An interventional instrument and viscoelasticity measurement method

Abstract

The application provides an interventional instrument and a viscoelasticity measurement method, which is based on laser speckle rheology technology, uses a fiber image transmission bundle as a guide wire main body, simultaneously transmits optical signals, collects time-varying speckle images through a high-speed camera, establishes the connection between speckle fluctuation and the mean square displacement of scattering particles in a viscoelastic substance through the analysis of time-varying speckle signals, quantitatively calculates the viscoelasticity information of the measured substance, measures the viscoelasticity of a plaque, destroys abnormal arterial endothelial cells and inflammatory cells in the plaque by using a photodynamic therapy method, achieves the purpose of quantitatively detecting the viscoelasticity of biological tissues and identifying abnormal positions and performing photodynamic therapy, can effectively detect the viscoelasticity characteristics of the plaque in the blood vessel, identify the abnormal positions in the blood vessel, perform photodynamic therapy on the atherosclerotic plaque and other abnormal positions by using laser, reduces the complexity of surgical operation, is helpful to promote the development of medical technology, and promotes the continuous upgrading and optimization of medical services.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical devices, and particularly relates to an interventional device and a viscoelasticity measurement method. BACKGROUND

[0002] Acute coronary syndrome (ACS) refers to a group of clinical symptoms caused by acute reduction or complete interruption of coronary artery blood flow. The main cause of ACS is the rupture or ulceration of coronary plaque, which leads to thrombosis and further causes obstruction of coronary artery blood flow. This can lead to myocardial ischemia, damage or even necrosis, and in severe cases, can lead to arrhythmia, heart failure or even death. Measurement of the viscoelasticity of intravascular plaque is crucial for identifying plaques at risk of rupture and reducing the incidence of myocardial infarction. Current techniques such as intravascular ultrasound, optical coherence tomography, infrared spectroscopy and coronary angiography can evaluate the microscopic structure and composition characteristics of key plaques, but they cannot predict the location of plaques during guidewire advancement and perform diagnosis and treatment on plaques.

[0003] Photodynamic therapy uses light of a specific wavelength to activate photosensitizers, destroying abnormal arterial endothelial cells and inflammatory cells in plaques, thereby reducing the size and risk of plaques. As a new treatment method, photodynamic therapy has great potential. In addition to being used for the treatment of atherosclerotic plaques, photodynamic therapy can also be used to treat other vascular diseases such as thrombotic diseases and intravascular tumors. Photodynamic therapy not only has the effects of reducing plaques, anti-inflammation and anti-thrombosis, but also can inhibit the excessive proliferation of vascular endothelial cells caused by balloon injury, and by promoting the growth and repair of normal endothelial cells, it provides a more stable vascular wall environment and prevents arterial restenosis. In addition, the integration of diagnosis and treatment of intravascular atherosclerotic plaques during guidewire advancement helps doctors better identify and locate lesions, improves medical quality and efficiency, reduces medical risks, improves patient experience, and promotes medical technology innovation.

[0004] As a new optical viscoelasticity measurement technology, laser speckle rheology (LSR) can realize the rapid, non-invasive, high-sensitivity and non-contact detection of the viscoelasticity of biological tissues. By analyzing the time-varying speckle signal, the relationship between speckle fluctuation and mean square displacement of scattering particles in viscoelastic substances is established, and the viscoelastic information of the measured substance is quantitatively calculated to achieve the purpose of quantitative detection of the viscoelasticity of biological tissues. The current diagnosis and treatment integrated probe combines optical imaging and laser treatment. In 2022, Fan Yingwei et al. invented an optical coherence tomography guided laser minimally invasive diagnosis and treatment endoscope probe, which changes the laser exit angle by adjusting the rotation of the reflector, uses the imaging laser fiber to judge the lesion position, and uses the ablation laser fiber for treatment, realizing the integration of in-vivo diagnosis and treatment. In 2022, Liao Hongen et al. proposed a diagnosis and treatment integrated probe which couples the imaging light and the treatment light into the same optical fiber through a dichroic mirror, solving the defects of poor matching of diagnosis and treatment and large monitoring error in the prior art, but the complex structure is not conducive to the miniaturization of the instrument. The application of laser speckle rheology technology to interventional clinical practice can realize the detection and diagnosis and treatment of the lesion position, simplify the system structure, and realize the integration of diagnosis and treatment of the lesion position, but there are still problems such as small imaging range, non-real-time imaging, and grid shadow in the transmission image due to the difference between the cladding and core materials of the image transmission bundle, loss of part of the image information, etc. SUMMARY

[0005] The technical problem to be solved by the present application is to provide an interventional instrument.

[0006] Another technical problem to be solved by the present application is to provide a viscoelasticity measurement method for the above-mentioned interventional instrument.

[0007] To solve the above technical problems, the technical solution of the present application is:

[0008] An interventional instrument, comprising a guide wire (4), an image transmission bundle front-end probe (9), a magnetic control guiding device, a laser irradiation device and an image receiving device, wherein,

[0009] The guide wire (4), the optical fiber image transmission bundle (5) is used as the main part of the guide wire (4), the outer layer of the optical fiber image transmission bundle (5) is inlaid with a magnet (6), the magnet (6) is composed of two magnet segments (11), the outer layer of the magnet (6) is provided with a protective sleeve (7), and the outer layer of the protective sleeve is plated with a hydrophilic coating (8);

[0010] The image transmission bundle front end probe (9) comprises four free curved surfaces (as reflecting mirrors) and an aspherical lens (9), the material of the image transmission bundle front end probe (9) is photoresist SU-8, the four free curved surfaces are coated with a reflective coating for reflecting the light emitted from the optical fiber image transmission bundle (5) to the side wall for illumination, the top of the four free curved surfaces is fixed with the aspherical lens (9) for receiving the scattered light signal of the front end of the probe, and the free curved surface of the image transmission bundle front end probe (9) is coupled to the front end of the optical fiber image transmission bundle.

[0011] The magnetic control guiding device comprises a wire feeding mechanism (3), a mechanical arm (1) and a permanent magnet (2), the wire feeding mechanism (3) and the mechanical arm (1) are arranged at intervals, the permanent magnet (2) is fixed at the end of the mechanical arm (1), the driving clamping part of the wire feeding mechanism (3) is connected with the wire guide (4), and the wire feeding mechanism and the mechanical arm are arranged on the two sides of the operating table during use, the wire feeding mechanism is close to the lower part of the human body, and the main working range of the mechanical arm is in the upper half of the human body.

[0012] The laser irradiation device comprises a laser (15), a first polarizing mirror (16), a beam expander (17) and a reflecting mirror (18), and the front end of the laser (15) is sequentially provided with the first polarizing mirror (16), the beam expander (17) and the reflecting mirror (18).

[0013] The image receiving device comprises an objective lens (19), a beam splitter (20), a second polarizing mirror (21), a focusing lens (22) and a CMOS camera (23), the reflecting mirror (18) is provided with the beam splitter (20) on the side surface, the beam splitter (20) divides the light beam into two paths, the two light beams propagate on the two sides of the beam splitter (20) respectively, the side of the beam splitter (20) is provided with the objective lens (19), the end of the optical fiber image transmission bundle (5) is coupled with the objective lens (19), and the other side of the beam splitter (20) is sequentially provided with the second polarizing mirror (21), the focusing lens (22) and the CMOS camera (23).

[0014] Preferably, the above-mentioned interventional instrument, the hydrophilic coating comprises a PUA (polyurethane acrylate) coating (12), a PVP (polyvinyl pyrrolidone) coating (13) and a hyaluronic acid gel film (14), wherein the PUA coating (12) is covered on the surface of the protective sleeve (7) by using ultraviolet curing technology, the PVP coating (13) is polymerized on the PUA coating (12) by using ultraviolet curing technology, and the hyaluronic acid gel film (14) is coated on the PVP coating (13).

[0015] Preferably, the above-mentioned interventional instrument, the material of the protective sleeve (7) is silicone rubber.

[0016] Preferably, in the above-mentioned interventional device, the optical fiber image bundle (5) is a polymer optical fiber image bundle with a core number of 13,000, a numerical aperture of 0.5, a diameter of 1 mm, and a diameter of 1.25 mm for the protective sleeve (7).

[0017] Preferably, in the above-mentioned interventional device, the magnet (11) is attached to the surface of the optical fiber image bundle (5) by using femtosecond laser processing technology. The magnet (11) is a axially polarized cylindrical N52 neodymium magnet with a length of 6mm. The two magnets (11) are attached to the front end and the middle section of the optical fiber image bundle (5) respectively, and the two magnets (11) are 21mm apart.

[0018] Preferably, in the above-mentioned interventional device, the four free-form and aspherical lenses of the front probe (9) of the image beam are integrated into one structure, and are directly printed onto the end face of the fiber image beam (5) using femtosecond laser two-photon polymerization technology. Gold (Au) material is used as the free-form reflective coating, and the coating is precisely deposited through physical vapor deposition (PVD) technology.

[0019] Preferably, in the above-mentioned interventional device, the aspherical lens can be described by the following expression:

[0020]

[0021] In the formula: a0 represents the height constant of the vertex of the aspherical lens, c represents the curvature, k represents the aspherical lens, and ai represents the coefficients in the polynomial expansion, used to describe the higher-order aspherical correction terms. The parameters of the aspherical lens are: a0 = 0.2 mm, c = 0.459 mm. -1 , k = 2.035, a2 = 0.171, a4 = 2.374, a6 = -3.723. The freeform surface can be described by the following expression:

[0022]

[0023] Off-axis eccentricity of optical surface and surface parameters c, k and y, y 2 y 3 y 4 x 2 x 4 x 2 y, x 2 y 2 The coefficients are as follows, where the origin of the coordinate system is the center of the probe structure.

[0024]

[0025]

[0026] Preferably, the above-mentioned interventional instrument, the laser (15) is a helium-neon laser with a wavelength of 632 nm, and the laser light source can adjust the light source intensity to interact with the photosensitizer drug to achieve photodynamic therapy of the atherosclerotic plaque in the blood vessel or promote the healing of the damaged endothelial cells of the blood vessel, thereby providing a more stable blood vessel wall environment.

[0027] Preferably, the above-mentioned interventional instrument, the magnetic control guiding device adjusts the magnetic field strength of the magnet on the guide wire according to the position of the guide wire (4) relative to the blood vessel wall to ensure that the guide wire (4) is located in the middle position of the blood vessel wall, and the position of the guide wire (4) relative to the blood vessel wall is obtained by analyzing the change rule of the speckle pattern.

[0028] The viscoelasticity measurement method of the above-mentioned interventional instrument includes the following specific steps:

[0029] (1) The guide wire is introduced into the radial artery or femoral artery by using the wire feeding mechanism, the magnetic control guiding device controls the rotation, advancement and bending of the guide wire, and after the guide wire reaches the target position, the catheter is slid along the guide wire to the predetermined position, and the photosensitizer is injected through the catheter;

[0030] (2) After the guide wire enters the blood vessel, when the guide wire approaches the plaque in the blood vessel, the image transmission probe (9) at the front end of the optical fiber image transmission bundle (5) can sense the existence and position of the plaque, causing the speckle pattern of the corresponding area to change significantly;

[0031] (3) The speckle pattern transmitted by the optical fiber image transmission bundle (5) is received and recorded in real time by using the image receiving device, the speckle pattern noise is eliminated by using the image super-resolution neural network method, and the quality of the speckle pattern image is improved;

[0032] (4) The reconstructed speckle pattern is further analyzed to obtain the viscoelasticity of the plaque;

[0033] (5) A deep learning algorithm based on convolutional neural network is used to classify plaques with different viscoelasticity through a series of speckle patterns;

[0034] (6) The pathological characteristics of the plaque are evaluated according to the data analysis results, the abnormal part is identified, and photodynamic therapy is performed, the power density and illumination time of the laser after passing through the optical fiber image transmission bundle are controlled by adjusting the illumination parameters of the laser, and the outgoing laser is accurately targeted to the macrophages in the abnormal plaque through the image transmission probe at the front end of the optical fiber image transmission bundle to treat the plaque.

[0035] Preferably, the viscoelasticity measurement method of the above-mentioned interventional instrument includes the following specific steps of step (1):

[0036] (1-1) The position of the permanent magnet at the end of the mechanical arm is accurately adjusted to ensure that the guide wire accurately enters the blood vessel system to be detected and the position and direction of the guide wire can be accurately controlled;

[0037] (1-2) After the guide wire enters the blood vessel, the speckle pattern obtained by the optical fiber image transmission bundle is analyzed to position the magnetic control guide wire and determine the relative position of the guide wire and the blood vessel wall; the mechanical arm and the permanent magnet in the magnetic control guide device are used to feedback control the magnetic field strength of the magnet on the guide wire, so as to ensure that the position and posture of the guide wire in the blood vessel meet the expectations, thereby ensuring the accurate performance of the subsequent steps.

[0038] Preferably, the viscoelasticity measurement method of the above interventional instrument, the specific steps of the step (3) comprise:

[0039] (3-1) Adjusting the frame rate and exposure time of the CMOS camera, adjusting the speckle size to be twice the size of a pixel, selecting the region of interest to collect images, and obtaining a series of speckle images changing with time;

[0040] (3-2) The speckle image obtained in step (3-1) is preliminarily denoised by using a single-image unsupervised denoising convolutional neural network method;

[0041] (3-3) The preliminarily denoised speckle image obtained in step (3-2) is image reconstructed by using a honeycomb-artifact removal convolutional neural network algorithm, including three convolutional layers: speckle extraction, nonlinear mapping and reconstruction;

[0042] (3-4) The reconstruction performance of HAR-CNN on the synthetic image is verified by superimposing an artificial honeycomb pattern on the original image, and two indicators of peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) are used for quantitative evaluation, wherein PSNR is used to quantify the recovery quality of the image, and the intensity difference between the two images is compared pixel by pixel, and SSIM is used to quantify the image quality relative to the direct source degradation.

[0043] Preferably, the viscoelasticity measurement method of the above interventional instrument, the specific steps of the step (4) comprise:

[0044] (4-1) Further analyzing the reconstructed speckle image in step (3), and cross-correlating the region of interest in the first image with the region of interest in all subsequent images to obtain the autocorrelation curve g2(t) of the time speckle intensity, and to improve the speckle time statistical accuracy, the same group of data is collected multiple times and averaged in time;

[0045] (4-2) The autocorrelation curve is fitted with a single exponential decay function, and the decorrelation time when the correlation decreases to 70% is extracted, which is used for qualitative analysis of speckles with different viscoelasticity;

[0046] (4-3) Extracting the mean square displacement MSD reflecting the Brownian motion characteristics of the particles inside the speckle from the autocorrelation curve;

[0047] (4-4) Substituting the MSD calculated in step (4-3) into the Stokes-Einstein relationship, the viscoelasticity of the plaque is quantitatively calculated.

[0048] Advantages:

[0049] The above interventional instrument, based on laser speckle rheology technology, uses an optical fiber image transmission bundle as the guide wire main body, simultaneously transmits optical signals, collects time-varying speckle images through a high-speed camera, establishes the relationship between speckle fluctuations and the mean square displacement of scattering particles in viscoelastic substances through analysis of time-varying speckle signals, quantitatively calculates the viscoelasticity information of the measured substance, measures the viscoelasticity of the plaque, and destroys abnormal endothelial cells in the artery and inflammatory cells in the plaque using photodynamic therapy, achieving the purpose of quantitative detection of the viscoelasticity of biological tissues and identification and photodynamic diagnosis and treatment of abnormal parts. It can effectively detect the viscoelasticity characteristics of the plaque in the blood vessel, identify abnormal parts, use laser to perform photodynamic therapy on atherosclerotic plaques, reduce plaques, and reduce risks, which helps to promote the development of medical technology and continuously upgrade and optimize medical services.

[0050] The interventional instrument can detect the plaque or tumor in the blood vessel in all directions and use photodynamic therapy to treat atherosclerotic plaques, thrombus, or tumors, which is of great significance for accurate identification and efficient treatment of abnormal parts. By analyzing the shape or change of the laser speckle pattern, the position of the magnetic guide wire relative to the blood vessel wall can be inferred, and the magnetic field can be adjusted in real time to control the position of the guide wire, thereby reducing the need for X-ray guidance and reducing the level of radiation exposure during the operation, protecting the health and safety of medical staff and patients. Specifically:

[0051] 1. The laser speckle rheology technology can detect the presence and location of the plaque in the blood vessel in real time, providing more accurate lesion positioning and surgical guidance for doctors, and improving the success rate of the operation and the treatment effect.

[0052] 2. The optical fiber image transmission bundle as the guide wire main body realizes flexible, fast, non-destructive, and high-sensitivity measurement of the viscoelasticity of the plaque, providing an important reference for the stability of the plaque for doctors to guide the development of individualized treatment strategies.

[0053] 3. The application of hydrophilic coating technology improves the intravascular sliding and guiding properties of the guide wire, reduces the risk of blood clotting, improves the clarity and accuracy of optical imaging, and improves the biocompatibility and stability of the guide wire.

[0054] 4. The large-angle image transmission bundle front-end probe can detect the plaque in the blood vessel in all directions without rotating the guide wire, shortening the operation time and reducing the discomfort and risk of the patient.

[0055] 5. The use of image super-resolution neural network method to process speckle images improves image quality and data accuracy, providing doctors with more comprehensive plaque assessment and treatment decision-making basis.

[0056] 6. The application of the magnetic control guiding device enables precise control of the entry, rotation, and movement of the guide wire, combined with real-time monitoring function, improves the positioning accuracy of the guide wire in the blood vessel, reduces the need for X-ray guidance, and can reduce the radiation exposure level during the operation, protecting the health and safety of medical staff and patients.

[0057] 7. Photodynamic diagnosis and treatment integration: By integrating photodynamic therapy technology into interventional instruments, a diagnosis and treatment integrated medical model is realized, which not only can detect abnormal parts, but also can perform real-time treatment in the same operation, providing patients with more comprehensive medical services and reducing the complexity and risk of the treatment process. BRIEF DESCRIPTION OF DRAWINGS

[0058] Figure 1 is a schematic diagram of a magnetic control guiding device;

[0059] Figure 2 is a schematic diagram of a guide wire structure;

[0060] Figure 3 is a schematic diagram of the distribution of magnets in the guide wire;

[0061] Figure 4 is a schematic diagram of the hydrophilic coating structure outside the optical fiber image transmission bundle;

[0062] Figure 5 is a schematic diagram of a laser speckle rheology measurement device;

[0063] Figure 6 is a flowchart of the magnetic control guide wire diagnosis and treatment integration process;

[0064] Figure 7 is a flowchart of the calculation of plaque viscoelasticity algorithm of laser speckle rheology;

[0065] Figure 8 is a schematic diagram of the HAR-CNN workflow for removing honeycomb artifacts;

[0066] Figure 9 is a schematic diagram of the network architecture of HAR-CNN;

[0067] Figure 10 Autocorrelation curves g2(t) of different biological tissue samples;

[0068] Figure 11 is a flowchart of a deep learning algorithm for classifying plaques.

[0069] In the diagram: 1-robotic arm; 2-permanent magnet; 3-wire feeding mechanism; 4-guide wire; 5-fiber image bundle; 6-magnet layer; 7-protective sleeve; 8-hydrophilic coating; 9-image bundle front probe; 10-reflective coating; 11-hollow cylindrical magnet; 12-PUA coating; 13-PVP coating; 14-hyaluronic acid gel film; 15-laser; 16-first polarizer; 17-beam expander; 18-reflector; 19-objective lens; 20-beam splitter; 21-second polarizer; 22-focusing lens; 23-CMOS camera. Detailed Implementation

[0070] The interventional device and viscoelasticity measurement method of the present invention will be described below with reference to the embodiments and accompanying drawings.

[0071] Example 1

[0072] An interventional device includes a guidewire 4, an image transmission beam front probe 9, a magnetically controlled guidance device, a laser irradiation device, and an image receiving device, wherein...

[0073] The guide wire 4, as Figure 2 As shown, the polymer optical fiber image bundle 5 serves as the main body of the guide wire 4. A magnet 6 is embedded in the outer layer of the optical fiber image bundle 5. The magnet 6 consists of two magnet segments 11. A protective sleeve 7 is provided on the outer layer of the magnet 6, and the outer layer of the protective sleeve is coated with a hydrophilic coating 8. The optical fiber image bundle 5 has a core count of 13000, a numerical aperture of 0.5, a diameter of 1 mm, and a diameter of 1.25 mm for the protective sleeve 7. The magnets 11 are distributed as follows... Figure 3 As shown, the magnet is fabricated as follows: A microfabrication environment conducive to the attachment of magnetic materials is created in a specific area on the fiber surface using femtosecond laser-induced local heating. Magnetic materials are then attached to the surface of the fiber image bundle 5 to form a strong hollow cylindrical magnet. Magnet 11 is a 6mm long, axially polarized cylindrical N52 neodymium magnet. Two sections of magnet 11 are attached to the front and middle sections of the fiber image bundle 5, respectively, with a distance of 21mm between them. The hydrophilic coating is as follows: Figure 4 As shown, the protective sleeve 7 of the optical fiber image bundle is made of silicone rubber (as the base material covered by the coating). A PUA coating 12, which serves as the substrate of the composite coating, a PVP coating 13, which serves as the surface of the composite coating, and a hyaluronic acid gel film 14, which is used to increase the coating's lubrication and biocompatibility in special scenarios involving human blood vessels, are sequentially fixed on it. The silicone rubber is partially cured and bonded to the PUA coating by ultraviolet light curing. The PVP coating is then polymerized with the PUA coating by ultraviolet light curing to form a PUA-PVP composite surface. Finally, the hyaluronic acid film is covered by the dip-coating method to form a hydrophilic coating.

[0074] The image transmission bundle front-end probe 9 includes four freeform surfaces (as reflectors) and an aspherical lens 9. The material of the image transmission bundle front-end probe 9 is SU-8 photoresist. The four freeform surfaces are coated with a reflective coating to reflect the light emitted from the fiber optic image transmission bundle 5 onto the sidewalls for illumination, and to couple the scattered light diffusely reflected from the patch surface into the fiber optic image transmission bundle, thus forming a speckle pattern on the camera. An aspherical lens 9 is fixed to the top of the four freeform surfaces to receive the scattered light signal from the probe front end. When the guide wire front end detects a patch, diffuse reflection occurs on the patch surface. The aspherical lens couples the reflected scattered light into the fiber optic image transmission bundle for transmission. The function of the aspherical lens is to improve the coupling efficiency of the beam and focus the beam into the image transmission bundle, thereby presenting a clear pattern on the camera. The aspherical lens can be described by the following expression:

[0075]

[0076] In the formula: a0 represents the height constant of the vertex of the aspherical lens, c represents the curvature, k represents the aspherical lens, and ai represents the coefficients in the polynomial expansion, used to describe the higher-order aspherical correction terms. The parameters of the aspherical lens are: a0 = 0.2 mm, c = 0.459 mm. -1 , k = 2.035, a2 = 0.171, a4 = 2.374, a6 = -3.723. The freeform surface can be described by the following expression:

[0077]

[0078] In the formula, c x and c y Let k be the radius of curvature of the surface in the XZ and YZ planes. x and k y Let be the quadratic aspherical coefficients of the surface in the XZ and YZ planes. The highest term of the xy polynomial is restricted to degree 4. The freeform surface can be described by the following expression:

[0079]

[0080] In the polynomial, the coefficients of the odd-degree terms of x are 0. To ensure the feasibility of processing, the highest-degree term of the xy polynomial is limited to 4. During design optimization, c, k, and y, y 2 y 3 y 4 x 2 x 4 x 2 y, x 2 y 2 The coefficients of are set as variables, and the coefficients of other polynomials are set to 0. The off-axis eccentricity of the optical surface and the surface parameters c, k, and y, y0 are also considered. 2 y3 y 4 x 2 x 4 x 2 y, x 2 y 2 The coefficients are as follows, where the origin of the coordinate system is the center of the probe structure.

[0081] y-direction eccentricity / mm -0.014 z-direction eccentricity / mm 0.176 Alpha tilt / ° 0.664 radius of curvature / mm 0.582 k -0.45827 y-term coefficient -0.08307 x 2 term coefficients 0.04517 y 2 term coefficients 0.16009 x 2 y 2 term coefficients -0.18887 y 3 term coefficients -0.12663 x 4 term coefficients 0.12464 x 2 y 2 term coefficients -0.05466 y 4 term coefficients 0.22077

[0082] This design enables simultaneous detection of plaque information on the vessel sidewall and guidewire tip during guidewire advancement, achieving omnidirectional detection without guidewire rotation, thus simplifying the system structure and enabling large-angle sensing. The freeform surface of the image beam front probe 9 is coupled to the front end of the fiber optic image beam. The four freeform surfaces and aspherical lenses of the image beam front probe 9 are integrated into a single structure, directly printed onto the end face of the fiber optic image beam using femtosecond laser two-photon polymerization technology. Gold (Au) material is used as the freeform surface reflective coating, and the coating is precisely deposited using physical vapor deposition (PVD) technology.

[0083] Magnetic guidance device such as Figure 1 As shown, it includes a wire feeding mechanism 3, a robotic arm 1, and a permanent magnet 2. The wire feeding mechanism consists of an active clamping mechanism and a dual-motion modular roller mechanism (component structure referenced in A Vascular Intervention Assist Device Using Bi-Motional Roller Cartridge Structure and Clinical Evaluation, Biosensors). Composed of (2021, 11, 329.), the system includes an active clamping mechanism that holds the guidewire, a dual-motion modular roller mechanism that advances the magnetically controlled guidewire into the interventional blood vessel, a wire feeding mechanism 3 and a robotic arm 1 spaced apart, a permanent magnet 2 fixed to the end of the robotic arm 1, and an active clamping component of the wire feeding mechanism 3 connected to the middle of the guidewire 4. During use, the wire feeding mechanism and the robotic arm are on opposite sides of the operating table, with the wire feeding mechanism close to the lower part of the human body and electrically connected to the vascular interventional surgery system. The main working range of the robotic arm is in the upper part of the human body. One end of the robotic arm is fixed with a permanent magnet (EMM), and the other end is fixed to the middle of one side of the vascular interventional surgery table. The permanent magnet 2 is an axially polarized cylindrical neodymium magnet with a diameter of 50×60mm. Its position is controlled by the robotic arm, thereby controlling the change of the magnetic field. After the guidewire is advanced by the wire feeding mechanism 3, the active clamping component of the wire feeding mechanism clamps the guidewire and pushes it into the blood vessel. The magnetic field strength of the magnet on the guidewire is adjusted according to the position of the guidewire 4 relative to the blood vessel wall, ensuring that the guidewire 4 is located in the middle position of the blood vessel wall. The position of the guidewire 4 relative to the blood vessel wall is obtained by analyzing the variation law of the speckle pattern.

[0084] Laser irradiation devices such as Figure 5 As shown, the laser irradiation device includes a helium-neon laser 15 with a wavelength of 632nm, a first polarizing mirror 16, a beam expander 17, and a reflector 18. The laser 15 is provided with the first polarizing mirror 16, the beam expander 17, and the reflector 18 in sequence at its front end. The laser source of the laser 15 can adjust the intensity of the light source and interact with the photosensitizer drug to achieve photodynamic therapy on atherosclerotic plaques in blood vessels.

[0085] Image receiving device such as Figure 5 As shown, the image receiving device includes an objective lens 19, a beam splitter 20, a second polarizer 21, a focusing lens 22, and a CMOS camera 23. The beam splitter 20 is provided on the side of the reflecting mirror 18. The beam splitter 20 splits the light beam into two paths, and the two paths propagate on both sides of the beam splitter 20. An objective lens 19 is provided on one side of the beam splitter 20. The end of the optical fiber image bundle 5 is coupled to the objective lens 19. The second polarizer 21, the focusing lens 22, and the CMOS camera 23 are sequentially provided on the other side of the beam splitter 20.

[0086] The aforementioned helium-neon laser outputs randomly polarized light at 632.8 nm. The polarization state of the beam is changed by the first polarizing mirror 16, and the beam spot is enlarged by the beam expander 17. The beam is then coupled into the fiber optic image bundle by the beam splitter 20 and the objective lens 19. The fiber optic image bundle focuses the beam spot onto the surface of the sample under test. The beam is scattered by the scattering particles inside the sample. The scattered light returns to the beam splitter 20 through the fiber optic image bundle, and then changes its polarization state by the second polarizing mirror 21 and the focusing lens 22 to form orthogonally polarized light. The scattered light is captured by the CMOS camera and transmitted to the computer to form a speckle pattern. The speckle pattern is processed to obtain the light intensity information of the corresponding speckle particles in each pixel and then processed.

[0087] The working principle of the device is as follows: when the guide wire detects a patch during the advancement process, the speckle pattern obtained by the camera will change significantly. The camera's acquisition frame rate is set to 400fps and the exposure time is 2500μs. A series of speckle patterns are acquired within 2s for each group. By analyzing the autocorrelation curve of the speckle fluctuation over time, the viscoelastic information of the patch can be obtained.

[0088] Example 2

[0089] The viscoelasticity measurement method of the interventional device described in Example 1 is combined with Figure 6 The description is as follows:

[0090] (1) The guidewire is introduced into the radial or femoral artery using a wire feeding mechanism. The magnetically controlled guide device controls the rotation, advance, and bending of the guidewire. After the guidewire reaches the target position, the catheter is slid along the guidewire to the predetermined position, and the photosensitizer is injected through the catheter.

[0091] (1-1) By precisely adjusting the position of the permanent magnet, it ensures that the guide wire accurately enters the blood vessel system to be detected, and can accurately control the position and direction of the guide wire;

[0092] (1-2) After the guide wire enters the blood vessel, the speckle pattern is obtained by the optical fiber image transmission bundle for analysis, so as to position the magnetic control guide wire and judge the relative position of the guide wire and the blood vessel wall; the mechanical arm and the permanent magnet in the magnetic control guide device are used to feedback control the magnetic field strength of the magnet on the guide wire, so as to ensure that the position and posture of the guide wire in the blood vessel meet the expectations, so as to ensure the accurate performance of the subsequent steps;

[0093] (2) After the guide wire enters the blood vessel, when the guide wire approaches the plaque in the blood vessel, the image transmission bundle front end probe 9 at the front end of the optical fiber image transmission bundle 5 will sense the existence and position of the plaque, resulting in obvious changes in the speckle image of the corresponding area;

[0094] (3) The image receiving device is used to receive and record the speckle pattern transmitted by the optical fiber image transmission bundle 5 in real time, and the image super-resolution neural network method is used to eliminate the speckle pattern noise and improve the speckle image quality;

[0095] (4) The reconstructed speckle pattern is further analyzed to obtain the viscoelasticity of the plaque;

[0096] (5) A deep learning algorithm based on convolutional neural network is used to classify plaques with different viscoelasticity through a series of speckle patterns;

[0097] (6) According to the data analysis result, the pathological characteristics of the plaque are evaluated, the abnormal part is identified, and then photodynamic therapy is performed, the power density and illumination time of the laser after passing through the optical fiber image transmission bundle are controlled by adjusting the illumination parameters of the laser, and the outgoing laser is accurately targeted to the macrophages in the abnormal plaque through the image transmission bundle front end probe at the front end of the optical fiber image transmission bundle, so as to treat the plaque.

[0098] The flow chart of the laser speckle rheology calculation plaque viscoelasticity algorithm is as shown in Figure 7 , and the specific steps are as follows:

[0099] Firstly, the frame rate of the CMOS camera is adjusted to 400 fps, the exposure time is 2500 μs, the speckle size is adjusted to twice the pixel size, the region of interest is selected, the camera noise is eliminated, the image is collected, and a series of speckle images changing with time are obtained. After the guide wire enters the blood vessel, when the guide wire approaches the plaque in the blood vessel, the optical fiber image transmission bundle front end wide-angle probe will sense the existence and position of the plaque, resulting in obvious changes in the speckle image of the corresponding area, and the speckle pattern change in the five areas receiving by the four free-form mirrors and aspherical lenses is analyzed, which is used to detect the existence and position of the plaque.

[0100] Because the core and cladding of the fiber bundle have different materials and different refractive indices, the transmission image produces grid shadows, loses part of the image information, and before analyzing viscoelasticity, the speckle pattern obtained is first reconstructed. Figure 8 The HAR-CNN workflow for removing honeycomb artifacts in fiber bundle imaging is shown in Fig. 1. Figure 8 As shown in Fig. 1, the speckle image collected by the fiber bundle is processed to remove dark noise, and the HAR-CNN convolutional neural network is trained, which includes three convolutional layers of speckle extraction, nonlinear mapping and reconstruction. The recovery performance of HAR-CNN on synthetic images is verified by superimposing an artificial honeycomb pattern on the original image, and it is used as an evaluation index to verify the HAR-CNN convolutional neural network.

[0101] Figure 9 The network architecture of HAR-CNN is shown in Fig. 2. Figure 9 As shown in Fig. 2, three convolutional layers are constructed for speckle extraction, nonlinear mapping and reconstruction layers. In the speckle extraction layer, the input is X, the weight of the convolution kernel is W1, the bias term is B1, and the output is Y1. The size of the convolution kernel in the first layer is 9, and the number of output feature maps is 64. The formula is:

[0102]

[0103] The recovery performance of HAR-CNN on synthetic images is verified by superimposing an artificial honeycomb pattern on the original image, and it is used as a direct source of quantitative evaluation. The peak signal-to-noise ratio (PSNR) and the structural similarity index (SSIM) are used for quantitative evaluation.

[0104] PSNR is used to quantify the recovery quality of the image, and to compare the intensity difference between two images pixel by pixel. The MSE is the mean square error between the true value and the estimated image. SSIM is used as a perceptual variable for the combination of three independent components of brightness, contrast and structure to quantify the degradation of image quality relative to ground truth.

[0105] In biological tissue or viscoelastic sample, the speed of internal particle fluctuation is limited by the size of sample viscoelasticity, the smaller the medium viscoelasticity, the faster the particle fluctuation, and vice versa. The scattered light of the medium internal particles will form a speckle pattern, and the intensity change of a series of speckle patterns over time can reflect the viscoelastic information of the medium. The correlation between the speckle patterns reflected by the scattering particles will gradually decrease over time, and the more intense the Brownian motion, the faster the correlation decreases. The series of speckle frames collected by laser speckle imaging can calculate the speckle intensity autocorrelation curve in time, and the normalized autocorrelation curve can be used to evaluate the motion speed of the medium internal particles. Therefore, further analysis of the reconstructed speckle pattern of the above steps, cross-correlation of the interested region in the first image and the interested region in all subsequent frame images to obtain the autocorrelation curve g2(t) of the time speckle intensity, in order to improve the time statistical accuracy of speckle, the same group of data is collected and averaged in time, as follows:

[0106]

[0107] Where I(t0) and I(t+t0) are the speckle intensities at I(t0) and I(t+t0) respectively, and < >pixels and < >t0 represent the average values of all pixels in space and time. The prerequisite for deriving the mechanical properties of the sample from the collected image frames is to extract the mean square displacement of the Brownian motion of the particles from the autocorrelation curve:

[0108]

[0109] Where k0 is the wave number, n is the refractive index of the medium, <Δr2(t)> is the mean square displacement of the scattering particles, and γ is the correction factor of the ratio of long diffusion path length to short diffusion path length. Generally, γ=5 / 3 is assumed, and this parameter will be affected by the polarization state of the received light and the size of the scattering particles. μa is the absorption coefficient, and μs' is the scattering coefficient. Substitute the calculated MSD value into the generalized Stokes-Einstein relationship to calculate the viscoelasticity, as follows:

[0110]

[0111] In the above formula, KB is the Boltzmann constant, T is the Kelvin temperature, a is the particle radius, ω=1 / t is the loading frequency, and Г represents the gamma function, The logarithmic derivative of the mean square displacement. Under the standard that the sample satisfies the validity of the generalized Stokes-Einstein relationship, the viscoelastic modulus |G*(ω)| can be derived from the MSD.

[0112] Four different biological tissue samples were selected to draw the autocorrelation curves g2(t) of different biological samples and calculate the decorrelation time τ. The evaluated tissue samples included: fat, muscle, skin and cartilage of a pig. All tissue samples were collected by the LSR method in a water bath at 37C, with a camera frame rate of 300 fps, 6000 speckle patterns were collected, with a diameter of 5mm for each tissue sample, 5 different spatial positions were collected and averaged, and the measurement results are shown in Figure 10 As shown in the results, the harder cartilage tissue has the largest decorrelation time τ (τ = 9.18s) and the slowest speckle fluctuation rate, and the softer fat tissue has the smallest decorrelation time τ (τ = 0.22s) and the fastest speckle fluctuation rate. For biological tissues, the LSR method studies the viscoelasticity of tissue samples in a wide modulus range by utilizing the Brownian motion of endogenous light scattering particles in the tissue.

[0113] Deep learning is used to classify and further analyze the speckles, as shown in Figure 11 A residual network (ResNet) is constructed to train the viscoelastic prediction and classification network (Viscoelastic prediction and classification network) by measuring the data. The network is used to quickly process the image and extract the viscoelasticity-related information contained therein, and the real-time viscoelasticity data at this time is given by the speckle pattern, and the image is classified into non-speckle, benign speckle and malignant speckle. This simplifies the large number of complex operations on the speckle pattern, realizes the fast response of the system, improves the data processing capacity of the system, effectively extracts the key information in the image, avoids interference from other invalid information, and enhances the generalization ability of the system, which can effectively adapt to changing physiological scenarios.

[0114] The sample is collected at a camera frame rate of 400 fps, and the autocorrelation function of the speckle fluctuation is established by analyzing the time-varying speckle pattern. This process can reveal the decorrelation time of different speckle regions. Then, according to the decorrelation time, the speckle regions are classified to obtain the corresponding real-time viscoelasticity data and speckle category, and a data set is constructed. The network is trained according to the 9:1 ratio of training set and validation set, and a practical viscoelasticity prediction and classification network is obtained. The input of the network is a group of 256x256 size speckle patterns, and the output is real-time viscoelasticity value and speckle classification. Each group of images is first processed through a group of 7x7 convolution layers, batch normalization, activation function and 3x3 pooling layer, then through 8 residual blocks, and finally through a global average pooling layer to obtain the features of the image.

[0115] Among them, the residual block is divided into two categories: A type is to pass through a convolution on the shortcut path in addition to twice convolution on the main path, which adapts to the dimension change of the feature map in the network; B type is to directly jump connect with the main path which has passed twice convolution. In the above network structure, the convolution and pooling calculation is particularly key, through which the final regression and classification results can be obtained. Convolution calculation extracts the features of the image by sliding a matrix called convolution kernel over the image and performing weighted summation on the pixels in each covered area. Batch normalization and activation function are followed to improve the stability and nonlinearity of the network. The calculation method is as follows:

[0116]

[0117] Where: o(i, j) is the element of the output feature map, I(s·i+m, s·j+n) is the element of the input image matrix, where s is the convolution kernel step size, m and n are the dimension indexes of the convolution kernel, and K(m, n) is the element of the convolution kernel (or filter) matrix.

[0118] Pooling calculation is rich in variety, and the maximum pooling and global average pooling are mainly used in this network. The maximum pooling retains the most significant features by extracting the maximum value from the local region of the feature map. This process is completed by sliding a fixed size window over the entire feature map and selecting the maximum element in each window. The calculation method is as follows:

[0119]

[0120] Where: o(i, j) is the element of the output feature map, I(s·i+m, s·j+n) is the element of the input image matrix, where s is the convolution kernel step size, m and n are the dimension indexes of the convolution kernel, and P is the size of the pooling window.

[0121] And the global average pooling calculates the average value of each channel of the feature map and flattens these average values into a one-dimensional vector. The fully connected layer realizes high abstraction and integration from image to feature by multiplying the one-dimensional vector with the weight matrix and adding the bias term, and then performing nonlinear transformation through the activation function, so as to complete the classification or regression task.

[0122] According to the data analysis result, the pathological characteristics of the plaque are evaluated, it is judged whether the plaque needs treatment, if the plaque needs treatment, the light power density of the laser is adjusted, the laser power required for treatment is input to activate the photosensitizer, the highly selective treatment of the abnormal part is realized, the damage to the surrounding healthy tissue is avoided, after the treatment is completed, the laser power is adjusted to the required power for measurement according to the principle of laser speckle rheology, then the viscoelasticity of the plaque after treatment is measured, the effect after the photodynamic therapy is checked, the in-situ evaluation is performed, if the treatment effect is good, the guide wire continues to advance to detect, if the treatment effect is poor, the plaque is treated by the method of photodynamic therapy.

[0123] The above only describes the preferred embodiments of the present application, and it should be noted that those skilled in the art can make several improvements and refinements without departing from the principles of the present application, and these improvements and refinements should also be considered as the protection scope of the present application.

Claims

1. An interventional instrument, characterized by: The guide wire (4), the image fiber bundle (5) is used as the main part of the guide wire (4), the outer layer of the image fiber bundle (5) is inlaid with a magnet (6), the magnet (6) is composed of two magnet segments (11), the outer layer of the magnet (6) is provided with a protective sleeve (7), and the outer layer of the protective sleeve is plated with a hydrophilic coating (8). The image fiber bundle front end probe (9) includes four free curved surfaces and one aspheric lens (9), the material of the image fiber bundle front end probe (9) is photoresist SU-8, the four free curved surfaces are coated with a reflective coating, the top of the four free curved surfaces is fixed with the aspheric lens (9), and the free curved surface of the image fiber bundle front end probe (9) is coupled to the front end of the image fiber bundle. The magnetic control guiding device includes a wire feeding mechanism (3), a mechanical arm (1) and a permanent magnet (2), the wire feeding mechanism (3) and the mechanical arm (1) are arranged at intervals, the permanent magnet (2) is fixed at the end of the mechanical arm (1), and the driving clamping part of the wire feeding mechanism (3) is connected with the guide wire (4). The laser irradiation device includes a laser (15), a first polarizing mirror (16), a beam expander (17) and a reflecting mirror (18), the front end of the laser (15) is sequentially provided with the first polarizing mirror (16), the beam expander (17) and the reflecting mirror (18). The image receiving device includes an objective lens (19), a beam splitter (20), a second polarizing mirror (21), a focusing lens (22) and a CMOS camera (23), the side surface of the reflecting mirror (18) is provided with the beam splitter (20), the beam splitter (20) divides the light beam into two paths, the two light beams propagate on the two sides of the beam splitter (20) respectively, one side of the beam splitter (20) is provided with the objective lens (19), the end of the image fiber bundle (5) is coupled with the objective lens (19), and the other side of the beam splitter (20) is sequentially provided with the second polarizing mirror (21), the focusing lens (22) and the CMOS camera (23). The hydrophilic coating includes a PUA coating (12), a PVP coating (13) and a hyaluronic acid gel film (14), the PUA coating (12) is covered on the surface of the protective sleeve (7) by using ultraviolet curing technology, the PVP coating (13) is polymerized on the PUA coating (12) by using ultraviolet curing technology, and the hyaluronic acid gel film (14) is coated on the PVP coating (13).

2. The interventional instrument of claim 1, wherein: The image fiber bundle (5) is a polymer image fiber bundle, the core number of the image fiber bundle (5) is 13000, the numerical aperture is 0.5, the diameter of the image fiber bundle (5) is 1 mm, the diameter of the protective sleeve (7) is 1.25 mm, and the material of the protective sleeve (7) is silicone rubber.

3. The interventional instrument of claim 1, wherein: The magnet (11) is attached to the surface of the image fiber bundle (5) by using femtosecond laser processing technology, the magnet (11) is an axially polarized cylindrical N52 neodymium magnet, and the two magnet segments (11) are respectively attached to the front end and the middle segment of the image fiber bundle (5).

4. The interventional instrument of claim 1, wherein: ​ 5. The interventional instrument of claim 1, wherein: The four free-form surfaces and aspherical lenses of the image transmission bundle front end probe (9) are integrated structures, printed directly on the end face of the optical fiber image transmission bundle (5) by femtosecond laser two-photon polymerization technology, and the free-form surface reflective coating is made of gold material and deposited accurately by physical vapor deposition technology.

6. The interventional instrument of claim 1, wherein: The laser (15) is a helium-neon laser with a wavelength of 632 nm.

7. The interventional instrument of claim 1, wherein: When working: (1) The guide wire (4) is introduced into the radial artery or femoral artery by the wire feeding mechanism, and the magnetic control guide device controls the rotation, advancement and bending of the guide wire. After the guide wire reaches the target position, the catheter is slid along the guide wire to the predetermined position, and the photosensitizer is injected through the catheter; (2) After the guide wire enters the blood vessel, when the guide wire approaches the plaque in the blood vessel, the image transmission bundle front end probe (9) at the front end of the optical fiber image transmission bundle (5) will sense the existence and position of the plaque, causing the speckle image of the corresponding area to change significantly; (3) The speckle pattern transmitted by the optical fiber image transmission bundle (5) is received and recorded in real time by the image receiving device, the speckle noise is removed by the image super-resolution neural network method, and the speckle image quality is improved; (4) The reconstructed speckle pattern is further analyzed to obtain the viscoelasticity of the plaque; (5) A deep learning algorithm based on convolutional neural network is used to classify plaques with different viscoelasticity through a series of speckle patterns; (6) According to the data analysis results, the pathological characteristics of the plaque are evaluated, and after identifying the abnormal part, photodynamic therapy is performed. By adjusting the light parameters of the laser, the power density and illumination time of the laser after passing through the optical fiber image transmission bundle are controlled, and the outgoing laser is accurately targeted at the macrophages in the abnormal plaque through the image transmission bundle front end probe at the front end of the optical fiber image transmission bundle.

8. The interventional instrument of claim 7, wherein: The specific steps of step (1) include: (1-1) The position of the permanent magnet at the end of the mechanical arm is accurately adjusted to ensure that the guide wire accurately enters the blood vessel system to be detected and the position and direction of the guide wire can be accurately controlled; (1-2) After the guide wire enters the blood vessel, the speckle pattern is obtained by the optical fiber image transmission bundle for analysis, so as to position the magnetic guide wire and judge the relative position of the guide wire and the blood vessel wall; the magnetic field strength of the magnet on the guide wire is feedback controlled by the mechanical arm and the permanent magnet in the magnetic guide device, so as to ensure that the position and posture of the guide wire in the blood vessel meet the expectations, so as to ensure the accurate performance of the subsequent steps.

9. The interventional instrument of claim 7, wherein: The specific steps of step (3) include: (3-1) Adjust the frame rate and exposure time of the CMOS camera, adjust the speckle size to be twice the size of a pixel, select the region of interest to collect images, and obtain a series of speckle images varying with time; (3-2) The speckle images obtained in step (3-1) are preliminarily removed by noise using a single-image unsupervised denoising convolutional neural network method; (3-3) The preliminarily denoised speckle images obtained in step (3-2) are reconstructed by a honeycomb-artifact removal convolutional neural network algorithm, including three convolutional layers: plaque extraction, nonlinear mapping and reconstruction; (3-4) The reconstruction performance of HAR-CNN on synthetic images is verified by superimposing artificial honeycomb patterns on the original images, and the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) are used for quantitative evaluation. The PSNR is used to quantify the recovery quality of the image, and the intensity difference between the two images is compared pixel by pixel. The SSIM is used to quantify the image quality relative to the direct source degradation.

10. The interventional instrument of claim 7, wherein: The specific steps of the step (4) include: (4-1) Further analysis of the reconstructed speckle pattern in step (3), and cross-correlation of the region of interest in the first frame image with the region of interest in all subsequent frame images to obtain the autocorrelation curve g2(t) of the time speckle intensity. To improve the accuracy of speckle time statistics, the same data set is collected multiple times and averaged in time; (4-2) Fit the autocorrelation curve with a single exponential decay function, and extract the decorrelation time when the correlation drops to 70%, which is used for qualitative analysis of speckles with different viscoelasticity; (4-3) Extract the mean square root displacement MSD from the autocorrelation curve, which reflects the Brownian motion characteristics of the particles inside the speckle; (4-4) Substitute the MSD calculated in step (4-3) into the Stokes-Einstein relationship to quantitatively calculate the viscoelasticity of the speckle.

Images