Handheld opto-acoustic multi-mode vascular puncture and tissue damage diagnosis system and device

Abstract

The invention provides a handheld photoacoustic multi-mode vascular puncture and tissue damage diagnosis system and device, and belongs to the technical field of photoacoustic imaging. According to the handheld multispectral photoacoustic imaging device, elastic force feedback and blood vessel real-time development are integrated, and the puncture success rate is increased by 30%; by virtue of hemoglobin / collagen double-index imaging, the stress injury can be pre-warned 72 hours in advance; the 3D hematoma volume automatically calculates an error lt; and repeated puncture and missed diagnosis are remarkably reduced. The invention provides a quantitative evaluation and real-time navigation integrated scheme for vascular puncture and tissue damage, and is safe and efficient.

Description

Technical Field

[0001] The present invention belongs to the field of photoacoustic imaging technology, and in particular relates to a handheld photoacoustic multimodal blood vessel puncture and tissue damage diagnosis system and device. Background Art

[0002] In clinical nursing and emergency treatment, venipuncture is one of the most common yet most experience-dependent invasive procedures. Existing technologies primarily rely on nurses' visual observation, palpation, or the use of traditional transmissive venography devices. However, due to limitations such as skin pigmentation, hair, subcutaneous fat thickness, and ambient light interference, the venous visualization at the puncture site is often unclear, resulting in a low first-time puncture success rate. Repeated punctures not only increase patient pain but may also cause complications such as phlebitis, hematoma, and nerve damage. The problem of "repeated venipuncture failures" is particularly prominent in pediatric, obese, elderly, and hypovolemic patients, and has become a key bottleneck affecting medical efficiency and patient satisfaction.

[0003] Pressure injuries (pressure ulcers) and subcutaneous congestion are common complications for patients who are bedridden for extended periods, undergo postoperative immobilization, or require anticoagulation. Currently, clinical risk assessment relies on regular inspection or palpation by nurses. However, early manifestations of pressure injuries are limited to localized congestion or occult ischemia, making them difficult to detect with the naked eye. Subcutaneous congestion, due to the spread of the hematoma to deeper layers, often extends beyond the visible area of ​​the body, leading to the dilemma of "difficulty in early detection and inaccurate assessment of the extent of the injury." While traditional ultrasound can assist in diagnosis, it relies on specialized operators, and the bulky equipment makes continuous bedside monitoring difficult.

[0004] Photoacoustic imaging (PAI) utilizes the physical mechanism of "light excitation and acoustic detection" to simultaneously acquire multi-parameter images such as hemoglobin concentration, oxygen saturation, and lipid content, offering the advantages of high optical contrast and deep acoustic penetration. In recent years, multispectral photoacoustic imaging (MSPAI) has achieved quantitative analysis of vascular networks, blood oxygen distribution, and tissue composition by projecting multi-wavelength pulsed lasers in time-sharing or parallel fashion. Theoretically, it can provide real-time three-dimensional positioning of blood vessels for venipuncture and early functional warnings for pressure injuries and subcutaneous congestion. However, existing photoacoustic systems are mostly desktop or cart-based, bulky, with complex optical fibers and high costs, making it difficult to meet the urgent clinical demand for "handheld, bedside, and immediate" capabilities.

[0005] The paper (Liu Qiang, Jin Tian, ​​Chen Qian, Xi Lei. Research Progress of Miniaturized Photoacoustic Imaging Technology in Biomedical Field[J]. Chinese Journal of Lasers, 2020, 47(2): 0207019.) discloses a handheld multispectral photoacoustic imaging technology that can be used for vascular imaging in clinical practice. It can distinguish blood vessels with a diameter as small as 100 microns and a depth of less than 1 centimeter and provide hemoglobin oxygen saturation and pulsation information. However, this technology can only achieve static imaging and cannot be used to assess tissue damage. Therefore, the relevant technology needs to be further improved. Summary of the Invention

[0006] In view of the problems existing in the prior art, the purpose of the present invention is to provide a handheld photoacoustic multimodal vascular puncture and tissue damage diagnosis system and device.

[0007] The present invention provides a photoacoustic guided puncture system, comprising: The laser excitation module is configured to emit 532 nm laser pulses to enhance blood vessel boundaries; The photoacoustic detection module is configured to receive the photoacoustic signal generated by the biological tissue and reconstruct the blood vessel boundary enhanced image based on the photoacoustic signal; an image processing module configured to obtain blood vessel contour information and a current puncture depth based on the blood vessel boundary enhanced image; an elasticity decision module configured to obtain tissue elasticity information in real time, combine the vascular contour information and current puncture depth output by the image processing module with the vascular stability index, and output an elasticity feedback decision, including the optimal puncture angle and vibration intensity, under a dynamic elastic navigation model and a virtual force feedback model; The human-computer interaction module is configured to display the blood vessel boundary enhanced image, the optimal puncture angle and the vibration intensity in real time and perform the blood vessel puncture operation.

[0008] Furthermore, the optimal puncture angle is calculated as follows: in, represents the dynamic elastic modulus of the vascular wall, , P Indicates blood pressure in blood vessels, r represents the vessel radius,h Indicates the wall thickness, Express the viscosity coefficient: 0.12Pa·s; Represents the blood vessel depth distribution map.

[0009] Furthermore, the elastic feedback is divided into level 1, level 2 and level 3; When the vibration intensity is greater than 80, the output is level 3; when the vibration intensity is greater than 50, the output is level 2; when the vibration intensity is less than 50, the output is level 1; When the current puncture depth is less than 2.0 mm, the vibration intensity is calculated as follows: When the current puncture depth is ≥2.0 mm, the vibration intensity is calculated as follows: in, , Indicates the current puncture depth. Indicates the probe contact pressure; represents the dynamic elastic modulus of the vascular wall, , P Indicates blood pressure in blood vessels, r represents the vessel radius, h Indicates the wall thickness, Express the viscosity coefficient: 0.12Pa·s.

[0010] Furthermore, the vascular stability index is calculated as follows: in, represents the curvature entropy of the blood vessel contour, , represents the normalized curvature probability distribution; represents the photoacoustic signal-to-noise ratio, , represents the signal energy after wavelet packet denoising, represents the participating noise energy; represents the attenuation factor, is 0.05; represents the dynamic elastic modulus of the vascular wall, , P Indicates blood pressure in blood vessels, r represents the vessel radius, h Indicates the wall thickness, Express the viscosity coefficient: 0.12Pa·s; When VSI>0.35, the puncture angle was limited to ≤30°.

[0011] The present invention also provides a pressure injury diagnosis system, comprising: The laser excitation module is configured to emit 850 nm laser pulses for collagen imaging; The photoacoustic detection module is configured to receive the photoacoustic signal generated by the biological tissue and reconstruct the collagen imaging image based on the photoacoustic signal; an image processing module configured to calculate a hemoglobin / collagen concentration ratio R based on the collagen imaging image and generate a heat map of the damaged area; an elasticity decision module configured to obtain tissue elasticity information in real time, combine the hemoglobin / collagen concentration ratio R and the damage area heat map output by the image processing module with the tissue damage diffusion coefficient and the pressure injury index, and output an elasticity feedback decision; The display and reporting module is configured to mark the risk areas of damage diffusion according to the tissue damage diffusion coefficient and the pressure damage index, and to provide different color warnings and automatically generate a diagnostic report.

[0012] Furthermore, the tissue damage diffusion coefficient is calculated as follows: in, represents the Euclidean norm of the collagen concentration gradient, ; represents the rate of change of hemoglobin concentration, , represents the time step, ; When DDI>2.5, it is marked as a high-risk area for damage spread.

[0013] Furthermore, the pressure injury index is calculated as follows: PDI=R×(tissue hardness / 10) Where R represents the hemoglobin / collagen concentration ratio: , It represents the average hemoglobin concentration in the selected area; represents the average concentration of collagen in the same area; , represents the calibration coefficient of isolated porcine tissue, ; When PDI>0.8, it indicates high risk, and red indicates warning; When 0.4≤PDI≤0.8, it indicates medium risk, and yellow indicates warning; When PDI is less than 0.4, it indicates low risk and no warning.

[0014] The present invention also provides a handheld photoacoustic blood vessel and tissue diagnostic device, comprising: a handle-type host A, on which is mounted a replaceable probe B, a laser control module E, an ultrasound receiving array G, a pressure sensor I, and AR display glasses K; the handle-type host A is integrated with a photoacoustic blood vessel and tissue diagnostic system; The replaceable probe B is a conical puncture probe C and / or a flat-head scanning probe D; The pressure sensor I is equipped with an elastic feedback unit J, and the elastic feedback unit J is integrated with the above-mentioned photoacoustic guided puncture system and the above-mentioned pressure injury diagnosis system.

[0015] Furthermore, the laser control module E is equipped with a dual-wavelength laser source F; the wavelengths of the dual-wavelength laser source F are 532nm and 850nm.

[0016] Furthermore, the ultrasound receiving array G is equipped with a 128-element CMUT array, and the 128-element CMUT array is arranged in a ring on the probe base.

[0017] Furthermore, the AR display glasses K are equipped with a Wi-Fi 6 wireless transmission module, and the AR display glasses K project the direction of blood vessels / damage area to the operator's field of view.

[0018] The present invention has achieved the following beneficial effects: (1) The handheld multispectral photoacoustic imaging device provided by the present invention improves the puncture success rate by 30% through real-time blood vessel visualization combined with elastic force feedback; (2) The device uses a hemoglobin / collagen dual-index imaging algorithm to provide 72-hour early warning of pressure injuries; (3) The device automatically calculates the 3D hematoma volume, reducing the hematoma volume measurement error to <5%, significantly reducing the risk of multiple punctures and missed diagnosis; (4) Compared with the literature (Liu Qiang, Jin Tian, ​​Chen Qian, Xi Lei. Research Progress of Miniaturized Photoacoustic Imaging Technology inBiomedical Field[J]. Chinese Journal of Lasers, 2020, 47(2): 0207019.), the present invention pioneered the dynamic stability assessment of vascular stability index (VSI) and constructed a tissue damage diffusion coefficient (DDI) system, providing a new integrated solution of quantitative assessment and real-time navigation for vascular puncture and tissue damage diagnosis.

[0019] Obviously, based on the above contents of the present invention, according to common technical knowledge and customary means in this field, without departing from the above basic technical ideas of the present invention, other various forms of modifications, replacements or changes can be made.

[0020] The following is a further detailed description of the present invention through specific embodiments in the form of examples. However, this should not be construed as limiting the scope of the present invention to the following examples. All technologies implemented based on the above-mentioned content of the present invention fall within the scope of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a workflow diagram of the handheld multispectral photoacoustic imaging device of the present invention. DETAILED DESCRIPTION

[0022] For better understanding and implementation, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0023] It should be noted that the algorithms for data collection, transmission, storage and processing steps not specifically described in the embodiments, as well as the hardware structures, circuit connections, etc. not specifically described can all be implemented through the disclosed content of the prior art.

[0024] Example 1: Handheld multispectral photoacoustic imaging device of the present invention 1. Overview of the structure of the handheld multispectral photoacoustic imaging device The main body of the handheld multispectral photoacoustic imaging device is a handle-type host A; The handle-type host A is equipped with a replaceable probe B. When the vascular puncture mode is selected, the replaceable probe B is a conical puncture probe C; when the tissue scanning mode is selected, the replaceable probe B is a flat-head scanning probe D. The handle-type host A is also equipped with a laser control module E, which is equipped with a dual-wavelength laser source F. Among them, 532nm is used for vascular imaging and 850nm is used for collagen detection. The handle-type host A is also equipped with an ultrasound receiving array G, which is equipped with a 128-element CMUT array (arranged in a ring on the probe base); The handle-type host A is also equipped with a pressure sensor I, which is equipped with an elastic feedback unit J, which can calculate tissue hardness in real time and output tactile feedback; The handle-type host A is also equipped with AR display glasses K (Wi-Fi 6 wireless transmission module), which can project the direction of blood vessels / damaged areas into the operator's field of view.

[0025] The core components are summarized as follows: 1. Dual-mode probe (1) Conical puncture probe C: The tip integrates a 532nm laser outlet and an ultrasonic receiver (puncture angle ≤ 30°); Laser outlet diameter: 200μm, divergence angle <5°; Ultrasonic receiver: 64-channel CMUT, center frequency 10MHz; Puncture stopper: Mechanical constraint ensures the angle is ≤30°.

[0026] (2) Flat-head scanning probe D: 5×5 cm rectangular array (850nm laser source), supports sliding scanning; Laser array: 8×8 VCSEL array (850nm); Ultrasonic array: 128-element CMUT (0.5mm spacing); Sliding encoder: displacement accuracy ±0.1mm. 2. Pressure-elasticity feedback system (pressure sensor) Located on the probe contact surface, it measures the probe contact pressure in real time (range 0-10N); Pressure sampling rate: 1kHz; Tissue hardness algorithm: tissue hardness = (pressure value / vascular deformation rate) × k; Tactile feedback: piezoelectric ceramic vibrator (0-100 levels of intensity adjustable).

[0027] 3. AR display system Vascular navigation: real-time projection of 3D vascular model (blue) + needle tunnel (green); Damage warning: DDI>2.5 area flashes red + PDI value superimposed display.

[0028] 2. Core Algorithm 1. Vascular puncture navigation algorithm (1) Dynamic elastic navigation model The specific structure of the dynamic elastic navigation model in the vascular puncture navigation algorithm of the present invention is as follows: The input module is configured to perform blood vessel contour extraction (Canny edge detection) through the original photoacoustic signal.

[0029] The data processing module is configured to import the extracted blood vessel contour and other information into the deformation differential equation and obtain the optimal puncture angle through the path optimization algorithm. .

[0030] The present invention is based on Fung's quasi-linear viscoelasticity theory based on biomechanics: It is simplified into a real-time calculation model to calculate the dynamic elastic modulus (kPa) of the blood vessel wall. : in, P represents the blood pressure of the blood vessel (estimated by the photoacoustic pulsation signal); r : vessel radius; h : wall thickness; is the viscosity coefficient (human plasma viscosity), the default value is 0.12 Pa·s.

[0031] The objective function of the path optimization algorithm is: ; Optimal puncture angle The calculation is: , This is the blood vessel depth distribution map.

[0032] The output module is configured to output the optimal puncture angle .

[0033] The clinical validation results using the above dynamic elastic navigation model are as follows: Among 120 patients with a BMI > 30, the puncture success rate was 98% (68% in the control group); The rate of vascular collapse decreased from 22% to 3% (p < 0.01 p <0.01).

[0034] (2) Virtual force feedback mechanism Biomechanical resistance model (based on Hertz contact theory): in, : dynamic elastic modulus of the vascular wall (kPa), derived from the above-mentioned dynamic elastic navigation model; : Current puncture depth (mm); : Probe contact pressure (N).

[0035] Vibration intensity ( ) The hierarchical mapping (0-100 level) is as follows: Superficial tissue ( <2.0 mm): ; Deep tissue ( ≥2.0 mm): .

[0036] According to the above vibration intensity ( ), output tactile feedback (level 1 / 2 / 3). The specific tactile feedback rules are as follows: when Greater than 80, output level 3, high-frequency continuous vibration (danger warning); when Greater than 50, output level 2, medium frequency intermittent vibration (warning); when Less than 50, output level 1, low-frequency micro-vibration (safety boot).

[0037] The above formula is derived based on the Hertzian Contact Model. Reference: Johnson KL. Contact Mechanics. Cambridge University Press, 1987.

[0038] The clinical validation results using the above virtual force feedback mechanism are as follows: In a test of 50 patients, the consistency rate between the feedback vibration intensity and the doctor's hand feel was 92% (Kappa=0.85).

[0039] 2. New diagnostic parameter design The VSI, DDI and other parameters described in the present invention are derived based on the first principles of biomechanics. Their mathematical definitions and algorithmic processes have been fully disclosed, and their clinical effects can be verified through numerical simulation.

[0040] (1) Vascular stability index (VSI) Parameter definition: Vessel contour curvature entropy ( ): ,in, represents the normalized curvature probability distribution (calculated by KDE kernel density estimation); Photoacoustic signal-to-noise ratio (dB): ,in, represents the signal energy after wavelet packet denoising (WPT-L9); represents the participating noise energy; Dynamic elastic modulus of vascular wall ( ) as described in the “Vascular Puncture Navigation Algorithm”; Attenuation factor ( ) is 0.05 (determined by COMSOL multi-parameter optimization); represents the natural exponential function.

[0041] When VSI>0.35, the puncture angle was limited to ≤30°.

[0042] (2) Tissue damage diffusion coefficient (DDI) Parameter definition: The Euclidean norm of the collagen concentration gradient ( , mg / mL / mm): , calculated by Sobel operator (3×3 convolution kernel); Hemoglobin concentration change rate ( , mg / mL / s): , time step (Meet CFL conditions: ).

[0043] When DDI>2.5, it is marked as a high-risk area for damage spread.

[0044] 3. Data processing flow (1) The entire process of puncture navigation S1, photoacoustic acquisition → signal enhancement: 532 nm laser excitation + wavelet packet denoising (WPT-L9); S2, signal enhancement → 3D reconstruction: compressed sensing algorithm (ADMM optimizer solves min‖Ax-b‖2+λ‖x‖1); S3, 3D reconstruction → parameter calculation: real-time parallel calculation: Thread 1: ; Thread 2: ; S4. Parameter calculation → path planning: variational optimization ; S5, Path Planning → AR Display: Project the dynamic needle tunnel (green dashed line); S6, AR display → tactile feedback: vibration level = force_feedback ( , depth, pressure).

[0045] Technology includes: Real-time parallel architecture: GPU acceleration (NVIDIA Jetson Orin) makes computing latency less than 50ms; Compressed sensing reconstruction: the sampling rate is reduced to 40% (the original data volume) while maintaining PSNR>35dB; Path optimization: Output the optimal puncture angle through the Hamiltonian operator (As described in the “Vascular Access Navigation Algorithm”).

[0046] (2) Fourth-order analysis of damage diagnosis 1) Step 1: Multispectral Decomposition Input: The reflected light intensity measured at two known wavelengths (532nm and 850nm): signal_532, signal_850; Based on the Beer-Lambert law, the absorption coefficient matrix A at these two wavelengths was determined. The two sets of intensities mentioned above primarily include the absorption contributions of three substances: Hb (deoxyhemoglobin), HbO2 (oxyhemoglobin), and collagen. By solving the linear equations using least squares, the unit extinction coefficients of the three substances at each wavelength were calculated: A = np.array([[220, 80, 5], # 532nm: Hb, HbO2, Collagen [35, 40, 185]]) # 850nm: Hb, HbO2, Collagen Then, the least squares method is used to inversely solve the mixed photoacoustic signal measured at the two wavelengths into the concentration vectors of the three substances: concentrations = np.linalg.lstsq(A, [signal_532, signal_850], rcond=None)[0] return concentrations # [C_Hb, C_HbO2, C_Collagen] 2) Step 2: Spatiotemporal Gradient Calculation Sobel gradient: grad_C = cv2.Sobel(collagen_map, cv2.CV_64F, 1, 1, ksize=3) Central difference (Delta t = 0.1s): dH_dt = (Hb_map[t+1] - Hb_map[t-1]) / 0.2 3) Step 3: DDI synthesis DDI_map = np.linalg.norm(grad_C, axis=2) * np.sqrt(np.abs(dH_dt)) 4) Step 4: Risk classification risk_mask = (DDI_map>2.5) | (VSI_map<0.2).

[0047] 2, Pressure Injury Index (PDI) PDI = R x (Tissue Hardness / 10) Where R represents the hemoglobin / collagen concentration ratio. Clinical significance: R>1 indicates hemoglobin enrichment (acute injury), R<0.3 indicates collagen dominance (healthy tissue).

[0048] The specific calculation of R is as follows: Parameter definition: Hb_mean represents the average concentration of hemoglobin (mg / mL) in the selected area, calculated by spectral decomposition of the 532nm laser excitation signal; Col_mean represents the average concentration of collagen (mg / mL) in the same area, calculated by inversion of the 850nm laser excitation signal.

[0049] Tissue Hardness (kPa): Where, (ex vivo porcine tissue calibration coefficient); the strain rate is obtained by photoacoustic sequence deformation analysis.

[0050] Diagnostic threshold: PDI>0.8→High risk (AR red flashing warning); 0.4≤PDI≤0.8→Medium risk (yellow prompt); PDI<0.4→Low risk (no warning).

[0051] Example 2, the handheld multi-spectral photoacoustic imaging device of the application is used for blood vessel puncture The working process of blood vessel puncture using the handheld multi-spectral photoacoustic imaging device of Example 1 includes the following steps: Figure 1 ): S1, start scanning: system initialization, enter working state.

[0052] S2. Mode selection: The user switches the vascular puncture mode through the interface: In this mode, a conical puncture probe is placed in contact with the skin and excited by a 532nm laser to enhance the blood vessel boundaries. The photoacoustic signal generated by the biological tissue is received and an enhanced image of the blood vessel boundaries is reconstructed based on it. S3. Acquiring blood vessel contour information and current puncture depth based on the blood vessel boundary enhanced image; S4. Elastic feedback decision: It is used to obtain tissue elasticity information in real time, combine the vascular contour information output by the image processing module and the current puncture depth with the vascular stability index, and output elastic feedback decisions under the dynamic elastic navigation model and virtual force feedback model, including the optimal puncture angle and vibration intensity. ; S5. Intelligent decision output: Output optimal puncture angle and vibration intensity: when the probe pressure is greater than 5N, the vibration alarm is triggered.

[0053] Example 3: Use of the handheld multispectral photoacoustic imaging device of the present invention for tissue damage assessment The workflow for tissue damage assessment using the handheld multispectral photoacoustic imaging device described in Example 1 includes the following steps: Figure 1 ): S1. Start scanning: the system is initialized and enters the working state.

[0054] S2. Mode selection: The user switches the tissue damage assessment mode through the interface: In this mode, a flat-head scanning probe is used for sliding scanning, and 850nm laser excitation is used for collagen imaging to obtain collagen distribution and generate a thermal map of the damaged area. S3, dual wavelength fusion calculation of hemoglobin / collagen concentration ratio R; S4. Elastic feedback decision: It is used to obtain tissue elasticity information in real time, combining the hemoglobin / collagen concentration ratio R and the damage area heat map output by the image processing module with the tissue damage diffusion coefficient and pressure injury index to output elasticity feedback decision; S5. Intelligent decision output: The risk area for damage spread is marked according to the tissue damage diffusion coefficient and pressure injury index, and different color warnings are prompted: when PDI>0.8, AR glasses mark the red warning area.

[0055] The beneficial effects of the present invention are demonstrated by experimental examples below.

[0056] Experimental Example 1: Application of the handheld multispectral photoacoustic imaging device of the present invention Scenario 1: Venipuncture The nurse wears AR glasses and uses a conical puncture probe to locate the blood vessel. The glasses display the 3D direction of the blood vessel (blue). Tactile feedback: When the probe contact pressure reaches 3N, the handle vibrates slightly → insert the needle at θ=60° → the first-time puncture success rate is 98%.

[0057] Scenario 2: Bedsore warning The flat-head scanning probe scans the sacrum and coccyx → PDI = 0.92 → AR glasses red highlighted area; Nursing advice: Turn the baby over every 2 hours and use a pressure relief pad → PDI drops to 0.3 after 3 days.

[0058] In summary, the present invention provides a handheld multimodal photoacoustic vascular puncture and tissue injury diagnostic system and device. This handheld multispectral photoacoustic imaging device integrates elastic force feedback and real-time vascular visualization, increasing puncture success rates by 30%. Hemoglobin / collagen dual-index imaging provides 72 hours of early warning of pressure injuries. Automatic 3D hematoma volume calculation has an error of <5%, significantly reducing repeat punctures and missed diagnoses. This invention provides a safe and efficient integrated solution for quantitative assessment and real-time navigation of vascular puncture and tissue injury.

Claims

1. A photoacoustic guided puncture system, characterized in that: include: The laser excitation module is configured to emit 532 nm laser pulses to enhance blood vessel boundaries; The photoacoustic detection module is configured to receive the photoacoustic signal generated by the biological tissue and reconstruct the blood vessel boundary enhanced image based on the photoacoustic signal; an image processing module configured to obtain blood vessel contour information and a current puncture depth based on the blood vessel boundary enhanced image; an elasticity decision module configured to obtain tissue elasticity information in real time, combine the vascular contour information and current puncture depth output by the image processing module with the vascular stability index, and output an elasticity feedback decision, including the optimal puncture angle and vibration intensity, under a dynamic elastic navigation model and a virtual force feedback model; The human-computer interaction module is configured to display the blood vessel boundary enhanced image, the optimal puncture angle and the vibration intensity in real time and perform the blood vessel puncture operation.

2. The system according to claim 1, wherein: The optimal puncture angle is calculated as follows: in, represents the dynamic elastic modulus of the vascular wall, , P Indicates blood pressure in blood vessels, r represents the vessel radius, h Indicates the wall thickness, Express the viscosity coefficient: 0.12Pa·s; Represents the blood vessel depth distribution map.

3. The system according to claim 1, wherein: The elastic feedback is divided into level 1, level 2 and level 3; When the vibration intensity is greater than 80, the output is level 3; when the vibration intensity is greater than 50, the output is level 2; when the vibration intensity is less than 50, the output is level 1; When the current puncture depth is less than 2.0 mm, the vibration intensity is calculated as follows: When the current puncture depth is ≥2.0 mm, the vibration intensity is calculated as follows: in, , Indicates the current puncture depth. Indicates the probe contact pressure; represents the dynamic elastic modulus of the vascular wall, , P Indicates blood pressure in blood vessels, r represents the vessel radius, h Indicates the wall thickness, Express the viscosity coefficient: 0.12Pa·s.

4. A pressure injury diagnosis system, characterized in that: include: The laser excitation module is configured to emit 850 nm laser pulses for collagen imaging; The photoacoustic detection module is configured to receive the photoacoustic signal generated by the biological tissue and reconstruct the collagen imaging image based on the photoacoustic signal; an image processing module configured to calculate a hemoglobin / collagen concentration ratio R based on the collagen imaging image and generate a heat map of the damaged area; an elasticity decision module configured to obtain tissue elasticity information in real time, combine the hemoglobin / collagen concentration ratio R and the damage area heat map output by the image processing module with the tissue damage diffusion coefficient and the pressure injury index, and output an elasticity feedback decision; The display and reporting module is configured to mark the risk areas of damage diffusion according to the tissue damage diffusion coefficient and the pressure damage index, and to provide different color warnings and automatically generate a diagnostic report.

5. The system according to claim 4, characterized in that The tissue damage diffusion coefficient is calculated as follows: in, represents the Euclidean norm of the collagen concentration gradient, ; represents the rate of change of hemoglobin concentration, , represents the time step, ; When DDI>2.5, it is marked as a high-risk area for damage spread.

6. The system according to claim 4, characterized in that The pressure injury index is calculated as follows: PDI=R×(tissue hardness / 10) Where R represents the hemoglobin / collagen concentration ratio: , It represents the average hemoglobin concentration in the selected area; represents the average concentration of collagen in the same area; , represents the calibration coefficient of isolated porcine tissue, ; When PDI>0.8, it indicates high risk, and red indicates warning; When 0.4≤PDI≤0.8, it indicates medium risk, and yellow indicates warning; When PDI is less than 0.4, it indicates low risk and no warning.

7. A handheld photoacoustic blood vessel and tissue diagnostic device, characterized in that: include: A handle-type host A, which is equipped with a replaceable probe B, a laser control module E, an ultrasound receiving array G, a pressure sensor I, and AR display glasses K; the handle-type host A integrates a photoacoustic blood vessel and tissue diagnosis system; The replaceable probe B is a conical puncture probe C and / or a flat-head scanning probe D; The pressure sensor I is equipped with an elastic feedback unit J, and the elastic feedback unit J is integrated with the photoacoustic guided puncture system described in any one of claims 1 to 3 and the pressure injury diagnosis system described in any one of claims 4 to 6.

8. The device according to claim 7, characterized in that The laser control module E is equipped with a dual-wavelength laser source F; the wavelengths of the dual-wavelength laser source F are 532nm and 850nm.

9. The device according to claim 7, characterized in that The ultrasound receiving array G is equipped with a 128-element CMUT array, which is arranged in a ring on the probe base.

10. The device according to claim 7, characterized in that The AR display glasses K are equipped with a Wi-Fi 6 wireless transmission module, and the AR display glasses K project the direction of blood vessels / damage area to the operator's field of view.

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