A method, system and computer device for structural photoacoustic imaging of biological tissues

Abstract

This invention discloses a method, system, and computer device for structural photoacoustic imaging of biological tissues, relating to the field of biomedical photonics technology. The method includes: converting a Gaussian light spot emitted by a laser into a linear light spot using an optical fiber bundle; adjusting the position of the optical fiber bundle so that the illumination plane of the linear light spot and the receiving plane of the linear array sensor are coaxial and at the same height, irradiating the biological tissue, and acquiring the photoacoustic signal with maximized sensitivity after irradiation using the linear array sensor; processing the photoacoustic signal to obtain a structural photoacoustic image of the biological tissue. This invention integrates the linear light spot and the linear array sensor into a single unit, enabling the linear array sensor to acquire photoacoustic signals with maximized sensitivity, achieving high-resolution, high-contrast, and high-sensitivity tissue imaging.

Description

Technical Field

[0001] This invention relates to the field of biomedical photonics technology, and in particular to a method, system and computer device for structural photoacoustic imaging of biological tissues. Background Technology

[0002] Photoacoustic imaging is a novel, non-invasive functional imaging method that combines the high resolution of ultrasound imaging with the high contrast of optical imaging, while overcoming the depth limitations of traditional optical imaging. Therefore, it enables 3D quantitative analysis of biological tissues. It is a completely new bioimaging technology based on the photoacoustic effect. When biological tissue is irradiated with a pulsed laser, its absorbing groups absorb the laser energy, generating ultrasonic signals that are detected by an ultrasound detector. By scanning the imaging area, the structure and function of the biological tissue can be reconstructed. Due to its non-invasive nature and high resolution, photoacoustic imaging has significant application prospects in the biomedical field.

[0003] In the detection of vascular morphology, photoacoustic imaging can reconstruct the three-dimensional morphology of microvessels and accurately measure parameters such as vessel diameter and length, providing an effective means for the early diagnosis of vascular lesions. Simultaneously, it can also play an important role in the diagnosis and treatment of tumors. By performing photoacoustic imaging on tumors, information such as tumor morphology, size, location, and margins can be obtained, enabling tumor tracking, early diagnosis, and surgical navigation, providing strong support for medical and health care.

[0004] Furthermore, photoacoustic imaging can also be used for brain functional imaging, blood oxygen concentration detection, and quantitative physiological and metabolic parameter imaging. For example, photoacoustic imaging technology can be used to track cerebral hemodynamics and conduct brain functional imaging; it can simultaneously measure blood oxygenation and pulse rate to achieve blood oxygen concentration detection; and it can also achieve quantitative parameter imaging measurement during the physiological and metabolic processes of diseases, providing more accurate information. However, current photoacoustic technology mostly uses ring array probes for measurement. These probes suffer from noise interference during measurement, and their imaging algorithms are relatively complex, inflexible, and costly, all of which limit their widespread clinical application. Therefore, in-depth research on the application of linear array probes in photoacoustic technology is of profound significance for promoting the development and clinical application of photoacoustic technology. In photoacoustic imaging using linear array probes, the algorithm is simple and inexpensive, and the measurement accuracy is superior to that of ring array probes. In addition, linear array probes offer high flexibility, suitable for precise imaging of tissues of different shapes, locations, sizes, and depths, making them widely applicable. For functional imaging, various complex methods are currently required to reconstruct multiple parameters, such as functional oxygen saturation, tissue water concentration, and tissue elastic modulus. However, existing photoacoustic imaging techniques also have inherent limitations. For example, compared to CT scans, MRI examinations, and ultrasound imaging, the penetration depth of photoacoustic imaging is relatively limited, generally only reaching 4 to 5 centimeters of human tissue thickness, which undoubtedly restricts its application range. In addition, photoacoustic imaging is susceptible to interference from various factors such as poor illumination uniformity, uneven distribution of sound wave sources, and certain environmental noises, making it difficult to guarantee the quality of the generated images. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of the prior art by providing a method, system, and computer device for structural photoacoustic imaging of biological tissues. This solves the problem that photoacoustic imaging in the prior art is easily affected by various factors such as poor illumination uniformity, uneven distribution of sound wave sources, and certain environmental noise, which makes it difficult to guarantee the quality of the generated images.

[0006] This invention specifically provides the following technical solution: a method for structural photoacoustic imaging of biological tissues, comprising the following steps:

[0007] The Gaussian spot emitted by the laser is converted into a linear spot by using an optical fiber bundle.

[0008] The position of the fiber bundle is adjusted so that the irradiation plane of the linear light spot and the receiving plane of the linear array sensor are coaxial and at the same height. The biological tissue is then irradiated, and the photoacoustic signal with the maximum sensitivity after irradiation is collected by the linear array sensor.

[0009] The photoacoustic signal is processed to obtain a structural photoacoustic image of biological tissue;

[0010] The step of processing the photoacoustic signal to obtain a structural photoacoustic image of biological tissue includes the following steps:

[0011] The generation and propagation equations of photoacoustic signals in acoustic coupling media are described using Newton's equations of motion, continuity equation, and thermoelastic equation.

[0012] A mathematical model of multispectral photoacoustic elasticity is obtained through the generation and propagation equations of photoacoustic signals;

[0013] The minimum squared error of the experimentally measured photoacoustic signal data and the calculated photoacoustic signal data along the boundary biological tissue is calculated using Newton's iteration method in the mathematical model.

[0014] The optimal mathematical model is re-obtained using the least squares error as the reconstruction model, and the structured photoacoustic image is obtained through the reconstruction model.

[0015] Preferably, the equations describing the generation and propagation of photoacoustic signals in the acoustic coupling medium using Newton's equations of motion, continuity equation, and thermoelastic equation are specifically expressed as follows:

[0016]

[0017]

[0018]

[0019] Where V is the velocity of particles in the tissue, and C p It is the specific heat capacity of the tissue. It is the tissue density, t is time, v s is the ultrasonic velocity within the tissue, p and T are the ultrasonic pressure and tissue temperature, respectively. H is defined as... , This represents the absorbed light energy density, and I(t) is the laser illuminance.

[0020] Preferably, obtaining the mathematical model of multispectral photoacoustic elasticity through the generation and propagation equations of photoacoustic signals includes the following steps:

[0021] Combining Newton's equations of motion and the thermoelastic equation, we obtain the following equation:

[0022]

[0023] Define the elastic modulus coefficient K as The above equation can be rewritten as:

[0024]

[0025] For a homogeneous medium, its density is defined as... The above equation can be rewritten as:

[0026]

[0027] Performing a Fourier transform on the ultrasonic pressure yields:

[0028]

[0029] The final mathematical model equation is:

[0030]

[0031] In the above formula, It is angular frequency. It is the wave number. and It is the speed of light in the medium and the elastic modulus of the medium.

[0032] Preferably, processing the final mathematical model includes the following steps:

[0033] Based on the mathematical model of photoacoustic elasticity, let O = K0 / K, we obtain:

[0034]

[0035] in, It is the light energy flux density. It is the optical absorption coefficient of the tissue, obtained according to Beer's Law:

[0036]

[0037] in, It is the light energy flux density. It is the optical absorption coefficient of the tissue, which, according to Beer's Law, is obtained as follows:

[0038]

[0039] in, , These are the extinction coefficient of the i-th tissue and the concentration of the i-th chromophore, respectively. The chromophore concentration here includes parameters such as functional oxygen saturation and water concentration.

[0040] Preferably, the Beer Law equation is imported into the processed mathematical model, and the specific expression is as follows:

[0041]

[0042] Discretizing the above equation using the finite element method yields:

[0043]

[0044] The inverse solution of the forward equation of the multispectral photoacoustic elastic equation is defined by the finite element discretization formula as follows:

[0045]

[0046] in, The desired concentration of chromophores and the elastic modulus of the tissue are defined as follows: , The concentration of each chromophore. The elastic modulus of the tissue. For regularization parameters, p o The photoacoustic data obtained from the experiment, p c The generated photoacoustic data is used for calculation.

[0047] Preferably, the specific expressions for the experimentally measured photoacoustic signal data and the calculated photoacoustic signal data are as follows:

[0048]

[0049] in, p o The photoacoustic data obtained from the experiment, p c The generated photoacoustic data is used for calculation.

[0050] Preferably, when defining the inverse solution of the forward equation of the multispectral photoacoustic elastic equation using the finite element discretization formula, obtaining the Jacobian matrix in the inverse solution includes the following steps:

[0051] According to the equation Jacobian matrix related to various chromophores Defined as:

[0052]

[0053] In the above equation, L It refers to the number of chromophores within the tissue, while Written as:

[0054]

[0055] Obtained through mathematical modeling combined with photon diffusion equations and The photon diffusion equation is:

[0056]

[0057] Jacobian matrix of elastic modulus parameter Also defined as:

[0058]

[0059] The Jacobian matrix is ​​calculated based on the adjoint method.

[0060] Preferably, the calculation of the Jacobian matrix based on the adjoint method includes the following steps:

[0061] Define an M×N matrix Let the matrix The following relationship must be satisfied:

[0062]

[0063] In the above equation, the vector The boundary measurement nodes have unit values, while the nodes everywhere else have zero values;

[0064] Let the left side of the Jacobian matrix containing the elastic modulus parameter be multiplied by... ,get:

[0065]

[0066] The left side of the above equation produces a Jacobian matrix.

[0067] Preferably, the present invention further includes a structured photoacoustic imaging system for biological tissues, comprising:

[0068] A linear spot acquisition unit is used to convert the Gaussian spot emitted by the laser into a linear spot through an optical fiber bundle;

[0069] The photoacoustic signal acquisition module is used to adjust the position of the fiber bundle so that the irradiation plane of the linear light spot and the receiving plane of the linear array sensor are coaxial and at the same height, so as to irradiate biological tissue and acquire the photoacoustic signal with maximum sensitivity after irradiation through the linear array sensor.

[0070] An imaging unit is used to process the photoacoustic signals to obtain biological tissue;

[0071] The imaging unit specifically includes:

[0072] The photoacoustic wave processing module is used to describe the generation and propagation equations of photoacoustic signals in the acoustic coupling medium using Newton's equations of motion, continuity equation, and thermoelastic equation.

[0073] The initial mathematical model building module is used to obtain a mathematical model of multispectral photoacoustic elasticity through the generation and propagation equations of photoacoustic signals.

[0074] The photoacoustic data calculation module is used to calculate the minimum squared error along the boundary of the experimentally measured photoacoustic signal data and the calculated photoacoustic signal data in the mathematical model using Newton's iteration method.

[0075] The reconstruction model building module is used to re-obtain the optimal mathematical model through least squares error as the reconstruction model, and to obtain the structured photoacoustic image of biological tissue through the reconstruction model.

[0076] Preferably, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the structured photoacoustic imaging method.

[0077] Compared with the prior art, the present invention has the following significant advantages:

[0078] This invention adjusts the position of the fiber bundle to make the illumination plane of the linear light spot and the receiving plane of the linear array sensor coaxial at the same height, thus integrating the linear light spot and the linear array sensor into one unit. This maximizes the photoacoustic signal acquisition sensitivity of the linear array sensor, enabling high-resolution, high-contrast, and high-sensitivity tissue imaging. Simultaneously, it employs multispectral photoacoustic elastic equations to directly acquire the optical and acoustic information contained in the photoacoustic signal, including tissue morphology and elastic modulus characteristics, functional oxygen saturation, and physiological parameters such as water concentration. This approach has lower system acquisition requirements, and the accuracy and precision of the acquired data are greatly improved. Attached Figure Description

[0079] Figure 1 (a) is the structured photoacoustic imaging system provided by the present invention; (b) is the 128-channel acquisition system; (c) is the 3D scanning imaging method; (d) is the combination of linear optical fiber and linear array ultrasonic probe; (e) is the cross-sectional view of the light outlet; (f) is the key component diagram of the integrated coaxial design of the combination of linear optical fiber and linear array ultrasonic probe.

[0080] Figure 2 (a) Photograph of the experimental sample; (b) Two-dimensional structure diagram of the photoacoustic structure of the pencil lead; (c) Three-dimensional structure diagram of the photoacoustic structure of the pencil lead;

[0081] Figure 3The images are reconstructed using the photoacoustic elastography technology provided by this invention; wherein (a) is an image of a rectangular pig liver tissue (a1), (a2) is a distribution map of deoxyhemoglobin concentration in the photoacoustic imaging of the rectangular pig liver tissue (a2), and (a3) ​​is a distribution map of elastic modulus coefficient in the photoacoustic imaging of the rectangular pig liver tissue (a3); in (b) is an image of a triangular pig liver tissue (b1), (b2) is a distribution map of deoxyhemoglobin concentration in the photoacoustic imaging of the triangular pig liver tissue (b2), and (b3) is a distribution map of elastic modulus coefficient in the photoacoustic imaging of the triangular pig liver tissue (b3); wherein (c) is a map of the average deoxyhemoglobin concentration in the photoacoustic imaging of the two types of pig liver tissue (a1); and (d) is a map of the average elastic modulus coefficient in the photoacoustic imaging of the two types of pig liver tissue (a2). Detailed Implementation

[0082] 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, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0083] This invention proposes a method, system, and computer device for structural photoacoustic imaging of biological tissues, which can be operated handheld or connected to a mechanical platform for precise three-dimensional scanning. Figure 1 As shown in (a), the light source in this system consists of an Nd:YAG laser system and an optical parametric oscillator (OPO) system (PhotoSonus-1, PhotoSonus Inc., EKSPLA). The Nd:YAG laser system can output dual-pump wavelengths of 532 / 1064 nm, while the OPO crystal excited by the pump source can output a tunable spectrum of 680 nm to 2300 nm. Furthermore, the laser has a maximum output energy of 200 mJ, a maximum pulse repetition frequency of 20 Hz, and a pulse width of 3-5 ns. The laser beam is transmitted through a single optical fiber, ultimately forming a 1*28 mm linear spot with 128 fiber bundles evenly arranged. The optical fibers and probe are fixed on a lifting platform (uKSA200, Zolix), and three-dimensional imaging is achieved through multi-layer two-dimensional scanning. Figure 1 (d) Demonstrates the linear light spot and medical linear array ultrasound sensor fixed on a self-designed 3D-processed mold, which is ultimately fixed on a lifting platform, such as... Figure 1As shown in (c), the linear light spot is angled and ultimately coaxial with the detection plane of the array ultrasonic probe, ensuring maximum sensitivity of signal generation and reception. In the experiment, the probe and optical fiber are placed in a water tank. The generated photoacoustic signal is acquired by the probe and transmitted to a 128-channel acquisition system (128-channel DAQ, e.g., ...). Figure 1 (b) As shown, after amplification, filtering, and other processing, the data is finally stored in the computer system for further data processing. The structured photoacoustic image is reconstructed using the delay and sum beamformer method.

[0084] Embodiments of the present invention provide a structural photoacoustic imaging method for biological tissues, comprising the following steps:

[0085] Step S1: Convert the Gaussian spot emitted by the laser into a linear spot or an extremely narrow rectangular spot using an optical fiber bundle.

[0086] Step S2: Adjust the position of the fiber bundle so that the irradiation plane of the linear light spot and the receiving plane of the linear array sensor are coaxial and at the same height, then irradiate the biological tissue, and collect the photoacoustic signal with the maximum sensitivity after irradiation through the linear array sensor.

[0087] Step S3: Process the photoacoustic signal to obtain a structural photoacoustic image of the biological tissue.

[0088] The process of processing photoacoustic signals to obtain structural photoacoustic images of biological tissues includes the following steps:

[0089] Step S31: Describe the generation and propagation equations of photoacoustic waves (signals) in the acoustic coupling medium using Newton's equations of motion, continuity equation, and thermoelastic equation.

[0090] Specifically, a reconstruction model for the multispectral photoacoustic elastography algorithm is established, which mainly describes the generation and propagation equations of photoacoustic waves in the acoustic coupling medium using the basic Newtonian equations of motion (1), continuity equation (2), and thermoelastic equation (3).

[0091] (1)

[0092] (2)

[0093] (3)

[0094] In the above formula, V It is the velocity of particles in the tissue. C p It is the specific heat capacity of the tissue. It is tissue density. t It is time.v s It is the ultrasonic velocity in the tissue. p and T It refers to ultrasonic pressure and tissue temperature. H Defined as , This represents the absorbed light energy density. I(t) This refers to laser illuminance.

[0095] Step S32: Obtain a mathematical model of multispectral photoacoustic elasticity through the generation and propagation equations of photoacoustic waves (signals).

[0096] Specifically, combining equations (1) and (3), we can obtain equation (4):

[0097] (4)

[0098] We define the elastic modulus. K for Equation (4) can be rewritten as:

[0099] (5)

[0100] For a homogeneous medium, we assume its density is... Equation (5) can be rewritten as:

[0101] (6)

[0102] Performing a Fourier transform on the sound pressure level yields:

[0103] (7)

[0104] Equation (6) can be written as:

[0105] (8)

[0106] In the above formula, It is angular frequency. It is the wave number. and It is the speed of light in the medium and the elastic modulus of the medium. Equation (8) is the mathematical model of multispectral photoacoustic elasticity.

[0107] The final mathematical model is processed through the following steps:

[0108] According to the mathematical model of photoacoustic elasticity, i.e., equation (8), let O=K 0 / K ,get:

[0109] (9)

[0110] Considering Equation (9) can be written as follows.

[0111] (10)

[0112] In the above equation, It is the light energy flux density. It is the optical absorption coefficient of the tissue, which, according to Beer's law, is obtained as follows:

[0113] (11)

[0114] Step S33: Use Newton's iteration method to calculate the minimum squared error along the boundary of the experimentally measured photoacoustic (signal) data and the calculated photoacoustic (signal) data in the mathematical model.

[0115] Specifically, in the above equation, , They are the first i The extinction coefficient of each tissue and the first i The chromophore concentration, here including parameters such as functional oxygen saturation and water concentration. Substituting equation (11) into equation (10) yields:

[0116] (12)

[0117] Equation (12) is the forward equation for multispectral photoacoustic elastography. Equation (12) is discretized using the finite element method:

[0118] (13)

[0119] According to equation (13), the inverse solution of the forward equation of the multispectral photoacoustic elastic equation is defined as:

[0120] (14)

[0121] In the above formula, The concentration of chromophores and the elastic modulus of the tissue that we want to obtain are defined as follows: , The concentration of each chromophore. The elastic modulus of the tissue. For regularization parameters, and For the photoacoustic data obtained from experiments and generated by calculation:

[0122] (15)

[0123] Let be the Jacobian matrix, defined as ,in, and These are represented as Jacobian matrices related to the elastic modulus parameter and various chromophores, respectively.

[0124] According to the equation Jacobian matrix It can be defined as:

[0125] (16)

[0126] In the above equation, L It refers to the number of chromophores within the tissue, while It can be written as:

[0127] (17)

[0128] In equations (16) and (17) and The solution is obtained by combining equation (9) with the photon diffusion equation (18):

[0129] (18)

[0130] Meanwhile, the Jacobian matrix It can also be written as:

[0131] (19)

[0132] The Jacobian matrix described above can be calculated using the adjoint method.

[0133] We first define an M×N matrix. Then let the matrix The following relationship must be satisfied:

[0134] (20)

[0135] In the above equation, the vector The boundary measurement nodes are unit values, while the nodes everywhere else are zero values. Then multiply the left side of equation (19) by... ,get:

[0136] (twenty one)

[0137] It can be observed that the left side of equation (21) produces a Jacobian matrix.

[0138] Step S34: Obtain the optimal mathematical model again through least squares error as the reconstruction model, and obtain the structured photoacoustic image of biological tissue through the reconstruction model.

[0139] Therefore, in summary, for the numerical solution method of the developed photoacoustic elastic equation, we need to use the Newton iteration method to solve the forward equation (13) and the inverse equation (14) to minimize the minimum square error of the experimentally measured and calculated photoacoustic data along the boundary.

[0140] The above method can simultaneously obtain the elastic modulus, functional oxygen saturation, and water concentration. The reconstruction process requires four wavelengths. The functional oxygen saturation is obtained by the ratio of oxyhemoglobin (HbO2) to the sum of oxyhemoglobin (HbO2) and deoxyhemoglobin (Hb). To reconstruct these two parameters, a wavelength is usually selected at the isoabsorption point of around 800 nm. Therefore, this project uses multiple wavelengths of 795 nm, 800 nm, 950 nm, and 1064 nm to simultaneously obtain the elastic modulus, functional oxygen saturation parameters, and water concentration.

[0141] refer to Figure 1 The embodiments of this application also provide a structured photoacoustic imaging system for biological tissues, including: a linear light spot acquisition unit, a photoacoustic signal acquisition module, and an imaging unit.

[0142] The linear spot acquisition unit is used to convert the Gaussian spot emitted by the (multi-wavelength pulse) laser into a linear spot or an extremely narrow rectangular spot using an optical fiber bundle; the photoacoustic signal acquisition module (including a lifting platform and a fixing device) is used to adjust the position of the optical fiber bundle so that the irradiation plane of the linear spot and the receiving plane of the linear array sensor are coaxial and at the same height, so as to irradiate the biological tissue and collect the photoacoustic signal with maximized sensitivity after irradiation through the linear array sensor; the imaging unit is used to process the photoacoustic signal to obtain the structural photoacoustic image of the biological tissue.

[0143] The process of obtaining structural photoacoustic images of biological tissues includes: a photoacoustic wave processing module, a mathematical model initialization module, a photoacoustic data calculation module, and a reconstruction model construction module.

[0144] The photoacoustic wave processing module is used to describe the generation and propagation equations of photoacoustic waves in the acoustic coupling medium using Newton's equations of motion, continuity equation, and thermoelastic equation; the mathematical model initialization module is used to obtain a mathematical model of multispectral photoacoustic elasticity using Newton's equations of motion and thermoelastic equation; the photoacoustic data calculation module is used to calculate the minimum squared error along the boundary of the experimentally measured photoacoustic data and the calculated photoacoustic data in the mathematical model using Newton's iteration method; and the reconstruction model construction module is used to re-obtain the optimal mathematical model through the minimum squared error as the reconstruction model, and obtain the structured photoacoustic image through the reconstruction model.

[0145] Specifically, the lifting platform is used to connect the fixing device, which is used to fix the fiber bundle of the multi-wavelength pulsed laser and the linear array sensor.

[0146] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the structured photoacoustic imaging method.

[0147] Experimental procedure:

[0148] The system comprises a multi-wavelength pulsed laser, a high-precision lifting platform, an integrated linear spot-linear array sensor mounting device, a water tank, a multi-channel acquisition card, and a computer. The laser transmits light through a self-designed optical fiber, converting a Gaussian spot into a linear spot or an extremely narrow rectangular spot. The linear spot fiber bundle and the linear array sensor are integrated using a specially designed mounting device, allowing for handheld illumination and reception, or fixed on the lifting platform for 3D scanning. Adjusting the position of the fiber bundle on the mounting device ensures that the illumination plane of the linear spot and the receiving plane of the linear array sensor are coaxial and at the same height, enhancing the sensitivity of the received signal. For handheld operation, ultrasonic adhesive is used as the coupling agent, while for 3D platform scanning fixed on the lifting platform, water from the water tank is used as the coupling agent. The signal is transmitted from the linear array sensor to the multi-channel acquisition card, then filtered and amplified before being stored and displayed on the computer platform. This invention integrates a linear spot and a linear array sensor into a single unit, enabling high-resolution, high-contrast, and high-sensitivity tissue imaging. Furthermore, the algorithm can also be used to obtain various functional parameters of biological tissues, such as tissue elastic modulus, functional oxygen saturation parameters, and water concentration.

[0149] In this experiment, industrial agar powder and water were first mixed at a ratio of 1:50 and heated, then poured into a cylindrical mold. After solidification, five 2cm long, 0.5mm pencil leads were inserted. The sample was placed in a photoacoustic water bath, and 660nm wavelength light was used to cover the pencil lead area, combined with a lifting platform for three-dimensional scanning. The final imaging result is shown in the figure below. Figure 2 (a) is a picture of the actual sample. Figure 2 (b) shows the two-dimensional result of photoacoustic imaging. Figure 2 (c) shows the three-dimensional result of 250 sections stitched together with a section spacing of 0.08 mm. The result shows that the elastic modulus of the pencil lead is 40 ± 0.5 GPa. The above experimental methods and imaging techniques have high repeatability and accuracy in this field and are suitable for comprehensive samples.

[0150] Functional photoacoustic imaging technology based on a linear spot-line array clinical ultrasound sensor was used to verify the feasibility and effectiveness of the method in vitro. Photoacoustic imaging was performed on two pieces of porcine liver tissue with different shapes. Figure 3 As can be seen, our algorithm reconstructed the functional results of liver tissues of different shapes (triangular (b) and rectangular (a)) very well, with an average deoxyhemoglobin concentration of (245±2 μM) and an average elastic modulus of (2.55±0.01 GPa). The results for measuring the tissue physiological characteristics are highly consistent with those obtained by peer researchers using ultrasound elastography, as detailed in Table 1. (Comparison) Figure 2 The results of the elastic modulus of pencil lead and Figure 3 The elastic modulus results of pig liver show that the elastic modulus parameter of pencil lead is about 15 times that of pig liver tissue. This result verifies that the method of the present invention can be used to distinguish tissues with different acoustic properties and ultimately for disease diagnosis.

[0151] The findings of this invention demonstrate that functional photoacoustic imaging technology possesses highly efficient tissue imaging capabilities, providing strong support for clinical medical diagnosis and treatment. Furthermore, the experimental process of this technology is relatively simple and easy to operate, offering inventors a wider range of experimental methods. It is worth noting that although the chicken breast and pig liver tissues used in this invention are only relatively simple models, their imaging results are sufficient to illustrate the superiority of this technology. It is hoped that this invention can provide other inventors with valuable ideas and experimental references.

[0152] Table 1. Reconstruction of different samples using ultrasonic elastography

[0153]

[0154] The above description, in conjunction with specific preferred embodiments, provides a more detailed explanation of the present invention. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such deductions or substitutions should be considered to fall within the scope of protection of the present invention.

Claims

1. A method for structural photoacoustic imaging of biological tissues, characterized in that, Includes the following steps: The Gaussian spot emitted by the laser is converted into a linear spot by using an optical fiber bundle; The position of the fiber bundle is adjusted so that the irradiation plane of the linear light spot and the receiving plane of the linear array sensor are coaxial and at the same height. The biological tissue is then irradiated, and the photoacoustic signal with the maximum sensitivity after irradiation is collected by the linear array sensor. The photoacoustic signal is processed to obtain a structural photoacoustic image of biological tissue; The process of processing the photoacoustic signal to obtain a structural photoacoustic image of biological tissue includes the following steps: The generation and propagation equations of photoacoustic signals in acoustic coupling media are described using Newton's equations of motion, continuity equation, and thermoelastic equation. A mathematical model of multispectral photoacoustic elasticity is obtained through the generation and propagation equations of photoacoustic signals; The least square error along the boundary of the experimentally measured photoacoustic signal data and the calculated photoacoustic signal data in the mathematical model is calculated using Newton's iteration method. The optimal mathematical model is re-obtained through the least squares error as a reconstruction model, and the structural photoacoustic image of biological tissue is obtained through the reconstruction model. The equations describing the generation and propagation of photoacoustic signals in the acoustic coupling medium, using Newton's equations of motion, continuity equation, and thermoelastic equation, are specifically expressed as follows: Where V is the velocity of particles in the tissue, and C p It is the specific heat capacity of the tissue. It is the tissue density, t is time, v s The ultrasonic velocity is the velocity within the tissue, p and T are the ultrasonic pressure and tissue temperature, and H is defined as... , I(t) represents the absorbed light energy density, and I(t) represents the laser illuminance. The mathematical model for obtaining multispectral photoacoustic elasticity through the generation and propagation equations of photoacoustic signals includes the following steps: Combining Newton's equations of motion and the thermoelastic equation, we obtain the following equation: Define the elastic modulus coefficient K as The above equation can be rewritten as: For a homogeneous medium, its density is defined as... The above equation can be rewritten as: Performing a Fourier transform on the ultrasonic pressure yields: The final mathematical model equation is: In the above formula, It is angular frequency. It is the wave number. and It is the speed of light in the medium and the elastic modulus of the medium.

2. The structural photoacoustic imaging method for biological tissues as described in claim 1, characterized in that, Processing the final mathematical model includes the following steps: Based on the mathematical model of photoacoustic elasticity, let O = K0 / K, we obtain: Considering The processed mathematical model is as follows: in, It is the light energy flux density. It is the optical absorption coefficient of the tissue, which, according to Beer's Law, is obtained as follows: in, , These are the extinction coefficient of the i-th tissue and the concentration of the i-th chromophore, respectively. The chromophore concentration includes the functional oxygen saturation and water concentration parameters.

3. The structural photoacoustic imaging method for biological tissues as described in claim 2, characterized in that, The Beer Law equation is imported into the processed mathematical model, and the specific expression is: Discretizing the above equation using the finite element method yields: The inverse solution of the forward equation of the multispectral photoacoustic elastic equation is defined by the finite element discretization formula as follows: in, The desired concentration of chromophores and the elastic modulus of the tissue are defined as follows: , The concentration of each chromophore. The elastic modulus of the tissue. For regularization parameters, p o The photoacoustic data obtained from the experiment, p c The generated photoacoustic data is used for calculation.

4. The structural photoacoustic imaging method for biological tissues as described in claim 3, characterized in that, The specific expressions for the photoacoustic signal data measured in the experiment and the photoacoustic signal data generated by calculation are as follows: in, p o The photoacoustic data obtained from the experiment, p c The generated photoacoustic data is used for calculation.

5. The structural photoacoustic imaging method for biological tissues as described in claim 3, characterized in that, When defining the inverse solution of the forward equation of the multispectral photoacoustic elastic equation using the finite element discretization formula, obtaining the Jacobian matrix in the inverse solution includes the following steps: According to the equation Jacobian matrix related to various chromophores Defined as: In the above equation, L It refers to the number of chromophores within the tissue, while Written as: Obtained through mathematical modeling combined with photon diffusion equations and The photon diffusion equation is: Jacobian matrix of elastic modulus parameter Also defined as: The Jacobian matrix is ​​calculated based on the adjoint method.

6. The structural photoacoustic imaging method for biological tissues as described in claim 5, characterized in that, The calculation of the Jacobian matrix based on the adjoint method includes the following steps: Define an M×N matrix Let the matrix The following relationship must be satisfied: In the above equation, the vector The boundary measurement nodes have unit values, while the nodes everywhere else have zero values; Let the left side of the Jacobian matrix containing the elastic modulus parameter be multiplied by... ,get: The left side of the above equation produces a Jacobian matrix.

7. A system for structural photoacoustic imaging of biological tissues as described in any one of claims 1-6, characterized in that, include: A linear spot acquisition unit is used to convert the Gaussian spot emitted by the laser into a linear spot through an optical fiber bundle; The photoacoustic signal acquisition module is used to adjust the position of the fiber bundle so that the irradiation plane of the linear light spot and the receiving plane of the linear array sensor are coaxial and at the same height, so as to irradiate biological tissue and acquire the photoacoustic signal with maximum sensitivity after irradiation through the linear array sensor. An imaging unit is used to process the photoacoustic signal to obtain a structural photoacoustic image of biological tissue; The imaging unit specifically includes: The photoacoustic wave processing module is used to describe the generation and propagation equations of photoacoustic signals in the acoustic coupling medium using Newton's equations of motion, continuity equation, and thermoelastic equation. The initial mathematical model building module is used to obtain a mathematical model of multispectral photoacoustic elasticity through the generation and propagation equations of photoacoustic signals. The photoacoustic data calculation module is used to calculate the minimum squared error along the boundary of the experimentally measured photoacoustic signal data and the calculated photoacoustic signal data in the mathematical model using Newton's iteration method. The reconstruction model building module is used to re-obtain the optimal mathematical model through least squares error as the reconstruction model, and to obtain the structured photoacoustic image of biological tissue through the reconstruction model.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, and when executed by the processor, the computer program causes the processor to perform the steps of the structured photoacoustic imaging method as described in any one of claims 1 to 6.

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