Deep thrombus quantitative measurement method and device based on photoacoustic imaging technology

Abstract

The invention discloses a deep thrombus quantitative measurement method and device based on a photoacoustic imaging technology, signals of a deep thrombus lesion area and signals of adjacent blood vessels are directly measured in the same area, invasive detection is not needed, and the deep thrombus quantitative measurement method is a nondestructive detection method and is convenient for clinical use; according to the method, near blood vessel signals are used as endogenous calibration factors, so that measurement errors caused by direct measurement of a deep thrombus area due to a spectrum coloring effect can be effectively calibrated, and a more accurate quantitative measurement result is obtained; the light absorption property of the overlying tissue of the lesion area does not need to be considered, so that the detection process is simplified, the calculation complexity is reduced, and the method is simpler and easier to use; a reconstruction algorithm and a calibration method based on simple calculation are used, priori knowledge and complex simulation calculation of a tissue environment are not needed, calculation resources are saved, the method has the advantages of being simple and easy to use, the accurate light absorption spectrum of the lesion thrombus in the deep tissue can be rapidly obtained, and the method is suitable for large-scale popularization and application. Therefore, a valuable reference is provided for clinical diagnosis and judgment of thrombus.

Description

Technical Field

[0001] The present invention relates to a method and device for quantitatively measuring deep thrombosis based on photoacoustic imaging, belonging to a method for non-destructive pathological detection of living tissues using photoacoustic imaging methods. Background Art

[0002] Photoacoustic imaging is an emerging functional imaging modality that combines optical contrast and acoustic imaging depth. Due to the advantages of non-invasiveness, convenience, harmlessness, etc., photoacoustic imaging has been applied in early tumor research, blood oxygen saturation measurement, brain imaging, breast cancer, etc. Photoacoustic imaging is based on the photoacoustic effect that molecules absorb short laser pulses and emit thermoelastic acoustic waves. Compared with traditional ultrasonic imaging, it can monitor deep tissues with high optical contrast. The intensity of the reconstructed photoacoustic image is proportional to the product of the light absorption of the chromophore and the light flux reaching the detection area. If photoacoustic imaging is performed using multiple wavelengths, the absorption spectrum of the chromophore can be obtained. Since each molecule in biological tissue has a unique light absorption spectrum, tissues with different molecular compositions can be distinguished according to the light absorption characteristics. Therefore, photoacoustic imaging can be used as a competitive candidate index for thrombus formation classification.

[0003] Human blood tissue is a good absorber of laser energy. In photoacoustic imaging of deep human tissues, the signal intensity of blood is much higher than that of the background signal, so that the signal in the vascular region can be clearly distinguished and calculated. Therefore, it is a feasible way to diagnose deep vascular tissues in the human body through photoacoustic imaging technology.

[0004] However, before the excitation laser irradiates the target chromophore, it has to pass through multiple layers of tissues to perform multispectral imaging of deep tissues. The light absorption of biological tissues at different laser wavelengths shows significant spectral differences, which leads to wavelength-dependent attenuation of light energy, also known as "spectral coloring". On the other hand, due to differences in human body composition, such as differences in lipid thickness and skin pigmentation, layered tissue structures show differences in light attenuation and acoustic properties. Existing techniques for correcting "spectral coloring" require prior knowledge of tissue structure and other limitations, which often requires the guidance of another imaging modality. This first increases the complexity of the acquisition system. At the same time, the estimation of tissue light absorption properties requires complex calculations, which brings inconvenience to the further clinical application of deep imaging. Summary of the Invention

[0005] Objective of the Invention: To overcome the deficiencies in the prior art, the present invention provides a method and device for quantitatively measuring deep thrombus based on photoacoustic imaging. Multiple measurements are carried out at multiple wavelengths to obtain the light absorption coefficient of the target. First, the blood signal in the blood vessel close to the target in deep tissue is used to calculate the correction factor to reduce the influence of "spectral coloring" of the overlying tissue on deep measurement. Then, the accurate deep thrombus spectrum obtained after calculation is used to evaluate its lesion characteristics. Finally, the slope of the blood light absorption coefficient is evaluated by using first-order polynomial fitting to distinguish the thrombus stage.

[0006] Technical Solution: To achieve the above objective, the technical solution adopted by the present invention is as follows:

[0007] A method for quantitatively measuring deep thrombus based on photoacoustic imaging technology for non-destructive pathological detection of living tissues, comprising the following steps:

[0008] Step 1: Adjust the pulsed laser to align with the area to be detected of the sample to excite photoacoustic signals; move the ultrasonic probe to align with the area to be detected of the sample to collect photoacoustic signals.

[0009] Step 2: At the same laser wavelength of the pulsed laser, repeat signal collection for the same area to be detected; adjust the laser wavelength of the pulsed laser and repeat signal collection for the same area to be detected.

[0010] Step 3: For each signal collection at the same laser wavelength, reconstruct the collected photoacoustic signals to obtain a photoacoustic image, and use the threshold segmentation method to obtain the initial sound pressure of the blood vessel area in each photoacoustic image.

[0011] Step 4: For different laser wavelengths, repeat the photoacoustic signal reconstruction process and the threshold segmentation process in Step 3 to obtain the initial sound pressure of the blood vessel area at different laser wavelengths.

[0012] Step 5: Determine the suspicious lesion area and the adjacent reference area based on the initial sound pressure of the blood vessel area at different laser wavelengths; based on the initial sound pressure of the adjacent reference area, use the endogenous calibration method to calibrate the initial sound pressure of the suspicious lesion area to obtain the light absorption coefficient of the suspicious lesion area.

[0013] Step 6: Characterize the change in the chemical composition of the suspicious lesion area according to the light absorption coefficient of the suspicious lesion area to determine the thrombus stage.

[0014] Specifically, in Step 2, the repeated signal collection for the same area to be detected includes the following steps:

[0015] Step 21: Since biological macromolecules (in blood, biological macromolecules are mainly hemoglobin) have specific light absorption properties related to the wavelength of laser, set the measurement band of the pulsed laser to 700 - 850 nm, set the adjustment step of the laser wavelength (usually 10 nm), and set the number of repeated irradiations of the pulsed laser on the area to be detected at each laser wavelength (usually 30 times); this measurement band is set because: Hemoglobin in blood is mainly composed of oxyhemoglobin and deoxyhemoglobin, and these two components both have obvious, wavelength - varying, and different specific light absorption properties for laser. Within this measurement band, the specific light absorption properties of these two components are more obvious, and the penetration power of the laser is good (in the same tissue, the longer the laser wavelength, the stronger the penetration power of the laser, which is more conducive to deep - tissue imaging). The selection of this measurement band takes into account both the light absorption intensity of the tissue and the penetration power of the laser;

[0016] Step 22: Synchronously turn on the pulsed laser and the ultrasonic probe, and repeatedly collect photoacoustic signals at different laser wavelengths.

[0017] Specifically, in step 3, the method of threshold segmentation is used to screen the initial sound pressure of the blood vessel area, which includes the following steps:

[0018] Step 31: Within the measurement band, since blood has good light absorption properties, the sound pressure intensity of blood in the photoacoustic image is greater than that of other tissues (such as muscle tissue); reconstruct each collected photoacoustic signal into a photoacoustic image, regard each light mass in the photoacoustic image as a region to be analyzed, and set a threshold Record the maximum value of the sound pressure intensity of each region to be analyzed as A max , and regard the signals in this region to be analyzed with sound pressure intensity greater than as stronger signals, and obtain the stronger signals of each region to be analyzed;

[0019] Step 32: Based on the stronger signals of each region to be analyzed, perform region segmentation on the photoacoustic image, regard the regions where the stronger signals are distributed in each region to be analyzed as the blood vessel regions of the region to be segmented, and form more than one blood vessel region in the photoacoustic image; calculate the average sound pressure intensity of each blood vessel region respectively, and regard the average sound pressure intensity as the initial sound pressure of the corresponding blood vessel region; for the blood vessel region at the r position, the initial sound pressure calculated at the λ laser wavelength is denoted as p0(r, λ);

[0020] Step 33: According to the photoacoustic effect theory, it can be obtained that:

[0021] p0(r, λ) = K·Γ·A(r, λ)·I(r, λ)

[0022] Where: K represents a constant determined by the sensitivity and aperture of the ultrasonic probe, and for a determined detection system, K is a constant; Γ is the Grüneisen constant characterizing photo-thermal conversion, and in the human detection environment, Γ is considered a constant; A(r, λ) represents the light absorption coefficient at position r and laser wavelength λ, and I(r, λ) represents the light flux at position r and laser wavelength λ.

[0023] The light absorption coefficient can reflect the light absorption property (molecular composition property) of the corresponding blood vessel region, which can help diagnose the stage and state of thrombosis; however, in non-invasive photoacoustic imaging, the light absorption coefficient of the tissue covering the blood vessel cannot be directly measured. Existing technologies mostly obtain the prior knowledge of the tissue covering the blood vessel through other imaging methods (such as ultrasonic imaging), and then estimate the light absorption coefficient of the tissue covering the blood vessel to indirectly obtain the light absorption coefficient of the tissue. In the photoacoustic effect theory p0(r, λ) = K·Γ·A(r, λ)·I(r, λ), p0(r, λ) is a measurable quantity, K and Γ are constants, and I(r, λ) is an estimated quantity obtained based on prior knowledge. Existing technologies need to first estimate I(r, λ) to obtain A(r, λ).

[0024] The tissue covering the blood vessel between the blood vessel and the ultrasonic probe will perform specific light absorption on the laser, and the light flux I(r, λ) is a variable related to the optical properties of the tissue. In a complex tissue composed of skin, fat, muscle, etc., the estimation of the light flux I(r, λ) is very complex, resulting in a large error when using the initial sound pressure p0(r, λ) to estimate the light absorption coefficient A(r, λ) of the blood vessel region, and the computational complexity of correcting the error is also very large; therefore, it is necessary to design a method that does not require complex calculations and has a weak dependence on prior knowledge such as the optical properties of the tissue covering the blood vessel to weaken the influence of the light flux I(r, λ) on the estimation of the light absorption coefficient A(r, λ).

[0025] Specifically, in step 3, for each signal acquisition at the same laser wavelength, the delay-and-sum algorithm is used to reconstruct the photoacoustic signal collected each time to obtain a photoacoustic image; the delay-and-sum algorithm is selected because: the delay-and-sum algorithm has both good imaging quality and low computational complexity, and at the same time can reflect the true initial sound pressure distribution of the tissue region, is simple and easy to use and meets the requirements of quantitative measurement.

[0026] Specifically, in step 5, an endogenous calibration method is used to calibrate the initial sound pressure of the suspicious lesion area to obtain the light absorption coefficient of the suspicious lesion area, including the following steps:

[0027] Step 51: At the λ laser wavelength, set, select, or calculate the initial sound pressure of the normal vascular region, calculate the deviation degree of the initial sound pressure of each vascular region respectively, determine the vascular regions with deviation degree exceeding the threshold as suspicious lesion regions, and mark the adjacent normal vascular regions of the suspicious lesion regions as adjacent reference regions;

[0028] Step 52: If at the λ laser wavelength, the position of the suspicious lesion region is r t , then record the initial sound pressure of the suspicious lesion region as the optical absorption coefficient of the suspicious lesion region as the position of the corresponding adjacent reference region is r c , then record the initial sound pressure of the adjacent reference region as the optical absorption coefficient of the adjacent reference region as According to the photoacoustic effect theory, there is:

[0029]

[0030] Where: r represents the vascular region position, K represents a constant determined by the sensitivity and aperture of the ultrasonic probe, Γ is the Grüneisen constant characterizing the photothermal conversion, A(r, λ) represents the optical absorption coefficient at the position r and the λ laser wavelength, and I(r, λ) represents the optical flux at the position r and the λ laser wavelength;

[0031] Step 53: Based on the assumption that the "spectral coloring" degree of the laser energy at adjacent positions is consistent, when the suspicious lesion region and the corresponding adjacent reference region are close enough, then r t ≈r c , it is considered that the optical fluxes of the suspicious lesion region and the corresponding adjacent reference region are equal at the same laser wavelength, regardless of the optical properties of the tissue covering the blood vessels, that is Calculate the optical absorption coefficient A t (λ) of the suspicious lesion region using the ratio of the corresponding initial sound pressures:

[0032]

[0033] Where: A c (λ) is mainly related to the absorption of hemoglobin in normal blood vessels, and the optical absorption coefficient of hemoglobin has been measured in existing references and is generally stable in normal blood vessels and can be considered as a known quantity; A t (λ) is calculated with endogenous calibration using the optical absorption coefficient of the adjacent reference region, avoiding the influence of the calculation error of the optical flux on the optical absorption coefficient and improving the accuracy of the optical absorption coefficient;

[0034] Step 54: At the λ laser wavelength, for the optical absorption coefficient A of the suspicious lesion regions at the position r t in all photoacoustic imagest (λ) Perform statistical calculations to obtain an average value, and use this average value as r t Position, estimated value A of the optical absorption coefficient at the λ laser wavelength t (λ);

[0035] Step 55: Repeat steps 52 to 54 until the estimated values of the optical absorption coefficients of all suspicious lesion areas at the λ laser wavelength are obtained;

[0036] Step 56: For different laser wavelengths, repeat steps 51 to 55 until the estimated values of the optical absorption coefficients of all suspicious lesion areas at all laser wavelengths are obtained.

[0037] Specifically, in step 6, use a first-order polynomial to fit the optical absorption coefficient or the estimated value of the optical absorption coefficient of the suspicious lesion area, use the fitting result to characterize the change in the chemical composition of the suspicious lesion area, and determine the stage of the thrombus; The reason for choosing a first-order polynomial fitting is that: the first-order polynomial fitting shows the change in the overall trend of the spectrum, which is more intuitive, has good robustness to the noise components in the measurement, and is convenient for real-time diagnosis due to its low computational complexity.

[0038] Specifically, in step 6, for the same suspicious lesion area, perform curve fitting on the optical absorption coefficients or the estimated values of the optical absorption coefficients at all laser wavelengths to obtain the optical absorption curve of the suspicious lesion area, use a first-order polynomial to fit the optical absorption curve, use the fitting result to characterize the change in the chemical composition of the suspicious lesion area, and determine the stage of the thrombus.

[0039] A deep thrombus quantitative measurement device based on photoacoustic imaging technology for implementing the above method, including a photoacoustic image reconstruction module, a blood vessel region segmentation module, a suspicious lesion region and adjacent reference region identification module, an endogenous calibration module, and a thrombus analysis module;

[0040] The photoacoustic image reconstruction module is used to reconstruct the photoacoustic signal collected by the ultrasonic probe into a photoacoustic image;

[0041] The blood vessel region segmentation module is used to segment the blood vessel region in the photoacoustic image and calculate the initial sound pressure of the blood vessel region;

[0042] The suspicious lesion region and adjacent reference region identification module identifies the suspicious lesion region based on the initial sound pressure of the normal blood vessel region according to the deviation degree of the initial sound pressure of each blood vessel region, and marks the normal blood vessel region closest to the suspicious lesion region as the adjacent reference region;

[0043] The endogenous calibration module calculates the optical absorption coefficient of the suspicious lesion area using the ratio of the corresponding initial sound pressures Where: A tThe optical absorption coefficient of the suspicious lesion area at the λ laser wavelength is denoted as (λ), and A t (λ) represents the optical absorption coefficient of the adjacent reference area at the λ laser wavelength, denotes the initial sound pressure of the suspicious lesion area, denotes the initial sound pressure of the adjacent reference area;

[0044] Based on the optical absorption coefficient of the suspicious lesion area, the thrombus analysis module characterizes the change in the chemical composition of the suspicious lesion area and determines the stage of the thrombus.

[0045] Specifically, the vascular region segmentation module uses the method of threshold segmentation to segment out the vascular region.

[0046] Beneficial effects: The deep thrombus quantitative measurement method and device based on photoacoustic imaging technology provided by the present invention have the following advantages compared with the prior art: 1. The present invention directly measures the signals of the deep thrombus lesion area and the adjacent blood vessels in the same area without invasive detection, which is a non-destructive detection method and is convenient for clinical use; 2. The present invention uses the adjacent blood vessel signal as an endogenous calibration factor, which can effectively calibrate the measurement error caused by the direct measurement of the deep thrombus area due to the "spectral coloring" effect, and obtain a more accurate quantitative measurement result; 3. The present invention does not need to consider the light absorption properties of the overlying tissue of the lesion area, thereby simplifying the detection process and reducing the computational complexity, making the method simpler and easier to use; 4. The reconstruction algorithm and calibration method used in the present invention are both based on simple calculations, without prior knowledge of the tissue environment and complex simulation calculations, saving computational resources, having the characteristics of simplicity and easy use, and can quickly obtain the accurate optical absorption spectrum of the lesion thrombus in deep tissue, thus providing a valuable reference for clinical diagnosis to judge the stage of the thrombus. Description of the Drawings

[0047] Figure 1 is a schematic diagram of the system structure for implementing the method of the present invention; 1 is reference sample 1; 2 is target sample 2; 3 is a container;

[0048] Figure 2 is a physical diagram of the sample and the photoacoustic imaging image under multi-wavelength measurement based on the method of the present invention;

[0049] Figure 3 is a set of multi-spectral measurement and correction results;

[0050] Figure 4 is the multi-spectral measurement and correction results under the influence of real biological tissue phantoms of various different tissues;

[0051] Figure 5 is to calculate the multi-spectral correlation between the multi-spectral signals of the target area before and after correction and the sample multi-spectral without tissue influence using the Pearson correlation coefficient;

[0052] Figure 6 It is the change of the first-order linear fitting slope of the deep tissue multispectrum over time under continuous-time measurement. Specific implementation mode

[0053] The present invention will be specifically introduced below in conjunction with the accompanying drawings and specific embodiments.

[0054] A deep vein thrombosis quantitative measurement device based on photoacoustic imaging technology for realizing the above method, including a photoacoustic image reconstruction module, a blood vessel region segmentation module, a suspicious lesion region and adjacent reference region identification module, an endogenous calibration module and a thrombus analysis module; the photoacoustic image reconstruction module is used to reconstruct the photoacoustic signal collected by the ultrasonic probe into a photoacoustic image; the blood vessel region segmentation module is used to segment the blood vessel region in the photoacoustic image and calculate the initial sound pressure of the blood vessel region; the suspicious lesion region and adjacent reference region identification module, based on the initial sound pressure of the normal blood vessel region, identifies the suspicious lesion region according to the deviation degree of the initial sound pressure of each blood vessel region, and marks the normal blood vessel region closest to the suspicious lesion region as the adjacent reference region; the endogenous calibration module calculates the light absorption coefficient of the suspicious lesion region using the ratio of the corresponding initial sound pressures; the thrombus analysis module, based on the light absorption coefficient of the suspicious lesion region, characterizes the change of the chemical composition of the suspicious lesion region and determines the stage of the thrombus.

[0055] Using the above deep vein thrombosis quantitative measurement device based on photoacoustic imaging technology for non-destructive pathological detection of living tissues, including the following steps:

[0056] Step 1: System setup

[0057] Adjust the pulsed laser to align with the area to be detected of the sample for exciting the photoacoustic signal; move the ultrasonic probe to align with the area to be detected of the sample for collecting the photoacoustic signal.

[0058] Step 2: Repeated signal acquisition of the area to be detected

[0059] Under the same laser wavelength of the pulsed laser, repeated signal acquisition is performed on the same area to be detected; the laser wavelength of the pulsed laser is adjusted, and repeated signal acquisition is performed on the same area to be detected; including the following steps:

[0060] Step 21: Set the starting laser wavelength of the pulsed laser to 700 nm, the cut-off laser wavelength to 850 nm, and the step size to 10 nm. Set the number of repeated irradiations of the pulsed laser on the area to be detected at each laser wavelength to 30, so as to realize repeated signal acquisition on the same area to be detected under the same laser wavelength;

[0061] Step 22: Set the laser wavelength, synchronously turn on the pulsed laser and the ultrasonic probe, and repeatedly collect photoacoustic signals at different laser wavelengths.

[0062] Step 23: Adjust the laser wavelength, synchronously turn on the pulsed laser and the ultrasonic probe, and repeatedly collect photoacoustic signals at different laser wavelengths.

[0063] Step 3: Segment the blood vessel area and calculate the initial sound pressure of the blood vessel area

[0064] For each signal acquisition at the same laser wavelength, use the delay summation algorithm to reconstruct the collected photoacoustic signals to obtain a photoacoustic image, and use the threshold segmentation method to obtain the initial sound pressure of the blood vessel area in each photoacoustic image; it includes the following steps:

[0065] Step 31: Reconstruct the collected photoacoustic signals into a photoacoustic image, take each light cluster in the photoacoustic image as a region to be analyzed, and set a threshold Record the maximum value of the sound pressure intensity of each region to be analyzed as A max , and take the signals in the region to be analyzed with a sound pressure intensity greater than as stronger signals, and obtain the stronger signals of each region to be analyzed;

[0066] Step 32: Based on the stronger signals of each region to be analyzed, perform region segmentation on the photoacoustic image, take the region where the stronger signals are distributed in each region to be analyzed as the blood vessel area of the region to be segmented, and form more than one blood vessel area in the photoacoustic image; calculate the average sound pressure intensity of each blood vessel area respectively, and take the average sound pressure intensity as the initial sound pressure of the corresponding blood vessel area; for the blood vessel area at the r position, the initial sound pressure calculated at the λ laser wavelength is denoted as p0(r, λ);

[0067] Step 33: According to the photoacoustic effect theory, it is obtained that:

[0068] p0(r, λ) = K·Γ·A(r, λ)·I(r, λ)

[0069] Where: K represents a constant determined by the sensitivity and aperture of the ultrasonic probe; Γ is the Grüneisen constant characterizing the photo-thermal conversion; A(r, λ) represents the light absorption coefficient at the r position and the λ laser wavelength, and I(r, λ) represents the light flux at the r position and the λ laser wavelength.

[0070] Step 34: For different laser wavelengths, repeat the photoacoustic signal reconstruction process and the threshold segmentation process in Steps 31 to 33 to obtain the initial sound pressure of each blood vessel area.

[0071] Step 4: Calculate the light absorption coefficient of the suspicious lesion area

[0072] Determine a suspicious lesion area and an adjacent reference area based on the initial sound pressure of the blood vessel area; calibrate the initial sound pressure of the suspicious lesion area using an endogenous calibration method based on the initial sound pressure of the adjacent reference area to obtain the optical absorption coefficient of the suspicious lesion area; the method includes the following steps:

[0073] Step 41: At the λ laser wavelength, set, select, or calculate the initial sound pressure of the normal blood vessel area, calculate the deviation degree of the initial sound pressure of each blood vessel area respectively, determine the blood vessel area with the deviation degree exceeding the threshold as the suspicious lesion area, and mark the adjacent normal blood vessel area of the suspicious lesion area as the adjacent reference area;

[0074] Step 42: If at the λ laser wavelength, the position of the suspicious lesion area is r t , then record the initial sound pressure of the suspicious lesion area as The optical absorption coefficient of the suspicious lesion area is The position of the corresponding adjacent reference area is r c , then record the initial sound pressure of the adjacent reference area as The optical absorption coefficient of the adjacent reference area is According to the photoacoustic effect theory, there is:

[0075]

[0076]

[0077] Where: r represents the blood vessel area position, K represents a constant determined by the sensitivity and aperture of the ultrasonic probe, Γ is the Grüneisen constant characterizing the photothermal conversion, A(r, λ) represents the optical absorption coefficient at the r position and the λ laser wavelength, and I(r, λ) represents the light flux at the r position and the λ laser wavelength;

[0078] Step 43: Based on the assumption that the "spectral coloring" degree of the laser energy at adjacent positions is consistent, when the suspicious lesion area and the corresponding adjacent reference area are close enough, then r t ≈ r c , it is considered that the light fluxes of the suspicious lesion area and the corresponding adjacent reference area at the same laser wavelength are equal, regardless of the optical properties of the tissue covering the blood vessel, that is Calculate the optical absorption coefficient A of the suspicious lesion area using the ratio of the corresponding initial sound pressures t (λ):

[0079]

[0080] Where: A c (λ) is mainly related to the absorption of hemoglobin in normal blood vessels, and the optical absorption coefficient of hemoglobin has been measured in existing references and is generally stable in normal blood vessels and can be considered as a known quantity; At The calculation of (λ) is endogenously calibrated using the light absorption coefficient of the adjacent reference region, avoiding the influence of the calculation error of the light flux on the light absorption coefficient and improving the accuracy of the light absorption coefficient.

[0081] Step 44: At the λ laser wavelength, for the suspicious lesion region at position r in all photoacoustic images t the light absorption coefficient A t (λ) is statistically calculated to obtain the average value, and this average value is used as the light absorption coefficient estimate A t at position r and λ laser wavelength; t (λ);

[0082] Step 45: Repeat steps 42 - 44 until the light absorption coefficient estimates of all suspicious lesion regions at the λ laser wavelength are obtained;

[0083] Step 46: For different laser wavelengths, repeat steps 41 - 45 until the light absorption coefficient estimates of all suspicious lesion regions at all laser wavelengths are obtained.

[0084] Step 5: Thrombus analysis

[0085] Use a first - order polynomial to fit the light absorption coefficient estimates of the suspicious lesion regions, use the fitting result to characterize the change in the chemical composition of the suspicious lesion regions, and determine the stage of the thrombus.

[0086] The following further illustrates the present invention with specific embodiments.

[0087] Taking the imaging of a blood vessel phantom covered by different tissues as an example, as Figure 1 and Figure 2 (1) shows, a transparent hose filled with ex - vivo sheep blood and a transparent hose filled with black ink are placed on top of biological tissue, and different thicknesses and types of biological tissue are covered on the hoses; the reason for using black ink is that the blood oxygen content in normal large blood vessels in the body is almost stable, which provides a reference light absorption coefficient and a basis for the calibration of the lesion region. During long - term measurements, it is difficult to keep the blood samples in the in - vitro environment of the experiment stable. Black ink has a known light absorption coefficient, and this light absorption coefficient is stable over time, so it can be used as a substitute for the blood sample; in Figure 1 1 and 2 respectively represent two blood vessel phantoms (reference sample and target sample), and 3 represents the container; use a photoacoustic imaging acquisition system to perform photoacoustic imaging on the two blood vessel phantoms, apply an ultrasonic coupling agent on the surface of the biological tissue, press the ultrasonic probe tightly against the biological tissue covering the hose, collect photoacoustic signals at multiple wavelengths, and perform image reconstruction. The reconstruction results are as Figure 2As shown in the right-side group of figures, it can be seen that for the photoacoustic images acquired at different wavelengths, the relative intensities of the acoustic pressure in the image regions of the two vascular phantoms vary, which is caused by the difference in their light absorption properties. After segmenting and extracting the signals from the reconstructed signals, the positions of the suspicious lesion region and its adjacent reference region are denoted as r t and r o , and the initial acoustic pressure distributions at the two positions are respectively and According to the process, the accurate spectrum (i.e., the initial acoustic pressure) of the suspicious lesion region is calculated, as shown in Figure 3 . It can be seen that in Figure 3 (1), there are obvious differences between the uncorrected spectrum of the target tube (i.e., the target sample) and the corrected spectrum of the target tube in Figure 3 (2), which indicates that the imaging target of deep tissues will have a large measurement error due to the influence of the upper tissues during photoacoustic imaging at multiple wavelengths.

[0088] Since real human tissues are complex, in this case, a tissue sample composed of pig skin, fat, and muscle stacked layer by layer is used as the upper tissue to simulate the tissue spectral coloring effect, and the above process is repeated for deep measurement and correction, and the results are as shown in Figure 4 . In Figure 4, (a) and (b) respectively show the uncorrected original multispectral curves of the target tube and the reference tube (i.e., the reference sample) and the multispectral curves after correction using this method. The four curves in each figure represent the multispectral curves without the influence of the upper tissue, affected by the skin, affected by the skin and fat, and affected by the skin, fat, and muscle. Figure 4 (c) shows the multispectral curve of the target tube after correction using this method. In Figure 4 (a) and Figure 4 (b), there are significant differences between the curves measured under different tissues, while in Figure 4 (c), there is better consistency between the curves. The calibrated multispectral curves have a stronger correlation with the curves without tissue attenuation (the curves marked with black squares), which indicates that using this method in deep tissue imaging can weaken the influence of the upper tissue on the light flux and obtain quantitative measurement results that are independent of the upper tissue and reflect the true light absorption properties of the target.

[0089] To quantitatively describe the improvement in accuracy of the multispectral curves measured by this method compared to direct measurement without calibration, the calibration effect of deep quantitative imaging is quantitatively analyzed from the perspective of curve correlation. The Pearson correlation coefficient is a commonly used evaluation criterion for calculating the correlation between two curves. Figure 5The multi-spectral measurement results calculated using the Pearson correlation coefficient are presented. By performing cross-correlation calculations on the multi-spectral curves of the uncorrected and corrected deep target samples respectively with the multi-spectral curve of the sample not affected by tissue coloring, it can be seen that compared with directly measuring the multi-spectral curve, the corrected multi-spectral curve of the deep tissue is more in line with the reference spectrum, and the correlation coefficient with the spectrum not affected by tissue is significantly improved. This indicates that the proposed method for quantitative measurement of deep tissue can obtain the accurate absorption spectrum of deep tissue, thereby being able to accurately judge the light absorption information of deep tissue thrombosis and accurately diagnose the thrombosis condition.

[0090] Since after human thrombosis occurs, the area of blood aggregation at the lesion site will change with the aggregation time, it is necessary to study the time-varying characteristics of the thrombus model. Figure 6 The first-order linear fitting results of the corrected multi-spectral curves obtained from the continuous measurements of the measured samples at 24-hour intervals over six days are presented. It can be seen that as time increases, the first-order fitting slope of the multi-spectral curve gradually decreases monotonically, which to a certain extent reflects the change in the properties after thrombus formation and is helpful for the non-destructive detection and characterization of thrombus.

[0091] In summary, a method for quantitatively evaluating the deep tissue thrombus stage based on photoacoustic imaging technology. By using the vascular signal near the thrombus as a correction factor, this method reduces the "spectral coloring" effect of the overlying tissue. Phantom experiments verify the accuracy of this method. Through this method, deep light absorption results unaffected by tissue characteristics can be obtained. Compared with direct measurement, the average Pearson correlation coefficient is significantly improved and the standard deviation is reduced. The continuous measurements at 24-hour intervals describe the change in the blood spectrum, and the slope of the blood spectrum decreases monotonically, providing a diagnostic reference for the thrombus formation time and type. This method does not require prior knowledge of tissue structure or complex calculations, so it is very suitable for clinical use. It provides a non-invasive tool for accurately quantifying the thrombus formation stage and helps to optimize the treatment strategy.

[0092] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the above embodiments do not limit the present invention in any form. Any technical solutions obtained by using equivalent replacement or equivalent transformation fall within the protection scope of the present invention.

Claims

1. A method for quantitatively measuring deep thrombosis based on photoacoustic imaging technology, which is used for non-destructive pathological detection of living tissues, and is characterized in that: It includes the following steps: Step 1: Adjust the pulsed laser to align with the area to be detected on the sample for exciting photoacoustic signals; move the ultrasonic probe to align with the area to be detected on the sample for collecting photoacoustic signals. Step 2: At the same laser wavelength of the pulsed laser, perform repeated signal collection on the same area to be detected; adjust the laser wavelength of the pulsed laser and perform repeated signal collection on the same area to be detected. Step 3: For each signal collection at the same laser wavelength, reconstruct the collected photoacoustic signals to obtain a photoacoustic image, and use the threshold segmentation method to obtain the initial sound pressure of the blood vessel area in each photoacoustic image. Step 4: For different laser wavelengths, repeat the photoacoustic signal reconstruction process and the threshold segmentation process in Step 3 to obtain the initial sound pressure of the blood vessel area at different laser wavelengths. Step 5: Determine the suspicious lesion area and the adjacent reference area based on the initial sound pressure of the blood vessel area at different laser wavelengths; based on the initial sound pressure of the adjacent reference area, use the endogenous calibration method to calibrate the initial sound pressure of the suspicious lesion area to obtain the light absorption coefficient of the suspicious lesion area. Step 6: Characterize the change in the chemical composition of the suspicious lesion area according to the light absorption coefficient of the suspicious lesion area to determine the stage of the thrombus.

2. The deep thrombus quantitative measurement method based on photoacoustic imaging technology according to claim 1, wherein: In the said Step 2, the repeated signal collection on the same area to be detected includes the following steps: Step 21: Set the measurement band of the pulsed laser to 700 - 850 nm, set the adjustment step size of the laser wavelength, and set the number of repeated irradiations of the pulsed laser on the area to be detected at each laser wavelength. Step 22: Synchronously turn on the pulsed laser and the ultrasonic probe, and repeatedly collect photoacoustic signals at different laser wavelengths.

3. The deep vein thrombosis quantitative measurement method based on photoacoustic imaging technology according to claim 1, wherein: In the said Step 3, the method of using threshold segmentation to screen the initial sound pressure of the blood vessel area includes the following steps: Step 31: Reconstruct the photoacoustic signal collected each time into a photoacoustic image. Take each light cluster in the photoacoustic image as a region to be analyzed, and set a threshold Record the maximum value of the sound pressure intensity of each region to be analyzed as A max , and use the signals in the region to be analyzed with sound pressure intensity greater than as stronger signals, and obtain the stronger signals of each region to be analyzed; Step 32: Perform region segmentation on the photoacoustic image based on the stronger signals in each area to be analyzed, take the area where the stronger signals are distributed in each area to be analyzed as the blood vessel area of the area to be segmented, and form more than one blood vessel area in the photoacoustic image; calculate the average sound pressure intensity of each blood vessel area respectively, and take the average sound pressure intensity as the initial sound pressure of the corresponding blood vessel area; for the blood vessel area at the r position, the initial sound pressure calculated at the λ laser wavelength is denoted as p0(r, λ). Step 33: According to the photoacoustic effect theory, it is obtained that: p0(r, λ) = K·Γ·A(r, λ)·I(r, λ) Where: K represents the constant determined by the sensitivity and aperture of the ultrasonic probe; Γ is the Grüneisen constant characterizing the photo - thermal conversion; A(r, λ) represents the light absorption coefficient at the r position and the λ laser wavelength, and I(r, λ) represents the light flux at the r position and the λ laser wavelength.

4. The method for quantitatively measuring deep thrombosis based on photoacoustic imaging technology according to claim 1, characterized in that: In the said Step 3, for each signal collection at the same laser wavelength, use the delay - sum algorithm to reconstruct the collected photoacoustic signals to obtain a photoacoustic image.

5. The method for quantitatively measuring deep thrombosis based on photoacoustic imaging technology according to claim 1, characterized in that: In the said Step 5, using the endogenous calibration method to calibrate the initial sound pressure of the suspicious lesion area to obtain the light absorption coefficient of the suspicious lesion area includes the following steps: Step 51: At the λ laser wavelength, set, select, or calculate the initial acoustic pressure of the normal vascular region, calculate the deviation degree for the initial acoustic pressure of each vascular region respectively, determine the vascular regions with deviation degree exceeding the threshold as suspicious lesion regions, and mark the nearest normal vascular region of the suspicious lesion region as the adjacent reference region; Step 52: If the position of the suspicious lesion area is r at the λ laser wavelength t , then record the initial sound pressure of the suspicious lesion area as The optical absorption coefficient of the suspicious lesion area is The position of the corresponding adjacent reference area is r c , then record the initial sound pressure of the adjacent reference area as The optical absorption coefficient of the adjacent reference area is According to the photoacoustic effect theory, there is Where: r represents the position of the vascular region, K represents a constant determined by the sensitivity and aperture of the ultrasonic probe, Γ is the Grüneisen constant characterizing the photo-thermal conversion, A(r, λ) represents the light absorption coefficient at the position r and the λ laser wavelength, and I(r, λ) represents the light flux at the position r and the λ laser wavelength; Step 53: Calculate the light absorption coefficient of the suspicious lesion area using the ratio corresponding to the initial sound pressure 6. The method for quantitatively measuring deep thrombosis based on photoacoustic imaging technology according to claim 5, characterized in that: It further includes the following steps: Step 54: At the λ laser wavelength, for the light absorption coefficient A t at the suspicious lesion area at position r in all photoacoustic images t (λ), perform statistical calculations to obtain the average value, and use this average value as the estimated value of the light absorption coefficient A t (λ) at position r and at the λ laser wavelength; t (λ); Step 55: Repeat steps 52 - 54 until the estimated values of the light absorption coefficients of all suspicious lesion regions at the λ laser wavelength are obtained; Step 56: For different laser wavelengths, repeat steps 51 - 55 until the estimated values of the light absorption coefficients of all suspicious lesion regions at all laser wavelengths are obtained.

7. The method for quantitatively measuring deep thrombosis based on photoacoustic imaging technology according to claim 1 or 6, characterized in that: In the said step 6, use a first-order polynomial to fit the light absorption coefficient or the estimated value of the light absorption coefficient of the suspicious lesion region, use the fitting result to characterize the change in the chemical composition of the suspicious lesion region, and determine the period of the thrombus.

8. The method for quantitatively measuring deep thrombosis based on photoacoustic imaging technology according to claim 1 or 6, characterized in that: In the said step 6, for the same suspicious lesion region, perform curve fitting on the light absorption coefficients or the estimated values of the light absorption coefficients at all laser wavelengths to obtain the light absorption curve of the suspicious lesion region, use a first-order polynomial to fit the light absorption curve, use the fitting result to characterize the change in the chemical composition of the suspicious lesion region, and determine the period of the thrombus.

9. A deep thrombosis quantitative measurement device based on photoacoustic imaging technology, characterized in that: It includes a photoacoustic image reconstruction module, a vascular region segmentation module, a suspicious lesion region and adjacent reference region identification module, an endogenous calibration module, and a thrombus analysis module; The said photoacoustic image reconstruction module is used to reconstruct the photoacoustic signals collected by the ultrasonic probe into a photoacoustic image; The said vascular region segmentation module is used to segment the vascular regions in the photoacoustic image and calculate the initial acoustic pressure of the vascular regions; The said suspicious lesion region and adjacent reference region identification module, based on the initial acoustic pressure of the normal vascular region, identifies the suspicious lesion regions according to the deviation degree of the initial acoustic pressure of each vascular region, and marks the nearest normal vascular region to the suspicious lesion region as the adjacent reference region; The endogenous calibration module calculates the light absorption coefficient of the suspicious lesion area using the ratio of the corresponding initial sound pressure where: A t (λ) represents the light absorption coefficient of the suspicious lesion area at the λ laser wavelength, A t (λ) represents the light absorption coefficient of the adjacent reference area at the λ laser wavelength, represents the initial sound pressure of the suspicious lesion area, represents the initial sound pressure of the adjacent reference area; The said thrombus analysis module, based on the light absorption coefficient of the suspicious lesion region, characterizes the change in the chemical composition of the suspicious lesion region and determines the period of the thrombus.

10. The deep vein thrombosis quantitative measurement device based on photoacoustic imaging technology according to claim 9, wherein: The said vascular region segmentation module uses the method of threshold segmentation to screen and segment the vascular regions.

Images