Interventional instrument and viscoelasticity measuring method

Abstract

The invention provides an intrusive instrument and a viscoelasticity measuring method. Based on a laser speckle rheology technology, an optical fiber image transmitting bundle is used as a guide wire main body, optical signals are transmitted, speckle images changing along with time are collected through a high-speed camera, and the viscoelasticity of the instrument is measured by analyzing time-varying speckle signals. The method comprises the following steps: establishing a relation between speckle fluctuation and mean square displacement of scattering particles in a viscoelastic substance, quantitatively calculating viscoelasticity information of the detected substance, measuring plaque viscoelasticity, destroying abnormal arterial endothelial cells and inflammatory cells in plaques by using a photodynamic therapy method, and determining the plaque viscoelasticity. The purposes of biological tissue viscoelasticity quantitative detection, abnormal part recognition and photodynamic therapy are achieved, viscoelasticity characteristics of plaques in blood vessels can be effectively detected, abnormal parts in the blood vessels can be recognized, photodynamic therapy is conducted on atherosclerotic plaques and other abnormal parts through laser, the complexity of surgical operation is reduced, and the photodynamic therapy efficiency is improved. The development of the medical technology is promoted, and the continuous upgrading and optimization of the medical service are promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of medical instruments, in particular to an interventional instrument and a viscoelasticity measurement method. Background Art

[0002] Acute Coronary Syndrome (ACS) refers to a group of clinical symptoms caused by a sharp decrease or complete interruption of coronary blood flow. The main cause of ACS is the rupture or ulceration of coronary plaques, which leads to thrombosis and then obstruction of coronary blood flow. This may lead to myocardial ischemia, damage or even necrosis, and in severe cases may lead to arrhythmia, heart failure or even death. The measurement of intravascular plaque viscoelasticity is crucial for identifying plaques at risk of rupture and thus reducing the incidence of myocardial infarction. Current technologies such as intravascular ultrasound, optical coherence tomography, infrared spectroscopy imaging and coronary angiography can evaluate the microstructure and composition characteristics of key plaques, but they cannot warn the location of plaques during guidewire advancement and diagnose and treat 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 danger of plaques. As an emerging treatment method, photodynamic therapy has great potential. In addition to being used to treat 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-inflammatory and anti-thrombotic, 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, provide a more stable vascular wall environment and prevent arterial restenosis. In addition, the integration of diagnosis and treatment of intravascular atherosclerotic plaques during the guidewire advancement process can help doctors better identify and locate lesions, improve medical quality and efficiency, reduce medical risks, improve patient experience, and promote medical technology innovation.

[0004] Laser speckle rheology (LSR) is a new type of optical viscoelasticity measurement technology that can achieve rapid, non-destructive, highly sensitive and non-contact detection of the viscoelasticity of biological tissues. This technology analyzes the time-varying speckle signal, establishes the connection between the speckle fluctuation and the mean square displacement of the scattered particles in the viscoelastic material, and quantitatively calculates the viscoelastic information of the measured material to achieve the purpose of quantitative detection of the viscoelasticity of biological tissues. The current integrated diagnosis and treatment probe combines optical imaging and laser treatment. In 2022, Fan Yingwei and others invented an optical coherence tomography-guided laser minimally invasive diagnosis and treatment endoscope probe. By adjusting the rotation of the reflector to change the laser emission angle, the imaging laser fiber is used to determine the location of the lesion, and the ablation laser fiber is used for treatment, realizing the integration of in vivo diagnosis and treatment. In 2022, Liao Hongen and others proposed an integrated diagnosis and treatment probe that couples imaging light and treatment light into the same optical fiber through a dichroic mirror, solving the poor matching of diagnosis and treatment in the existing technology and the defects of large monitoring errors, but the complex structure is not conducive to the miniaturization of the device. The application of laser speckle rheology technology in interventional clinical practice can realize the detection and diagnosis of lesion locations, simplify the system structure and realize the integration of diagnosis and treatment of lesion locations. However, it is still necessary to solve problems such as small imaging range, non-real-time imaging, and grid shadows in the transmitted image and loss of some image information due to the different materials of the cladding and core layers of the image transmission beam. Summary of the invention

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

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

[0007] In order to solve the above technical problems, the technical solution of the present invention is:

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

[0009] The guide wire (4) and the optical fiber image transmission bundle (5) serve as the main body 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 sections of magnets (11); the outer layer of the magnet (6) is provided with a protective cover (7); the outer layer of the protective cover is plated with a hydrophilic coating (8);

[0010] The image transmission bundle front end probe (9) comprises four free-form surfaces (serving as reflectors) and an aspheric lens (9). The material of the image transmission bundle front end probe (9) is photoresist SU-8. The four free-form surfaces are coated with a reflective coating for reflecting light emitted from the optical fiber image transmission bundle (5) onto the side wall for illumination. The tops of the four free-form surfaces are fixed with an aspheric lens (9) for receiving scattered light signals from the front end of the probe. The free-form surfaces of the image transmission bundle front end probe (9) are 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 to the end of the mechanical arm (1); the active clamping component of the wire feeding mechanism (3) is connected to the guide wire (4); during use, the wire feeding mechanism and the mechanical arm are on both sides of the operating table, 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 part of the human body;

[0012] The laser irradiation device comprises a laser (15), a first polarizer (16), a beam expander (17) and a reflector (18); the front end of the laser (15) is provided with the first polarizer (16), the beam expander (17) and the reflector (18) in sequence;

[0013] The image receiving device comprises an objective lens (19), a beam splitter (20), a second polarizer (21), a focusing lens (22), and a CMOS camera (23). The side of the reflector (18) is provided with a beam splitter (20). The beam splitter (20) splits a light beam into two paths. The two paths of light are respectively propagated 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 transmission bundle (5) is coupled with the objective lens (19). The other side of the beam splitter (20) is provided with a second polarizer (21), a focusing lens (22), and a CMOS camera (23) in sequence.

[0014] Preferably, in the above-mentioned interventional instrument, the hydrophilic coating includes 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 cover (7) by ultraviolet curing technology, the PVP coating (13) is polymerized on the PUA coating (12) by ultraviolet curing technology, and the hyaluronic acid gel film (14) is coated on the PVP coating (13).

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

[0016] Preferably, in the above-mentioned interventional instrument, the optical fiber imaging bundle (5) is a polymer optical fiber imaging bundle, the core number of which is 13000, the numerical aperture is 0.5, the diameter of the optical fiber imaging bundle (5) is 1 mm, and the diameter of the protective cover (7) is 1.25 mm.

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

[0018] Preferably, in the above-mentioned interventional instrument, the four free-form surfaces and the aspherical lens of the front-end probe (9) of the imaging bundle are an integrated structure, which are directly printed onto the end face of the optical fiber imaging bundle (5) using femtosecond laser two-photon polymerization technology, and gold (Au) material is used as the free-form surface reflective coating, and the precise deposition of the coating is achieved through physical vapor deposition (PVD) technology.

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

[0020]

[0021] Where: a0 represents the height constant of the vertex of the aspheric lens, c represents the curvature, k represents, and ai represents the coefficient in the polynomial expansion, which is used to describe the high-order aspheric correction term. The parameters of the aspheric lens are: a0 = 0.2 mm, c = 0.459 mm -1 , k = 2.035, a2 = 0.171, a4 = 2.374, a6 = -3.723. The free-form surface can be described by the following expression:

[0022]

[0023] The off-axis eccentricity and surface parameters c, k and y, y of the optical surface 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, in 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 and interact with the photosensitizer drug to achieve photodynamic therapy for intravascular atherosclerotic plaques or promote the healing of damaged endothelial cells in blood vessels, thereby providing a more stable vascular wall environment.

[0027] Preferably, in the above-mentioned interventional instrument, the magnetic field strength of the magnet on the guide wire is feedback-adjusted 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 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 pattern of the speckle pattern.

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

[0029] (1) A guide wire is introduced into the radial artery or femoral artery using a wire feeding mechanism, and a magnetic control guide device controls the rotation, advancement, and bending of the guide wire. After the guide wire reaches the target position, a catheter is slid along the guide wire to a predetermined position, and a 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 imaging bundle front end probe (9) at the front end of the optical fiber imaging bundle (5) will sense the existence and position of the plaque, causing the speckle image of the corresponding area to change significantly;

[0031] (3) using an image receiving device to receive and record in real time the speckle pattern transmitted by the optical fiber image transmission bundle (5), and using an image super-resolution neural network method to eliminate speckle pattern noise and improve the quality of the speckle image;

[0032] (4) Further analysis of the reconstructed speckle pattern to obtain the plaque viscoelasticity;

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

[0034] (6) Evaluate the pathological characteristics of the plaque based on the data analysis results, and perform photodynamic therapy after identifying the abnormal area. By adjusting the illumination parameters of the laser, the power density and illumination time of the laser after passing through the fiber optic imaging bundle are controlled. The outgoing laser is precisely targeted to the macrophages in the abnormal plaque through the front-end probe of the fiber optic imaging bundle to treat the plaque.

[0035] Preferably, in the above-mentioned method for measuring viscoelasticity of an interventional device, the specific steps of step (1) include:

[0036] (1-1) By precisely adjusting the position of the permanent magnet at the end of the robotic arm, the guidewire is ensured to accurately enter the vascular system to be inspected, and the position and direction of the guidewire can be precisely controlled;

[0037] (1-2) After the guidewire enters the blood vessel, the speckle pattern is acquired through the fiber optic imaging bundle for analysis, so as to locate the magnetically controlled guidewire and determine the relative position of the guidewire and the blood vessel wall. The magnetic field strength of the magnet on the guidewire is feedback-controlled using the robotic arm and permanent magnet in the magnetically controlled guidance device to ensure that the position and posture of the guidewire inside the blood vessel are in line with expectations, thereby ensuring the accuracy of subsequent steps.

[0038] Preferably, in the above-mentioned method for measuring viscoelasticity of an interventional instrument, the specific steps of step (3) include:

[0039] (3-1) Adjust the frame rate and exposure time of the CMOS camera, adjust the speckle size to twice the pixel size, select a region of interest to collect images, and obtain a series of speckle images that change over time;

[0040] (3-2) using a single image unsupervised denoising convolutional neural network method to preliminarily remove noise from the speckle image obtained in step (3-1);

[0041] (3-3) reconstructing the preliminary denoised speckle image obtained in step (3-2) using a honeycomb-artifact removal convolutional neural network algorithm, including three convolutional layers: patch extraction, nonlinear mapping, and reconstruction;

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

[0043] Preferably, in the above-mentioned method for measuring viscoelasticity of an interventional instrument, the specific steps of step (4) include:

[0044] (4-1) further analyzing the speckle pattern reconstructed in step (3), cross-correlating 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 temporal speckle intensity. To improve the temporal statistical accuracy of the speckle pattern, the same set of data is collected multiple times and averaged in time.

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

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

[0047] (4-4) Substitute the MSD calculated in step (4-3) into the Stokes-Einstein equation to quantitatively calculate the viscoelasticity of the plaque.

[0048] Beneficial effects:

[0049] The above-mentioned interventional device is based on laser speckle rheology technology, uses a fiber optic image bundle as the guide wire body, and transmits optical signals at the same time. The speckle image that changes with time is collected by a high-speed camera. By analyzing the time-varying speckle signal, the connection between the speckle fluctuation and the mean square displacement of the scattering particles in the viscoelastic material is established, the viscoelastic information of the measured substance is quantitatively calculated, the viscoelasticity of the plaque is measured, and the photodynamic therapy method is used to destroy abnormal arterial endothelial cells and inflammatory cells in the plaque, so as to achieve the purpose of quantitative detection of the viscoelasticity of biological tissues, identification of abnormal sites and photodynamic diagnosis and treatment. It can effectively detect the viscoelastic characteristics of plaques in blood vessels, identify abnormal sites, and use lasers to perform photodynamic therapy on atherosclerotic plaques, reduce plaques and reduce risks, which will help promote the development of medical technology and promote the continuous upgrading and optimization of medical services.

[0050] The interventional device can perform all-round detection of plaques or tumors in blood vessels and use photodynamic therapy to treat atherosclerotic plaques, thrombi or tumors, which is of great significance for accurate identification and efficient treatment of abnormal parts. By analyzing the morphology or changes of the laser speckle pattern, the position of the magnetically controlled 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, reducing the level of radiation exposure during surgery, and 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 intravascular plaques in real time, providing doctors with more accurate lesion localization and surgical guidance, thereby improving the success rate of surgery and treatment effects.

[0052] 2. Using the fiber optic imaging bundle as the main body of the guidewire, flexible, rapid, non-destructive, and highly sensitive measurements of plaque viscoelasticity are achieved, providing doctors with an important reference for plaque stability and guiding the formulation of personalized treatment strategies.

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

[0054] 4. The use of a large-angle imaging beam front-end probe can perform all-round detection of plaques in blood vessels without rotating the guide wire, shortening the operation time and reducing patient discomfort and surgical risks.

[0055] 5. The image super-resolution neural network method is used to process speckle images, which improves image quality and data accuracy, and provides doctors with a more comprehensive basis for plaque assessment and treatment decision-making.

[0056] 6. The application of magnetic control guidance device enables precise control of the entry, rotation and movement of the guide wire. Combined with the real-time monitoring function, it 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 surgery, protecting the health and safety of medical staff and patients.

[0057] 7. Integrated photodynamic diagnosis and treatment: By integrating photodynamic therapy technology into interventional devices, an integrated diagnosis and treatment medical model is achieved, which can not only detect abnormal parts, but also 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 THE DRAWINGS

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

[0059] Figure 2 is a schematic diagram of the guidewire structure;

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

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

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

[0063] Figure 6 It is a flow chart of integrated diagnosis and treatment of magnetically controlled guidewires;

[0064] Figure 7 It is the flow chart of the algorithm for calculating the viscoelasticity of plaques using laser speckle rheology;

[0065] Figure 8 It is a schematic diagram of the HAR-CNN workflow for cellular artifact removal;

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

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

[0068] Fig.11 It is a flowchart of the deep learning algorithm for classifying plaques.

[0069] In the figure: 1-robot arm; 2-permanent magnet; 3-wire feeding mechanism; 4-guide wire; 5-optical fiber image bundle; 6-magnet layer; 7-protective cover; 8-hydrophilic coating; 9-front end probe of image bundle; 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 DESCRIPTION

[0070] The interventional instrument and viscoelasticity measurement method of the present invention are described below with reference to the embodiments and drawings.

[0071] Example 1

[0072] An interventional device includes a guide wire 4, an image transmission beam front-end probe 9, a magnetic control guidance device, a laser irradiation device and an image receiving device, wherein:

[0073] The guide wire 4 is as Figure 2 As shown, the polymer optical fiber imaging bundle 5 is the main part of the guide wire 4, the outer layer of the optical fiber imaging bundle 5 is inlaid with a magnet 6, the magnet 6 is composed of two sections of magnets 11, the outer layer of the magnet 6 is provided with a protective cover 7, the outer layer of the protective cover is plated with a hydrophilic coating 8, the core number of the optical fiber imaging bundle 5 is 13000, the numerical aperture is 0.5, the diameter of the optical fiber imaging bundle 5 is 1mm, and the diameter of the protective cover 7 is 1.25mm; the distribution of the magnet 11 is as shown in Figure 3 As shown, the preparation method of the magnet is: using the femtosecond laser to induce local heating effect, a micro-processing scene is formed in a specific area on the surface of the optical fiber, which is conducive to the attachment of magnetic materials, and the magnetic materials are attached to the surface of the optical fiber imaging bundle 5 to form a hollow cylindrical magnet with strong magnetism. The magnet 11 is a relatively axially polarized cylindrical N52 neodymium magnet with a length of 6 mm. The two sections of the magnet 11 are respectively attached to the front end and the middle section of the optical fiber imaging bundle 5, and the two sections of the magnet 11 are 21 mm apart; the hydrophilic coating is as shown in FIG. Figure 4 As shown, the protective cover 7 of the optical fiber imaging bundle is made of silicone rubber (as the base material covered by the coating), on which are fixed in sequence a PUA coating 12 as the composite coating base, a PVP coating 13 as the composite coating surface, and a hyaluronic acid gel film 14 for increasing the lubricity and bioaffinity of the coating in special scenarios of human blood vessels. The silicone rubber is incompletely cured and combined with the PUA coating by ultraviolet light curing, and the PVP coating is polymerized with the PUA coating by ultraviolet light curing to form a PUA-PVP composite surface, and finally the hyaluronic acid film is covered by a dip-pull method to form a hydrophilic coating;

[0074] The front-end probe 9 of the imaging bundle includes four free-form surfaces (as reflectors) and an aspheric lens 9. The material of the front-end probe 9 of the imaging bundle is photoresist SU-8. The four free-form surfaces are coated with a reflective coating, which is used to reflect the light emitted from the optical fiber imaging bundle 5 to the side wall for illumination, and couple the scattered light diffusely reflected from the surface of the plaque into the optical fiber imaging bundle to form a speckle pattern on the camera; an aspheric lens 9 is fixed on the top of the four free-form surfaces to receive the scattered light signal from the front end of the probe. When the front end of the guide wire detects a plaque, the surface of the plaque undergoes diffuse reflection, and the aspheric lens can couple the reflected scattered light into the optical fiber imaging bundle for transmission. The function of the aspheric lens is to improve the coupling efficiency of the light beam and focus the light beam into the imaging bundle, thereby presenting a clear pattern on the camera. The aspheric lens can be described by the following expression:

[0075]

[0076] Where: a0 represents the height constant of the vertex of the aspheric lens, c represents the curvature, k represents, and ai represents the coefficient in the polynomial expansion, which is used to describe the high-order aspheric correction term. The parameters of the aspheric lens are: a0 = 0.2 mm, c = 0.459 mm -1 , k = 2.035, a2 = 0.171, a4 = 2.374, a6 = -3.723. The free-form surface can be described by the following expression:

[0077]

[0078] In the formula, c x and c y is the radius of curvature of the surface in the XZ and YZ planes, k x and k y are the quadratic aspheric coefficients of the surface in the XZ and YZ planes. The highest term of the xy polynomial is limited to 4. The free-form surface can be described by the following expression:

[0079]

[0080] The coefficient of the odd-order term of x in the polynomial is 0. To ensure the feasibility of processing, the highest term of the xy polynomial is limited to 4. When optimizing the design, 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 other polynomial coefficients are set to 0. The off-axis eccentricity of the optical surface and the surface parameters c, k and y, y 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] Eccentricity in y direction / mm -0.014 Z direction eccentricity / mm 0.176 Alpha Tilt / ° 0.664 Curvature radius / mm 0.582 k -0.45827 y-term coefficient -0.08307 <![CDATA[x 2 Term coefficient]]> 0.04517 <![CDATA[y 2 Term coefficient]]> 0.16009 <![CDATA[x 2 y 2 Term coefficient]]> -0.18887 <![CDATA[y 3 Term coefficient]]> -0.12663 <![CDATA[x 4 Term coefficient]]> 0.12464 <![CDATA[x 2 y 2 Term coefficient]]> -0.05466 <![CDATA[y 4 Term coefficient]]> 0.22077

[0082] This design enables the guidewire to simultaneously detect plaque information on the side wall of the blood vessel and the front end of the guidewire during advancement, and all-round detection can be achieved without rotating the guidewire, thereby simplifying the system structure and sensing at a large angle. The free-form surface of the front-end probe 9 of the image transmission bundle is coupled to the front end of the optical fiber image transmission bundle. The four free-form surfaces and the aspherical lens of the front-end probe 9 of the image transmission bundle are an integrated structure, which is directly printed on the end face of the optical fiber image transmission bundle using femtosecond laser two-photon polymerization technology, and gold (Au) material is used as the free-form surface reflective coating, and the precise deposition of the coating is achieved through physical vapor deposition (PVD) technology.

[0083] Magnetic control guidance device Figure 1 As shown, it includes a wire feeding mechanism 3, a robotic arm 1 and a permanent magnet 2. The wire feeding mechanism is composed of an active clamping mechanism and a dual-motion modular roller cartridge mechanism (the component structure refers to A Vascular Intervention AssistDevice Using Bi-Motional Roller Cartridge Structure and Clinical Evaluation, Biosensors 2021, 11, 329.), an active clamping mechanism clamps the guide wire, and a double-motion modular roller drum mechanism pushes the magnetically controlled guide wire into the interventional blood vessel. The wire feeding mechanism 3 and the robotic arm 1 are arranged at intervals, and the permanent magnet 2 is fixed at the end of the robotic arm 1. The active clamping component of the wire feeding mechanism 3 is connected to the middle of the guide wire 4. During use, the wire feeding mechanism and the robotic arm are on both sides of the operating table, and the wire feeding mechanism is close to the lower part of the human body and is electrically connected to the vascular interventional surgery system. The main working range of the robotic arm is in the upper half of the human body. A permanent magnet (EMM) is fixed at one end of the robotic arm, and the other end is fixed to the middle of one side of the vascular interventional surgery workbench. The permanent magnet 2 is an axially polarized cylindrical neodymium magnet of D50×60mm, and its position change is controlled by the robotic arm, thereby controlling the magnetic field change. After the guide wire is pushed into the wire feeding mechanism 3, the active clamping component of the wire feeding mechanism clamps the guide wire and pushes it into the interventional blood vessel. The magnetic field strength of the magnet on the guide wire guided by the mechanical arm and the permanent magnet at its end in the magnetic control guiding device is feedback-adjusted 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 of the blood vessel wall. The position of the guide wire 4 relative to the blood vessel wall is obtained by analyzing the variation law of the speckle pattern.

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

[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. A beam splitter 20 is provided on the side of the reflector 18. The beam splitter 20 splits the light beam into two paths. The two paths of light propagate on both sides of the beam splitter 20, respectively. An objective lens 19 is provided on one side of the beam splitter 20. The end of the optical fiber image transmission bundle 5 is coupled with the objective lens 19. A second polarizer 21, a focusing lens 22, and a CMOS camera 23 are provided on the other side of the beam splitter 20 in sequence.

[0086] The above-mentioned He-Ne laser outputs 632.8nm randomly polarized light, which is changed in polarization state by the first polarizer 16, and then expanded in spot by the beam expander 17, and then coupled to the optical fiber imaging bundle by the beam splitter 20 and the objective lens 19, and the spot is focused on the surface of the sample to be measured by the optical fiber imaging bundle. The light beam generates scattered light by scattering particles inside the sample, and the scattered light returns to the beam splitter 20 through the optical fiber imaging bundle, and then changes its polarization state by the second polarizer 21 and the focusing lens 22 to form orthogonal polarized light. The scattered light is captured by the CMOS camera and transmitted to the computer to form a speckle pattern, and the speckle pattern is processed to obtain the light intensity information of the corresponding speckle particles in each pixel and process it.

[0087] The working principle of the device is as follows: when the guide wire detects a plaque during advancement, the speckle pattern obtained by the camera will change significantly. The camera acquisition frame rate is set to 400fps, the exposure time is 2500μs, and a series of speckle patterns within 2s are collected in each group. The viscoelastic information of the plaque is obtained by analyzing the autocorrelation curve of the speckle fluctuation that changes with time.

[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) A guide wire is introduced into the radial artery or femoral artery using a wire feeding mechanism. 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 a photosensitizer is injected through the catheter:

[0091] (1-1) By precisely adjusting the position of the permanent magnet, the guide wire is ensured to accurately enter the vascular system to be detected, and the position and direction of the guide wire can be precisely controlled;

[0092] (1-2) After the guidewire enters the blood vessel, the speckle pattern is obtained through the fiber optic imaging bundle for analysis, so as to locate the magnetically controlled guidewire and determine the relative position of the guidewire and the blood vessel wall; the magnetic field strength of the magnet on the guidewire is feedback-controlled using the mechanical arm and permanent magnet in the magnetically controlled guidance device to ensure that the position and posture of the guidewire inside the blood vessel meet expectations, so as to ensure the accuracy of subsequent steps;

[0093] (2) After the guide wire enters the blood vessel, when the guide wire approaches the plaque in the blood vessel, the imaging bundle front-end probe 9 at the front end of the optical fiber imaging bundle 5 will sense the existence and position of the plaque, causing the speckle image of the corresponding area to change significantly;

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

[0095] (4) Further analysis of the reconstructed speckle pattern to obtain the plaque viscoelasticity;

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

[0097] (6) Evaluate the pathological characteristics of the plaque based on the data analysis results, and perform photodynamic therapy after identifying the abnormal area. By adjusting the illumination parameters of the laser, the power density and illumination time of the laser after passing through the fiber optic imaging bundle are controlled. The outgoing laser is precisely targeted to the macrophages in the abnormal plaque through the front-end probe of the fiber optic imaging bundle to treat the plaque.

[0098] The flowchart of the algorithm for calculating the viscoelasticity of plaques using laser speckle rheology is as follows: Figure 7 As shown, the specific steps are as follows:

[0099] First, the frame rate of the CMOS camera was adjusted to 400fps, the exposure time was 2500μs, the speckle size was adjusted to twice the pixel size, the region of interest was selected, the camera noise was eliminated to collect images, and a series of speckle images that change over time were obtained. After the guidewire enters the blood vessel, when the guidewire approaches the plaque in the blood vessel, the large-angle probe at the front end of the fiber optic imaging bundle will sense the presence and position of the plaque, causing a significant change in the speckle image of the corresponding area. The speckle pattern changes received by the four free-form surface reflectors and the aspherical lens in a total of 5 areas are analyzed to detect the presence and position of the plaque.

[0100] Since the core and cladding of the optical fiber image transmission bundle are made of different materials and have different refractive indices, the transmitted image produces a grid shadow and loses some image information. Before analyzing the viscoelasticity, the acquired speckle pattern is first reconstructed. Figure 8 Schematic diagram of the HAR-CNN workflow for honeycomb artifact removal in fiber bundle imaging. Figure 8 As shown in the figure, the speckle image collected by the fiber-optic imaging bundle is subjected to dark noise removal and trained in the HAR-CNN convolutional neural network, whose architecture includes three convolutional layers: patch extraction, nonlinear mapping, and reconstruction. The restoration performance of HAR-CNN on the synthetic image is verified by superimposing an artificial honeycomb pattern on the original image, and it is used as an evaluation indicator to verify the HAR-CNN convolutional neural network.

[0101] Fig. 9 This is a schematic diagram of the network architecture of HAR-CNN, such as Fig. 9 As shown in the figure, three convolutional layers are constructed for patch extraction, nonlinear mapping and reconstruction layers. In the patch 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 convolution kernel size of the first layer is 9, the number of output feature maps is 64, and the formula is:

[0102]

[0103] Artificial honeycomb patterns are superimposed on the original images to verify the restoration performance of HAR-CNN on the synthetic images and used as a direct source for quantitative evaluation. The quantitative evaluation is performed using two indicators: peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM).

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

[0105] In biological tissues or viscoelastic samples, the speed of internal particle fluctuations is limited by the size of the sample's viscoelasticity. The smaller the medium's viscoelasticity, the faster the particles fluctuate, and vice versa. The scattered light of particles inside the medium will form a speckle pattern. The temporal changes in the light intensity of a series of speckle patterns can reflect the viscoelastic information of the medium. The correlation between the speckle patterns reflected by the scattered particles will gradually decrease over time. The more intense the Brownian motion, the faster the correlation decreases. A series of speckle frames collected by laser speckle imaging can calculate the speckle intensity autocorrelation curve in time. After normalizing the autocorrelation curve, it can be used to evaluate the movement speed of particles inside the medium. Therefore, the speckle pattern reconstructed in the above steps is further analyzed, and the region of interest in the first frame image is cross-correlated with the region of interest in all subsequent frame images to obtain the temporal speckle intensity autocorrelation curve g2(t). In order to improve the statistical accuracy of speckle time, the same set of data is collected multiple times and averaged in time, as shown below:

[0106]

[0107] Where I(t0) and I(t+t0) refer to the speckle intensity at I(t0) and I(t+t0) respectively, and <>pixels and <>t0 respectively refer to the average values ​​of all pixels in the image in space and time. The premise for deriving the mechanical properties of the sample from the acquired 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 a correction factor for the ratio of the long diffusion path length to the short diffusion path length. It is generally assumed that γ = 5 / 3, and this parameter is 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. The calculated MSD value is substituted into the generalized Stokes-Einstein relationship to calculate the viscoelasticity, as shown below:

[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. Logarithmic derivative of the mean square displacement. The viscoelastic modulus |G*(ω)| can be derived from the MSD if the sample meets the criteria for validity of the generalized Stokes-Einstein relation.

[0112] Four different biological tissue samples were selected, and the autocorrelation curves g2(t) of different biological samples were plotted, and the decorrelation time τ was calculated. The tissue samples evaluated included pig fat, muscle, skin, and cartilage. All tissue samples were collected in a 37°C water bath by the LSR method at a camera frame rate of 300fps. 6000 speckle patterns were collected at 5 different spatial locations for averaging. The measurement results are shown in Figure 2. Fig.10 As shown, the results show that 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] Use deep learning to classify plaques and conduct further analysis, such as Fig.11 As shown in the figure, a residual network (ResNet) is constructed, and a viscoelastic prediction and classification network (Viscoelastic prediction and classification network) is obtained by training with measured data. The network is used to quickly process the image, extract the viscoelastic related information contained therein, give the real-time viscoelastic data at this time through the speckle pattern, and classify the image into plaque-free, benign plaque, and malignant plaque. It simplifies a large number of complex operations on the speckle pattern, realizes the rapid response of the system; improves the data processing capability of the system, effectively extracts the key information in the image, and avoids interference from other invalid information; enhances the generalization ability of the system, and can effectively adapt to changing physiological scenes.

[0114] 10k speckle images were collected for the sample at a frame rate of 400fps by the camera. By analyzing the time-varying speckle images, the autocorrelation function of the speckle fluctuation was established. This process can reveal the decorrelation time of different speckle areas. Then, the speckle areas were classified according to the decorrelation time, and the corresponding real-time viscoelastic data and plaque categories were obtained to construct a data set. The network was trained by splitting it into a training set and a validation set in a ratio of 9:1 to obtain a practical viscoelastic prediction and classification network. The input of the network is a set of 256×256 speckle images, and the output is real-time viscoelastic values ​​and plaque classification. Each group of images first passes through a set of 7×7 convolutional layers, batch normalization, activation functions, and 3×3 pooling layers, then passes through 8 residual blocks, and finally passes through a global average pooling layer to obtain the image features.

[0115] Among them, the residual blocks are divided into two categories: in addition to two convolutions on the main path, the A-type blocks also undergo one convolution on the shortcut path to adapt to the dimensional changes of the feature map in the network; the B-type shortcuts are directly connected to the main path that has undergone two convolutions. In the above network structure, convolution and pooling calculations are particularly critical, and their calculations can be used to obtain the final regression and classification results. The convolution calculation extracts the features of the image by sliding a matrix called a convolution kernel on the image and performing a weighted summation on the pixels in each covered area. This is followed by batch normalization and activation functions 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 indices of the convolution kernel, and K(m, n) is the element of the convolution kernel (or filter) matrix.

[0118] There are many types of pooling calculations. The network mainly uses maximum pooling and global average pooling. Maximum pooling retains the most significant features by extracting the maximum value from the local area of ​​the feature map. This process is completed by sliding a fixed-size window across the entire feature map and selecting the largest 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 indices of the convolution kernel, and P is the pooling window size.

[0121] 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 multiplies the one-dimensional vector with the weight matrix and adds the bias term, and then performs a nonlinear transformation through the activation function to achieve a high degree of abstraction and integration from image to feature, thereby completing the classification or regression task.

[0122] According to the data analysis results, the pathological characteristics of the plaque are evaluated to determine whether the plaque needs treatment. If treatment is required, the optical power density of the laser is adjusted and the laser power required for treatment is input to activate the photosensitizer, thereby achieving highly selective treatment of abnormal parts and avoiding damage to surrounding healthy tissues. After the treatment is completed, the principle of laser speckle rheology is continued to be used to adjust the laser power to the power required for measurement, and then the viscoelasticity of the treated plaque is measured, and the effect of photodynamic therapy is checked for intraoperative evaluation. If the treatment effect is good, the guide wire continues to move forward for detection. If the treatment effect is not good, the photodynamic therapy method continues to be used to diagnose and treat the plaque.

[0123] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An interventional device, characterized in that: It comprises a guide wire (4), an image transmission beam front-end probe (9), a magnetron guidance device, a laser irradiation device and an image receiving device, wherein: The guide wire (4) and the optical fiber image transmission bundle (5) serve as the main body 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 sections of magnets (11); the outer layer of the magnet (6) is provided with a protective cover (7); the outer layer of the protective cover is plated with a hydrophilic coating (8); The image transmission bundle front-end probe (9) comprises four free-form surfaces and an aspheric lens (9); the material of the image transmission bundle front-end probe (9) is photoresist SU-8; the four free-form surfaces are coated with a reflective coating; the aspheric lens (9) is fixed on the top of the four free-form surfaces; the free-form surface of the image transmission bundle front-end probe (9) is coupled to the front end of the optical fiber image transmission bundle; The magnetic control guiding device comprises a wire feeding mechanism (3), a mechanical arm (1) and a permanent magnet (2), wherein 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 active clamping component of the wire feeding mechanism (3) is connected to the guide wire (4); The laser irradiation device comprises a laser (15), a first polarizer (16), a beam expander (17) and a reflector (18); the front end of the laser (15) is provided with the first polarizer (16), the beam expander (17) and the reflector (18) in sequence; The image receiving device comprises an objective lens (19), a beam splitter (20), a second polarizer (21), a focusing lens (22), and a CMOS camera (23). The side of the reflector (18) is provided with a beam splitter (20). The beam splitter (20) splits a light beam into two paths. The two paths of light are respectively propagated 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 transmission bundle (5) is coupled with the objective lens (19). The other side of the beam splitter (20) is provided with a second polarizer (21), a focusing lens (22), and a CMOS camera (23) in sequence.

2. The interventional device according to claim 1, characterized in that: The hydrophilic coating comprises a PUA coating (12), a PVP coating (13) and a hyaluronic acid gel film (14), wherein the PUA coating (12) is covered on the surface of the protective cover (7) by ultraviolet curing technology, the PVP coating (13) is polymerized on the PUA coating (12) by ultraviolet curing technology, and the hyaluronic acid gel film (14) is coated on the PVP coating (13).

3. The interventional device according to claim 1, characterized in that: The optical fiber image transmission bundle (5) is a polymer optical fiber image transmission bundle, the core number of which is 13000, the numerical aperture is 0.5, the diameter of the optical fiber image transmission 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.

4. The interventional device according to claim 1, characterized in that: The magnet (11) is made by attaching magnetic material to the surface of the optical fiber image transmission bundle (5) using femtosecond laser processing technology. The magnet (11) is a relatively axially polarized cylindrical N52 neodymium magnet. Two sections of the magnet (11) are respectively attached to the front end and the middle section of the optical fiber image transmission bundle (5).

5. The interventional device according to claim 1, characterized in that: The four free-form surfaces and the aspherical lens of the front-end probe (9) of the image transmission bundle are an integrated structure, which are directly printed onto the end face of the optical fiber image transmission bundle (5) using femtosecond laser two-photon polymerization technology, and gold material is used as the free-form surface reflective coating, and the precise deposition of the coating is achieved through physical vapor deposition technology.

6. The interventional device according to claim 1, characterized in that: The laser (15) is a helium-neon laser with a wavelength of 632 nm.

7. The method for measuring viscoelasticity of an interventional device according to any one of claims 1 to 6, characterized in that: The specific steps are as follows: (1) A guide wire is introduced into the radial artery or femoral artery using a wire feeding mechanism, and a magnetic control guide device controls the rotation, advancement, and bending of the guide wire. After the guide wire reaches the target position, a catheter is slid along the guide wire to a predetermined position, and a 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 imaging bundle front end probe (9) at the front end of the optical fiber imaging bundle (5) will sense the existence and position of the plaque, causing the speckle image of the corresponding area to change significantly; (3) using an image receiving device to receive and record in real time the speckle pattern transmitted by the optical fiber image transmission bundle (5), and using an image super-resolution neural network method to eliminate speckle pattern noise and improve the quality of the speckle image; (4) Further analysis of the reconstructed speckle pattern to obtain the plaque viscoelasticity; (5) A deep learning algorithm based on convolutional neural network is used to classify plaques with different viscoelastic properties through a series of speckle patterns; (6) Evaluate the pathological characteristics of the plaque based on the data analysis results, and perform photodynamic therapy after identifying the abnormal area. By adjusting the laser illumination parameters, the power density and illumination time of the laser after passing through the fiber optic imaging bundle are controlled. The outgoing laser is precisely targeted to the macrophages in the abnormal plaque through the front-end probe of the fiber optic imaging bundle.

8. The method for measuring viscoelasticity of an interventional device according to claim 7, characterized in that: The specific steps of step (1) include: (1-1) By precisely adjusting the position of the permanent magnet at the end of the robotic arm, the guidewire is ensured to accurately enter the vascular system to be inspected, and the position and direction of the guidewire can be precisely controlled; (1-2) After the guidewire enters the blood vessel, the speckle pattern is acquired through the fiber optic imaging bundle for analysis, so as to locate the magnetically controlled guidewire and determine the relative position of the guidewire and the blood vessel wall. The magnetic field strength of the magnet on the guidewire is feedback-controlled using the robotic arm and permanent magnet in the magnetically controlled guidance device to ensure that the position and posture of the guidewire inside the blood vessel are in line with expectations, thereby ensuring the accuracy of subsequent steps.

9. The method for measuring viscoelasticity of an interventional device according to claim 7, characterized in that: 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 twice the pixel size, select a region of interest to collect images, and obtain a series of speckle images that change over time; (3-2) using a single image unsupervised denoising convolutional neural network method to preliminarily remove noise from the speckle image obtained in step (3-1); (3-3) reconstructing the preliminary denoised speckle image obtained in step (3-2) using a honeycomb-artifact removal convolutional neural network algorithm, including three convolutional layers: patch extraction, nonlinear mapping, and reconstruction; (3-4) The reconstruction performance of HAR-CNN on the synthetic image was verified by superimposing an artificial honeycomb pattern on the original image, and the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) were used for quantitative evaluation. PSNR is used to quantify the quality of image restoration while comparing the pixel-by-pixel intensity difference between the two images, and SSIM is used to quantify the degradation of image quality relative to the direct source.

10. The method for measuring viscoelasticity of an interventional device according to claim 7, characterized in that: The specific steps of step (4) include: (4-1) further analyzing the speckle pattern reconstructed in step (3), cross-correlating 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 temporal speckle intensity. To improve the temporal statistical accuracy of the speckle pattern, the same set of data is collected multiple times and averaged in time. (4-2) The autocorrelation curve was fitted with a single exponential decay function, and the decorrelation time when the correlation dropped to 70% was extracted for qualitative analysis of plaques with different viscoelasticity; (4-3) Extracting the root mean square displacement (MSD) reflecting the Brownian motion characteristics of particles inside the plaque from the autocorrelation curve; (4-4) Substitute the MSD calculated in step (4-3) into the Stokes-Einstein equation to quantitatively calculate the viscoelasticity of the plaque.

Images