Pleura strain and lung strain relevance judgment method based on spot tracking technology

Abstract

The invention discloses a pleural strain and lung strain relevance judgment method based on a spot tracking technology, which comprises the following steps: setting different levels of driving pressures, testing pleural longitudinal strain and tidal volume corresponding to each driving pressure, and calculating pleural longitudinal strain variation and tidal volume variation corresponding to each driving pressure; constructing a pulmonary alveolar deformation evaluation model, and determining the correlation between the pleural longitudinal strain variation and the tidal volume variation and the correlation between the pleural longitudinal strain variation and the driving pressure variation; according to the scheme, obvious correlation between the tidal volume and the driving pressure is determined based on tests, namely, the longitudinal stretching of the dirty pleura is positively correlated with the lung strain, the stress and strain of the lung tissue can be effectively reflected by measuring the longitudinal stretching degree (strain) of the pleura, and the longitudinal stretching degree (strain) is an ideal bedside index for monitoring the tension and volume change of the tissue in real time.

Description

Technical Field

[0001] This invention relates to the field of speckle tracking technology, and more specifically to a method for determining the correlation between pleural strain and lung strain based on speckle tracking technology. Background Technology

[0002] Acute respiratory distress syndrome (ARDS) is a common illness admitted to intensive care units (ICUs), accounting for 10.4% of ICU patients and 23.4%-27.1% of those requiring mechanical ventilation. In the United States, approximately 200,000 people are diagnosed with ARDS annually, resulting in 75,000 deaths, exceeding the mortality rates of breast cancer or HIV infection. The mortality rate for severe ARDS remains around 40%-50%. It also incurs enormous medical costs, ranging from $53,861 to $139,574. For patients who recover and are discharged, there is a prolonged period of income loss; the average income loss in the first year after discharge is approximately $30,199, and the average income loss over five years reaches as high as $193,903. Currently, there is no effective treatment; treatment primarily focuses on symptomatic and supportive care.

[0003] Low tidal volume ventilation strategies can effectively reduce ventilator-induced lung injury (VALI) and mortality in ARDS patients. The basis for improved prognosis lies in reducing volumetric injury caused by alveolar overinflation; however, there is currently no practical standard to measure the degree of alveolar expansion. Currently, driving pressure or transpulmonary pressure is most commonly used in clinical practice to guide tidal volume titration. However, the lungs of ARDS patients exhibit heterogeneity, with varying compliance in different areas. Therefore, driving pressure or transpulmonary pressure titrated based on the "whole lung" has different effects on different parts of the lung and may even cause upper lung overinflation, exacerbating damage. Therefore, there is an urgent need for a bedside monitoring technology that can accurately reflect the degree of local alveolar expansion. Summary of the Invention

[0004] The purpose of this invention is to provide a method for determining the correlation between pleural strain and lung strain based on speckle tracking technology, so as to solve the technical problem that there is a lack of bedside monitoring technology that can accurately reflect the degree of local alveolar expansion in the prior art.

[0005] To solve the above-mentioned technical problems, the present invention specifically provides the following technical solution: A method for determining the correlation between pleural strain and lung strain based on speckle tracking technology includes the following steps: Different levels of driving pressure were set, and the longitudinal strain and tidal volume of the pleura corresponding to each driving pressure were tested. The changes in longitudinal strain and tidal volume of the pleura corresponding to each driving pressure were calculated. An alveolar deformation assessment model was constructed to determine the correlation between changes in pleural longitudinal strain and tidal volume, as well as the correlation between changes in pleural longitudinal strain and driving pressure.

[0006] As a preferred embodiment of the present invention, the steps for testing the longitudinal strain of the pleura corresponding to each driving pressure are as follows: Determine the checkpoints for testing longitudinal strain of the pleura: the upper blue point, the lower blue point, and the diaphragm point; Ultrasound images were used to acquire ultrasound video of the pleural region: the linear array probe was placed at the upper blue point, lower blue point and diaphragm point respectively, with the linear array probe perpendicular to the two ribs. The gain and depth were adjusted to make the dynamic sliding of the pleural structure clearly visible. Specifically, at each checkpoint, dynamic pleural images are recorded for at least three consecutive complete respiratory cycles and stored. The tidal volume was collected in real time using a ventilator to monitor the pleural area using ultrasound video at each examination point.

[0007] As a preferred embodiment of the present invention, based on the ultrasound video of the pleural region corresponding to the upper blue dot, lower blue dot, and diaphragm point, the maximum longitudinal strain of the visceral pleura corresponding to the upper blue dot, lower blue dot, and diaphragm point is measured respectively. The specific implementation method is as follows: The ultrasound video of the pleural region is imported into image recognition software. The pleural region of interest is selected using the pleural hyperechoic line as the upper / lower boundary. The upper and lower boundaries of the pleural region of interest are adjusted so that the pleural region of interest can track the pleural spots and exhibit stable periodic movement with respiration. The pleural region of interest is analyzed and measured to identify spots in the pleural region of interest and to calculate the average value of the maximum longitudinal strain mPLS of the visceral pleura corresponding to the three layers of the pleural region of interest, forming a time-pleural strain curve similar to a respiratory waveform. The time-pleural strain curve is calibrated based on the respiratory cycle to mark a complete respiratory cycle on the time-pleural strain curve. The start and end points of the respiratory cycle are set as the first and second troughs of the time-pleural strain curve, respectively. The end of inspiration corresponds to the peak of the time-pleural strain curve, and the end of expiration corresponds to the trough of the time-pleural strain curve.

[0008] As a preferred embodiment of the present invention, the image recognition software automatically divides the pleural region of interest into three segments, each marked with a different color for easy distinction. The three segments are yellow, green, and blue, respectively. Yellow represents the left / 3rd segment of the visceral pleura.

[0009] Green represents the middle third of the visceral pleura.

[0010] Blue represents the right third of the visceral pleura.

[0011] The maximum longitudinal strain mPLS of the visceral pleura for each pair of spots in the pleural region of interest is specifically the average peak longitudinal strain, which is the average of the maximum contractile deformation peaks reached in the longitudinal direction on the left, middle and lateral sides of the pleural region of interest.

[0012] As a preferred embodiment of the present invention, the method for obtaining the maximum longitudinal strain of the pleura in the pleural region of interest based on the time-pleural strain curve is as follows: Based on speckle tracking of the pleura in the region of interest, the time-pleural strain curves for that segment are obtained. The vertical axis of the time-pleural strain curve represents the longitudinal strain value of the pleura, and the horizontal axis represents time. Find the most positive value on the time-pleural strain curve during each respiratory cycle; this value represents the peak longitudinal strain. The average peak longitudinal strain of the pleura is obtained by averaging the peak strain of each segment or all spots within the pleural region of interest.

[0013] As a preferred embodiment of the present invention, the method for identifying spots in the pleural region of interest is as follows: Using two-dimensional grayscale ultrasound sequences, each spot within the region of interest is automatically identified and tracked through autocorrelation and optimal pattern matching techniques. Among them, autocorrelation technology is used to match the spatial position of the same spot in different frames, and optimal pattern matching technology identifies a group of spots whose pixel grayscale features match the most. In this way, the spatial trajectory of the spot in each breathing cycle can be accurately tracked frame by frame.

[0014] As a preferred embodiment of the present invention Maximum longitudinal strain of the pleura = ( ) / ; in, The distance between the last spots during inhalation. The distance between the spots at the end of expiration.

[0015] As a preferred embodiment of the present invention, when the driving pressure is adjusted to 10cmH2O, the maximum longitudinal strain of the pleura corresponding to the driving pressure is calculated, and the tidal volume corresponding to the driving pressure is obtained. When the driving pressure is adjusted to 15 cmH2O, the maximum longitudinal strain of the pleura corresponding to the driving pressure is calculated, and the tidal volume corresponding to the driving pressure is obtained. When the driving pressure is adjusted to 20 cmH2O, the maximum longitudinal strain of the pleura corresponding to the driving pressure is calculated, and the tidal volume corresponding to the driving pressure is obtained. Calculate the maximum longitudinal strain change of the pleura ΔmPLS when the driving pressure is 15cmH2O and 20cmH2O, and the tidal volume change ΔVt when the driving pressure is 15cmH2O and 20cmH2O.

[0016] As a preferred embodiment of the present invention, when constructing the alveolar deformation assessment model, the maximum longitudinal strain of the visceral pleura obtained in the test corresponding to each driving pressure is automatically collected and recorded. Intragroup correlation coefficient analysis was performed on the measurement results to screen out data with high stability; The relationship between the change in maximum longitudinal strain of the visceral pleura ΔmPLS and the change in tidal volume ΔVt was calculated by regression analysis or correlation evaluation. The relationship between the change in maximum longitudinal strain ΔmPLS of the visceral pleura and the driving pressure ΔDP was calculated by regression analysis or correlation evaluation.

[0017] As a preferred embodiment of the present invention, the method for performing intragroup correlation coefficient analysis on the measurement results and screening out data with high stability is as follows: The maximum longitudinal strain of the visceral pleura at the upper blue point, lower blue point, and diaphragm point of normal healthy individuals was measured by different operators using different driving pressures corresponding to the volume-controlled ventilation mode. The maximum longitudinal strain of the visceral pleura at the upper blue point of mechanically ventilated patients was measured by different operators using different driving pressures corresponding to the volume-controlled ventilation mode. Calculate the intraclass correlation coefficient of the maximum longitudinal strain of the visceral pleura in normal healthy individuals within a 95% confidence interval, and the intraclass correlation coefficient of the maximum longitudinal strain of the visceral pleura in mechanically ventilated patients within a 95% confidence interval. Calculate the intergroup correlation coefficient of the maximum longitudinal strain of the visceral pleura in normal healthy individuals within a 95% confidence interval, and the intergroup correlation coefficient of the maximum longitudinal strain of the visceral pleura in mechanically ventilated patients within a 95% confidence interval. The consistency of quantitative calculation of longitudinal pleural strain based on speckle tracking technique was evaluated based on the intragroup correlation coefficients and intergroup correlation coefficients within the 95% confidence intervals for healthy individuals and mechanically ventilated patients. Calculate the maximum longitudinal strain of the visceral pleura corresponding to the consistency of longitudinal strain of the pleura in mechanically ventilated patients.

[0018] Compared with the prior art, the present invention has the following advantages: This invention is based on experimental findings that tidal volume and driving pressure are significantly correlated, that is, the longitudinal stretching of the visceral pleura is positively correlated with lung strain. Measuring the longitudinal stretching (strain) of the pleura can effectively reflect the stress and strain of lung tissue, and is a relatively ideal indicator for bedside real-time monitoring of tissue tension and volume changes. Therefore, by using speckle tracking technology to calculate the longitudinal strain value of the visceral pleura, the lung strain can be determined, enabling bedside monitoring, assessment and classification of lung strain. Attached Figure Description

[0019] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0020] Figure 1 A schematic diagram illustrating the measurement of longitudinal strain of the pleura using the speckle tracking technique provided in an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the changes and correlations of tidal volume and mPLS under different driving pressures, provided in an embodiment of the present invention. Figure 3 This figure shows the consistency test results of the maximum longitudinal strain of the pleura at different locations within and between operators, according to an embodiment of the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Ultrasonic two-dimensional speckle tracking technology is based on measuring the interaction between tissue and ultrasound beam to generate specific acoustic markers, called specks.

[0023] By using specialized software to track high-brightness specks frame by frame, the two-dimensional displacement of any point within a tissue can be determined in real time. Combined with time analysis, curves (strain curves) showing the distance changes between different monitoring specks are generated. Currently, this technology is mainly used to assess cardiac function. However, an increasing number of studies are using this technology to measure the strain of other organs or tissues to assess their function, such as the diaphragm, skeletal muscles, pleura, Achilles tendon, blood flow, and carpal tunnel. In other words, ultrasound speckle tracking technology was initially mainly used in cardiac ultrasound (such as evaluating left ventricular strain). Recently, it has gradually expanded to diaphragmatic function assessment and skeletal muscle biomechanical property analysis, but research on "longitudinal strain of the pleura" is still relatively limited.

[0024] This implementation uses speckle tracking technology to quantify the maximum longitudinal strain of the visceral pleura (mPLS, the degree of pleural stretching during respiration) to identify pneumothorax. Theoretically, pleural longitudinal strain can effectively reflect lung strain, so monitoring mPLS has important value in guiding the optimization of protective lung ventilation strategies for acute respiratory distress syndrome.

[0025] This invention provides a method for determining the correlation between pleural strain and lung strain based on speckle tracking technology, specifically including the following steps: Different driving pressures were set, and the longitudinal strain and tidal volume of the pleura corresponding to each driving pressure were tested. The changes in longitudinal strain and tidal volume of the pleura corresponding to each driving pressure were calculated. An alveolar deformation assessment model was constructed to determine the correlation between changes in pleural longitudinal strain and tidal volume, as well as the correlation between changes in pleural longitudinal strain and driving pressure.

[0026] For example, the maximum longitudinal strain and tidal volume of the visceral pleura corresponding to the upper blue point, lower blue point, and diaphragm point were measured in healthy volunteers at driving pressures of 10, 15, and 20 cmH2O, respectively. The maximum longitudinal strain and tidal volume of the visceral pleura corresponding to the upper blue point were measured in mechanically ventilated patients at driving pressures of 10, 15, and 20 cmH2O, respectively.

[0027] That is, when the driving pressure is adjusted to 10cmH2O, the maximum longitudinal strain of the pleura corresponding to the driving pressure is calculated, and the tidal volume corresponding to the driving pressure is obtained. When the driving pressure is adjusted to 15 cmH2O, the maximum longitudinal strain of the pleura corresponding to the driving pressure is calculated, and the tidal volume corresponding to the driving pressure is obtained. When the driving pressure is adjusted to 20 cmH2O, the maximum longitudinal strain of the pleura corresponding to the driving pressure is calculated, and the tidal volume corresponding to the driving pressure is obtained. Calculate the maximum longitudinal strain change of the pleura ΔmPLS when the driving pressure is 15cmH2O and 20cmH2O, and the tidal volume change ΔVt when the driving pressure is 15cmH2O and 20cmH2O.

[0028] The formula for calculating the change in tidal volume ΔVt is: ΔVt1 = (tidal volume when DP=15cmH2O - tidal volume when DP=10cmH2O), ΔVt2 = (tidal volume when DP=20cmH2O - tidal volume when DP=15cmH2O).

[0029] The formula for calculating the maximum longitudinal strain ΔmPLS of the visceral pleura is as follows: ΔmPLS1 is (maximum longitudinal strain of the visceral pleura when DP=15cmH2O - maximum longitudinal strain of the visceral pleura when DP=10cmH2O), and ΔmPLS2 is (maximum longitudinal strain of the visceral pleura when DP=20cmH2O - maximum longitudinal strain of the visceral pleura when DP=15cmH2O).

[0030] Among them, such as Figure 1 As shown, Figure 1 (A) shows a schematic diagram of speckle tracking technology for measuring longitudinal strain of the pleura. Longitudinal strain of the pleura = (spot spacing at the end of inspiration - spot spacing at the end of expiration) / spot spacing at the end of expiration x 100%. (B) shows the output interface of EchoPac software, which shows the time-pleura strain curve and the maximum strain.

[0031] The method for testing the longitudinal strain of the pleura corresponding to each driving pressure is as follows: Determine the checkpoints for testing longitudinal strain of the pleura: the upper blue point, the lower blue point, and the diaphragm point.

[0032] Ultrasound images were used to acquire ultrasound video of the pleural region: the linear array probe was placed at the upper blue point, lower blue point and diaphragm point respectively, with the linear array probe perpendicular to the two ribs. The gain and depth were adjusted to make the dynamic sliding of the pleural structure clearly visible.

[0033] Specifically, at each checkpoint, dynamic pleural images of at least three consecutive complete respiratory cycles are recorded and stored. Tidal volume corresponding to the acquisition of ultrasound video of the pleural area at each checkpoint is collected in real time using a ventilator.

[0034] The patient or a healthy individual is placed in a semi-recumbent position (head of bed elevated 30-45°). Using GE's Vivid7 and Vivid S6 ultrasound scanners, the linear array probe (Vivid S6 9LRS: 4.0-13.0 MHz; Vivid 7 10L: 4.0-11.0 MHz) is placed at the measurement point, perpendicular to two adjacent ribs. The image depth and gain are adjusted to make the pleural sliding clearly visible, and video of more than three complete respiratory cycles is recorded.

[0035] Export the video to the EchoPAC software workstation (version 113, GE, USA) for analysis. Use the apical dual-chamber echocardiography mode to select the pleural region of interest (ROI) and begin delineation. Place the upper boundary of the ROI on the pleural line. The width of the ROI can be selected as the default width or gradually moved up and down to obtain stable measurement results. Visually observing the ROI can effectively track the pleural "spots" that exhibit stable periodic motion with respiration. Begin analyzing and measuring the three parts of the ROI (yellow, blue, and green). A time-pleural strain curve similar to a respiratory waveform can be observed.

[0036] Set the start and end points of the respiratory cycle to the first and second troughs of the time-strain curve, respectively (for ultrasound machines with built-in respiratory waveforms, the start point of the respiratory cycle can be set with reference to the respiratory waveform). Adjust the analysis cursor (corresponding to the aortic valve closure time in cardiac speckle tracking) to the peak to obtain the maximum longitudinal strain mPLS of the visceral pleura in the three parts of the ROI (yellow, blue, and green).

[0037] The formula for calculating the maximum longitudinal strain mPLS of the visceral pleura is: pleural longitudinal strain = (spot spacing at the end of inspiration - spot spacing at the end of expiration) / spot spacing at the end of expiration x 100%.

[0038] Based on the ultrasound videos of the pleural regions corresponding to the upper blue dot, lower blue dot, and diaphragm point, the maximum longitudinal strain of the visceral pleura corresponding to the upper blue dot, lower blue dot, and diaphragm point was measured. The specific implementation method is as follows: Import the ultrasound video of the pleural region into the image recognition software, select the pleural region of interest with the pleural hyperechoic line as the upper / lower boundary, and adjust the upper and lower boundaries of the pleural region of interest so that the pleural region of interest can track the pleural spots to show a stable periodic movement with respiration. The pleural region of interest is analyzed and measured to identify spots in the pleural region of interest and to calculate the average value of the maximum longitudinal strain mPLS of the visceral pleura corresponding to the three layers of the pleural region of interest, forming a time-pleural strain curve similar to a respiratory waveform. The time-pleural strain curve is calibrated based on the respiratory cycle to mark a complete respiratory cycle on the time-pleural strain curve. The start and end points of the respiratory cycle are set as the first and second troughs of the time-pleural strain curve, respectively. The end of inspiration corresponds to the peak of the time-pleural strain curve, and the end of expiration corresponds to the trough of the time-pleural strain curve.

[0039] Among them, a speckle is a characteristic acoustic texture observed in echocardiographic grayscale images, formed within the visceral pleura due to the scattering and interference of ultrasound waves with different tissue structures. Each speckle is essentially a coherent scattering phenomenon caused by the combined action of many tiny scatterers (such as intercellular matrix structures). Specks possess spatial stability and can be considered as an "acoustic fingerprint" within the visceral pleura, migrating synchronously with the respiratory movements of the visceral pleura.

[0040] The method for identifying spots in the pleural region of interest is as follows: Using two-dimensional grayscale ultrasound sequences, each spot within the region of interest is automatically identified and tracked through autocorrelation and optimal pattern matching techniques. Among them, autocorrelation technology is used to match the spatial position of the same spot in different frames, and optimal pattern matching technology identifies a group of spots whose pixel grayscale features match the most. In this way, the spatial trajectory of the spot in each breathing cycle can be accurately tracked frame by frame.

[0041] At this point, the method based on the spot formation time-pleural strain curve is as follows: Spatial trajectory calculation: Tracking the actual displacement of the same visceral pleural spot in each frame.

[0042] Tissue length variation: The change in distance between spots between consecutive frames represents the “strain” of the visceral pleura in that region.

[0043] Maximum longitudinal strain of the pleura = ( ) / ; in, The distance between the last spots during inhalation. The distance between the spots at the end of expiration.

[0044] The time-pleural strain curve is used to record the dynamic change of "spot spacing" over time. The horizontal axis is "time" and the vertical axis is "strain value".

[0045] Among them, the key points of the time-pleural strain curve after combining it with the respiratory cycle include: the end of expiration (the lowest point / trough of the curve), at which point the parietal pleura (alveolar) is most retracted and the distance between the spots is shortest. This point is usually defined as the reference starting point. The end of inspiration (the highest point / peak of the curve), at which point the parietal pleura (alveolar) is most stretched (expanded) and the distance between the spots is largest. This is the maximum strain point.

[0046] The time-pleural strain curve reflects the periodic stretching and recoil of the parietal pleura during a complete respiratory cycle. The height difference between the peaks and troughs, i.e., the "maximum strain value," is exactly equal to the ratio of the difference between the spot distances at the end of inspiration and the end of expiration to the end-expiratory distance. Each trough to the next constitutes one standard respiratory cycle.

[0047] The changes in the spatial distance (or the overall ROI) of the spots at each time point (time axis) are converted into strain values, and a "time-pleural strain curve" is plotted. The curve can reflect in detail the dynamic characteristics of the deformation of the visceral pleura in each respiratory cycle, including the stretching and recoil phases.

[0048] The region of interest (ROI) refers to a specific visceral pleura region that is manually or automatically delineated for quantitative analysis in visceral pleural spot tracking analysis.

[0049] The image recognition software automatically divides the pleural region of interest into three layers, each marked with a different color for easy distinction: yellow, green, and blue. Yellow represents the inner visceral pleura, which is the layer closest to the alveoli.

[0050] Green represents the middle layer of the visceral pleura, which is located in the middle of the thickness of the visceral pleura.

[0051] Blue represents the outer visceral pleura, the layer closest to the chest wall.

[0052] The maximum longitudinal strain mPLS of the visceral pleura for each pair of spots in the pleural region of interest is specifically the average peak longitudinal strain, which is the average of the maximum contractile deformation peaks reached in the longitudinal direction by the inner, middle and outer layers of the pleural region of interest.

[0053] The method for obtaining the maximum longitudinal strain of each pleural layer in the pleural region of interest based on the time-pleural strain curve is as follows: Based on spot tracking of the coal seam pleura of the pleural region of interest, the time-pleural strain curves of the layer are obtained respectively. The vertical axis of the time-pleural strain curve is the longitudinal strain value of the pleura, and the horizontal axis is time. Find the most positive value on the time-pleural strain curve during each respiratory cycle; this value represents the peak longitudinal strain. The peak strain of each segment or all spots within the pleural region of interest is averaged to obtain the average peak longitudinal strain of the pleura, i.e., the maximum longitudinal strain of the visceral pleura in the pleural region of interest, mPLS, which is the average of the peak strains at all measuring points.

[0054] When constructing the alveolar deformation assessment model, the maximum longitudinal strain of the visceral pleura obtained from the test corresponding to each driving pressure is automatically collected and recorded. Intragroup correlation coefficient analysis was performed on the measurement results to screen out data with high stability; The intra-group and inter-group consistency correlation coefficients are the cornerstones of the overall technical feasibility. They are the gold standard in science for measuring the reliability of a measurement method, and their core purpose is to answer two fundamental questions: ① Is this measurement method stable? (Reproducibility) and ② Can different people obtain the same results using this method? (Reproducibility) If the answers to these two questions are no (i.e., low ICC values), then all data obtained based on this method, and all subsequent conclusions drawn (such as the correlation between mPLS and driving pressure), will be unreliable.

[0055] The method for performing within-group correlation coefficient analysis on the measurement results is as follows: The maximum longitudinal strain of the visceral pleura at the upper blue point, lower blue point, and diaphragm point of normal healthy individuals was measured by different operators using different driving pressures corresponding to the volume-controlled ventilation mode. The maximum longitudinal strain of the visceral pleura at the upper blue point of mechanically ventilated patients was measured by different operators using different driving pressures corresponding to the volume-controlled ventilation mode. Calculate the intraclass correlation coefficient of the maximum longitudinal strain of the visceral pleura in normal healthy individuals within a 95% confidence interval, and the intraclass correlation coefficient of the maximum longitudinal strain of the visceral pleura in mechanically ventilated patients within a 95% confidence interval. The consistency of quantitative calculation of longitudinal pleural strain based on speckle tracking technique was evaluated based on the intragroup correlation coefficients of normal healthy individuals and mechanically ventilated patients within the 95% confidence interval. Studies show that intra-operator and inter-operator ICC values ​​were good (0.52-0.97) for all examination sites, see details below. Figure 2 .

[0056] Among the healthy volunteers, the blue dots showed the following intra-operator ICC: Operator 1# had an intra-operator ICC of 0.97, 95% CI (0.93 to 0.99); Operator 2# had an intra-operator ICC of 0.78, 95% CI (0.57 to 0.90); and the inter-operator ICC between Operators 1# and 2# was 0.86, 95% CI (0.70 to 0.93).

[0057] Under the blue dot for healthy volunteers: the intra-operator ICC for Operator 1 was 0.75, 95% CI (0.45 to 0.89); the intra-operator ICC for Operator 2 was 0.59, 95% CI (0.57 to 0.82); and the inter-operator ICC between Operators 1 and 2 was 0.54, 95% CI (-0.03 to 0.80).

[0058] Diaphragmatic points in healthy volunteers: Intra-operator ICC for operator #1 was 0.67, 95% CI (0.38 to 0.84); intra-operator ICC for operator #2 was 0.52, 95% CI (-0.06 to 0.79); inter-operator ICC for operators #1 and #2 was 0.93, 95% CI (0.85 to 0.97).

[0059] Blue dots on mechanically ventilated patients: Intra-operator ICC for Operator 1# was 0.57, 95% CI (0.00 to 0.81); Intra-operator ICC for Operator 2# was 0.96, 95% CI (0.89 to 0.98); Inter-operator ICC for Operators 1# and 2# was 0.58, 95% CI (0.05 to 0.81).

[0060] Figure 2 This demonstrates the intra- and inter-operator consistency of speckle tracking technology in quantifying maximum longitudinal strain of the pleura in healthy volunteers and mechanically ventilated patients. Figure 2 (A) Mark blue dots for healthy volunteers; Figure 2 (B) Blue dots for healthy volunteers; Figure 2 (C) represents the diaphragm point of a healthy volunteer; Figure 2 (D) Blue dots are marked for mechanically ventilated patients.

[0061] Therefore, it is feasible to quantify the longitudinal stretch of the visceral pleura using speckle tracking technology, demonstrating good repeatability and consistency. The correlation analysis of the measurement results is performed as follows: The relationship between the change in maximum longitudinal strain of the visceral pleura ΔmPLS and the change in tidal volume ΔVt was calculated by regression analysis or correlation evaluation. The relationship between the change in maximum longitudinal strain ΔmPLS of the visceral pleura and the driving pressure ΔDP was calculated by regression analysis or correlation evaluation.

[0062] The strong correlation between the change in maximum longitudinal strain of the visceral pleura, ΔmPLS, and the change in tidal volume, ΔVt, is R. 2 =0.56 (P<0.0001); The driving pressure (cmH2O) at 10, 15 and 20 cmH2O corresponded to tidal volume, and ΔVt was the change in tidal volume. The differences were significant (all P < 0.0001).

[0063] The driving pressure (cmH2O) differed significantly among the maximum longitudinal strain mPLS of the visceral pleura at 10, 15 and 20 (all P < 0.0001).

[0064] Figure 3 The correlation between the change in maximum longitudinal strain of the visceral pleura ΔmPLS and the change in tidal volume ΔVt in (A) is P<0.0001.

[0065] Figure 3 (B) represents the tidal volume corresponding to the driving pressure (cmH2O) at 10, 15, and 20, respectively. ΔVt is the change in tidal volume, and DP is the driving pressure. The calculation formulas are (tidal volume at DP=15cmH2O - tidal volume at DP=10cmH2O) and (tidal volume at DP=20cmH2O - tidal volume at DP=15cmH2O).

[0066] Figure 3 (C) represents the maximum longitudinal strain mPLS of the visceral pleura when the driving pressure (cmH2O) is 10, 15, and 20, respectively.

[0067] Figure 3 (D) shows the scatter plots of ΔmPLS1 and ΔmPLS2. Note: mPLS is the maximum longitudinal strain of the pleura; ΔmPLS is the change in mPLS, including ΔmPLS1 (mPLS at DP=15cmH2O - mPLS at DP=10cmH2O) and ΔmPLS2 (mPLS at DP=20cmH2O - mPLS at DP=15cmH2O).

[0068] Therefore, using speckle tracking technology to quantify the longitudinal stretch of the visceral pleura shows a significant correlation with tidal volume and driving pressure, and the longitudinal stretch of the visceral pleura is positively correlated with lung strain. Measuring the degree of longitudinal stretch (strain) of the pleura can effectively reflect the stress and strain of lung tissue, and is a relatively ideal indicator for bedside real-time monitoring of tissue tension and volume changes.

[0069] Furthermore, based on the correspondence between tidal volume and lung strain, and the correlation between longitudinal strain of the visceral pleura and tidal volume, it was determined that longitudinal strain of the visceral pleura is positively correlated with lung strain. Therefore, the longitudinal strain value of the visceral pleura calculated by speckle tracking technology can determine the lung strain status, enabling bedside monitoring, assessment, and classification of lung strain.

[0070] The above embodiments are merely exemplary embodiments of this application and are not intended to limit this application. The scope of protection of this application is defined by the claims. Those skilled in the art can make various modifications or equivalent substitutions to this application within its substance and scope of protection, and such modifications or equivalent substitutions should also be considered to fall within the scope of protection of this application.

Claims

1. A method for determining the correlation between pleural strain and lung strain based on speckle tracking technology, characterized in that, Includes the following steps: Different levels of driving pressure were set, and the longitudinal strain and tidal volume of the pleura corresponding to each driving pressure were tested. The changes in longitudinal strain and tidal volume of the pleura corresponding to each driving pressure were calculated. An alveolar deformation assessment model was constructed to determine the correlation between changes in pleural longitudinal strain and tidal volume, as well as the correlation between changes in pleural longitudinal strain and driving pressure.

2. The method for determining the correlation between pleural strain and lung strain based on speckle tracking technology according to claim 1, characterized in that, The steps for testing the longitudinal strain of the pleura corresponding to each driving pressure are as follows: Determine the checkpoints for testing longitudinal strain of the pleura: the upper blue point, the lower blue point, and the diaphragm point; Ultrasound images were used to acquire ultrasound video of the pleural region: the linear array probe was placed at the upper blue point, lower blue point and diaphragm point respectively, with the linear array probe perpendicular to the two ribs. The gain and depth were adjusted to make the dynamic sliding of the pleural structure clearly visible. Specifically, at each checkpoint, dynamic pleural images are recorded for at least three consecutive complete respiratory cycles and stored. The tidal volume was collected in real time using a ventilator to monitor the pleural area using ultrasound video at each examination point.

3. The method for determining the correlation between pleural strain and lung strain based on speckle tracking technology according to claim 2, characterized in that, Based on the ultrasound videos of the pleural regions corresponding to the upper blue dot, lower blue dot, and diaphragm point, the maximum longitudinal strain of the visceral pleura corresponding to the upper blue dot, lower blue dot, and diaphragm point was measured. The specific implementation method is as follows: The ultrasound video of the pleural region is imported into image recognition software. The pleural region of interest is selected using the pleural hyperechoic line as the upper / lower boundary. The upper and lower boundaries of the pleural region of interest are adjusted so that the pleural region of interest can track the pleural spots and exhibit stable periodic movement with respiration. The pleural region of interest is analyzed and measured to identify spots in the pleural region of interest and to calculate the average value of the maximum longitudinal strain mPLS of the visceral pleura corresponding to the three layers of the pleural region of interest, forming a time-pleural strain curve similar to a respiratory waveform. The time-pleural strain curve is calibrated based on the respiratory cycle to mark a complete respiratory cycle on the time-pleural strain curve. The start and end points of the respiratory cycle are set as the first and second troughs of the time-pleural strain curve, respectively. The end of inspiration corresponds to the peak of the time-pleural strain curve, and the end of expiration corresponds to the trough of the time-pleural strain curve.

4. The method for determining the correlation between pleural strain and lung strain based on speckle tracking technology according to claim 3, characterized in that, The image recognition software automatically divides the pleural region of interest into three layers, each marked with a different color for easy distinction: yellow, green, and blue. Yellow represents the inner visceral pleura, which is the layer closest to the alveoli. Green represents the middle layer of the visceral pleura, which is located in the middle of the thickness of the visceral pleura; Blue represents the outer layer of the visceral pleura, the layer closest to the chest wall; The maximum longitudinal strain mPLS of the visceral pleura for each pair of spots in the pleural region of interest is specifically the average peak longitudinal strain, which is the average of the maximum contractile deformation peaks reached in the longitudinal direction by the inner, middle and outer layers of the pleural region of interest.

5. The method for determining the correlation between pleural strain and lung strain based on speckle tracking technology according to claim 4, characterized in that, The method for obtaining the maximum longitudinal strain of the pleura in the region of interest based on the time-pleural strain curve is as follows: Based on spot tracking of the coal seam pleura of the pleural region of interest, the time-pleural strain curves of the layer are obtained respectively. The vertical axis of the time-pleural strain curve is the longitudinal strain value of the pleura, and the horizontal axis is time. Find the most positive value on the time-pleural strain curve during each respiratory cycle; this value represents the peak longitudinal strain. The average peak longitudinal strain of the pleura is obtained by averaging the peak strain of each segment or all spots within the pleural region of interest.

6. The method for determining the correlation between pleural strain and lung strain based on speckle tracking technology according to claim 3, characterized in that, The method for identifying spots in the pleural region of interest is as follows: Using two-dimensional grayscale ultrasound sequences, each spot within the region of interest is automatically identified and tracked through autocorrelation and optimal pattern matching techniques. Among them, autocorrelation technology is used to match the spatial position of the same spot in different frames, and optimal pattern matching technology identifies a group of spots whose pixel grayscale features match the most. In this way, the spatial trajectory of the spot in each breathing cycle can be accurately tracked frame by frame.

7. The method for determining the correlation between pleural strain and lung strain based on speckle tracking technology according to claim 3, characterized in that, Maximum longitudinal strain of the pleura = ( ) / ; in, The distance between the last spots during inhalation. The distance between the spots at the end of expiration.

8. The method for determining the correlation between pleural strain and lung strain based on speckle tracking technology according to claim 3, characterized in that, When the driving pressure is adjusted to 10 cmH2O, the maximum longitudinal strain of the pleura corresponding to the driving pressure is calculated, and the tidal volume corresponding to the driving pressure is obtained. When the driving pressure is adjusted to 15 cmH2O, the maximum longitudinal strain of the pleura corresponding to the driving pressure is calculated, and the tidal volume corresponding to the driving pressure is obtained. When the driving pressure is adjusted to 20 cmH2O, the maximum longitudinal strain of the pleura corresponding to the driving pressure is calculated, and the tidal volume corresponding to the driving pressure is obtained. Calculate the maximum longitudinal strain change of the pleura ΔmPLS when the driving pressure is 15cmH2O and 20cmH2O, and the tidal volume change ΔVt when the driving pressure is 15cmH2O and 20cmH2O.

9. The method for determining the correlation between pleural strain and lung strain based on speckle tracking technology according to claim 1, characterized in that, When constructing the alveolar deformation assessment model, the maximum longitudinal strain of the visceral pleura obtained from the test corresponding to each driving pressure is automatically collected and recorded. Intragroup correlation coefficient analysis was performed on the measurement results to screen out data with high stability; The relationship between the change in maximum longitudinal strain of the visceral pleura ΔmPLS and the change in tidal volume ΔVt was calculated by regression analysis or correlation evaluation. The relationship between the change in maximum longitudinal strain ΔmPLS of the visceral pleura and the driving pressure ΔDP was calculated by regression analysis or correlation evaluation.

10. The method for determining the correlation between pleural strain and lung strain based on speckle tracking technology according to claim 1, characterized in that, The method for performing intragroup correlation coefficient analysis on the measurement results to screen out data with high stability is as follows: The maximum longitudinal strain of the visceral pleura at the upper blue point, lower blue point, and diaphragm point of normal healthy individuals was measured by different operators using different driving pressures corresponding to the volume-controlled ventilation mode. The maximum longitudinal strain of the visceral pleura at the upper blue point of mechanically ventilated patients was measured by different operators using different driving pressures corresponding to the volume-controlled ventilation mode. Calculate the intraclass correlation coefficient of the maximum longitudinal strain of the visceral pleura in normal healthy individuals within a 95% confidence interval, and the intraclass correlation coefficient of the maximum longitudinal strain of the visceral pleura in mechanically ventilated patients within a 95% confidence interval. Calculate the intergroup correlation coefficient of the maximum longitudinal strain of the visceral pleura in normal healthy individuals within a 95% confidence interval, and the intergroup correlation coefficient of the maximum longitudinal strain of the visceral pleura in mechanically ventilated patients within a 95% confidence interval. The consistency of quantitative calculation of longitudinal pleural strain based on speckle tracking technique was evaluated based on the intra-group correlation coefficients and inter-group correlation coefficients within the 95% confidence intervals for healthy individuals and mechanically ventilated patients.

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