, expressed in cmbhO. Once a best RPF 91 has been determined, at a maximum level 92, overdistension can be assumed for higher pressure PEEP phases 93, and collapse can be assumed for lower pressure PEEP phases 94. The regional overdistension and the regional collapse may be expressed as percentages relative to the best RPF 91.

As an example, in Figure 9, at PEEP 10, a Qpeak of 50 may be determined as the maximum level 91 , thus the best RPF 91 , whereas at PEEP 14, a Qpeak of 30 may be determined. This value of 30 corresponds with a 40% loss of Qpeak relative to the maximum value of 50. Therefore, a value of 40% overdistension may be determined for this aerated region (i.e. pixel). For collapse, an example would be analogous but vice versa.

Figure 10 schematically illustrates an output of a parameter derived from the at least one set of regional lung mechanics parameters, in a format suitable for direct input into a spontaneously triggered mechanical ventilator. The derived parameter is global overdistension over collapse, expressed as a percentage. In the bottom graph 101 , global overdistension 102 and global collapse 103 are shown. These are set out over various PEEP pressure phases (expressed in cmH2O) Together with a series om images corresponding with the various PEEP pressure phases and showing how overdistension and collapse occur over the EIT-imaged thorax at each PEEP pressure phase through the use of colouring, an operator of the ventilator is able to configure the ventilator indirectly. If no machine-to-machine connection with the ventilator is possible or allowed, this is the most direct way of controlling the ventilator.

The operator may consult the graph to determine a suitable PEEP pressure phase, based on desired conditions. For example, the operator may desire to configure the ventilator based on an equilibrium between overdistension and collapse, i.e. the point where they cross 105. Alternatively, the operator may desire to configure the ventilator by setting a maximum of e.g. 5% collapse (and may accept the corresponding overdistension, even if that is slightly higher than at the equilibrium) and may select the PEEP pressure phase just below 5% collapse, so at point 104.

As used in this application and in the claims, the singular forms “a,” “an,” and “the” include the plural forms unless the context clearly dictates otherwise. The systems, apparatus, and methods described herein should not be construed as limiting in any way. Instead, the present disclosure is directed toward all novel and non-obvious features and aspects of the various disclosed embodiments, alone and in various combinations and sub-combinations with one another. The disclosed systems, methods, and apparatus are not limited to any specific aspect or feature or combinations thereof, nor do the disclosed systems, methods, and apparatus require that any one or more specific advantages be present or problems be solved. Any theories of operation are to facilitate explanation, but the disclosed systems, methods, and apparatus are not limited to such theories of operation.

Although the operations of some of the disclosed methods are described in a particular, sequential order for convenient presentation, it should be understood that this manner of description encompasses rearrangement, unless a particular ordering is required by specific language set forth below. For example, operations described sequentially may in some cases be rearranged or performed concurrently. Moreover, for the sake of simplicity, the attached figures may not show the various ways in which the disclosed systems, methods, and apparatus can be used in conjunction with other systems, methods, and apparatus. Additionally, the description sometimes uses terms like “obtaining” and “outputting” to describe the disclosed methods. These terms are high-level abstractions of the actual operations that are performed. The actual operations that correspond to these terms will vary depending on the particular implementation and are readily discernible by the skilled person.

It will be appreciated that for simplicity and clarity of illustration, where appropriate, reference numerals may have been repeated among the different figures to indicate corresponding or analogous elements. In addition, numerous specific details are set forth in order to provide a thorough understanding of the examples described herein. However, it will be understood by the skilled person that the examples described herein can be practiced without these specific details. In other instances, methods, procedures and components have not been described in detail so as not to obscure the related relevant feature being described. The drawings are not necessarily to scale and the proportions of certain parts may be exaggerated to better illustrate details and features. The description is not to be considered as limiting the scope of the examples described herein.

It will be apparent to the skilled person that substantial variations may be made in accordance with specific implementations. For example, customized hardware might also be used, and/or particular elements might be implemented in hardware, software (including portable software, such as applets, etc.), or both. Further, connection to other computing devices such as network input/output devices may be employed.

With reference to the appended figures, components that can include memory can include non-transitory machine-readable media. The terms “machine-readable storage medium” and “computer-readable storage medium” as used herein refer to any storage medium that participates in providing data that causes a machine to operate in a specific fashion. In embodiments provided hereinabove, various machine-readable storage media might be involved in providing instructions/code to processors and/or other device(s) for execution. Additionally or alternatively, the machine-readable storage media might be used to store and/or carry such instructions/code. In many implementations, a computer-readable storage medium is a physical and/or tangible storage medium. Such a medium may take many forms, including, but not limited to, non-volatile media, volatile media, and transmission media. Common forms of computer-readable storage media include, for example, magnetic and/or optical media, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a programmable read-only memory (PROM), an erasable programmable readonly memory (EPROM), a FLASH-EPROM, any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read instructions and/or code.

In some implementations, operations or processing may involve physical manipulation of physical quantities. Typically, although not necessarily, such quantities may take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, or otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to such signals as bits, data, values, elements, symbols, characters, terms, numbers, numerals, or the like. It should be understood, however, that all of these or similar terms are to be associated with appropriate physical quantities and are merely convenient labels. Unless specifically stated otherwise, as apparent from the discussion herein, it is appreciated that throughout this specification discussions utilizing terms such as “processing,” “computing,” “calculating,” “determining,” or the like refer to actions or processes of a specific apparatus, such as a special purpose computer, special purpose computing apparatus or a similar special purpose electronic computing device. In the context of this specification, therefore, a special purpose computer or a similar special purpose electronic computing device is capable of manipulating or transforming signals, typically represented as physical electronic or magnetic quantities within memories, registers, or other information storage devices, transmission devices, or display devices of the special purpose computer or similar special purpose electronic computing device.

Claims

1. A computer-implemented method for controlling spontaneously triggered mechanical ventilation of a patient, the method comprising:

- obtaining electrical impedance tomography, EIT, data recorded during a positive end- expiratory pressure, PEEP, trial imposed on the patient, wherein the EIT data represents a plurality of electrical impedances over a plurality of lung-related tissue regions of the patient over a duration of the PEEP trial;

- detecting at least one aerated region among the plurality of lung-related tissue regions, based on the obtained EIT data;

- determining at least one regional peak flow, RPF, corresponding with the at least one aerated region, based on the obtained EIT data;

- calculating at least one set of regional lung mechanics parameters for the at least one aerated region, based on the at least one RPF; and

- outputting the at least one set of regional lung mechanics parameters for the at least one aerated region or at least one parameter derived from the at least one set of regional lung mechanics parameters, in a format suitable for direct input into a spontaneously triggered mechanical ventilator.

2. The method of any previous claim, wherein the step of calculating at least one set of regional lung mechanics parameters for the at least one aerated region, based on the at least one RPF, comprises:

3. The method of any previous claim, comprising:

- filtering the obtained EIT data using a low-pass filter, preferably a Butterworth filter having a filter order of at least four, preferably having a cut-off frequency between an average human respiratory rate and an average human heart rate, more preferably having a cut-off frequency between 0.67 Hz and 1 Hz, most preferably having a cutoff frequency of approximately 0.83 Hz.

4. The method of any previous claim, wherein the step of detecting at least one aerated region among the plurality of lung-related tissue regions, based on the obtained EIT data, comprises:

- determining a maximum impedance of the tissue regions;

5. The method of any previous claim, wherein the at least one parameter derived from the at least one set of regional lung mechanics parameters is based on a weighted average of the overdistension parameters and a weighted average of the collapse parameters over all aerated regions among the at least one aerated region.

6. The method of any previous claim, comprising:

- detecting a number of breaths for the at least one aerated region, based on the obtained EIT data; wherein determining at least one RPF, for the at least one aerated region, comprises determining the at least one RPF for the or each breath for the at least one aerated region.

7. The method of any previous claim, wherein the number of breaths is detected for the at least one aerated region over descending pressure steps of the PEEP trial.

8. The method of any previous claim, wherein the step of determining at least one RPF, for the or each breath for the at least one aerated region, comprises:

9. The method of claim 8 when dependent on claim 7, further comprising:

- for the at least one aerated region, determining a statistical value, preferably the median, based on the maximum slopes for all breaths among the or each breath of said aerated region over each pressure step of the PEEP trial, and using the determined statistical value, preferably the median, as the RPF.

10. The method of any one of claims 8-9, wherein a slope of a breath is a first-order derivative based on at least three samples of a slope of said breath.

11. The method of any previous claim, wherein each set of regional lung parameters of the at least one set of regional lung parameters comprises an overdistension parameter and a collapse parameter for a corresponding aerated region of the at least one aerated region, wherein an overdistension of an aerated region relates to a measure of overinflation of lung tissue and wherein a collapse of an aerated region relates to a measure of underinflation of lung tissue.

12. The method of any previous claim, wherein direct input into the spontaneously triggered mechanical ventilator comprises:

13. A computer program comprising instructions configured for, when executed by at least one processor, causing the at least one processor to perform the steps of the method of any of the previous claims.

14. A data processing apparatus comprising at least one processor and at least one memory, the at least one memory storing the computer program of claim 13.

15. A system for controlling spontaneously triggered mechanical ventilation of a patient, the system comprising: - an electrical impedance tomography scanner;

- a patient ventilator; and

- a data processing apparatus according to claim 14.