Image velocimetry system for blood vessels, vasculopathy risk assessment method, blood vessel detection device-nanoparticle composition and application thereof

Abstract

The invention discloses an image velocity measurement system for blood vessels, a vascular lesion risk assessment method, a blood vessel detection device-nanoparticle composition and application thereof, and relates to the field of image processing. The system comprises a targeted visual nanoparticle drug delivery unit, a double-ring scanning optical probe, a CMOS imaging device, an image acquisition and double-domain correlation processing module and a coupling mechanical parameter calculation module. According to the invention, the dual-ring scanning optical probe is combined with the external CMOS imaging device, so that efficient transceiving and transmission of the fluorescence signals of the nanoparticles are realized; and performing digital image correlation and microscopic particle image velocity measurement on the image sequence to finally obtain time synchronization data of various mechanical parameters such as vascular wall deformation, near-wall blood flow velocity, shear stress and the like, and performing vascular lesion risk assessment and early warning based on the time synchronization data.

Description

Technical Field

[0001] The present invention relates to the field of image processing, and in particular to an image velocimetry system for blood vessels, a method for assessing the risk of vascular lesions, a blood vessel detection device-nanoparticle composition, and applications thereof. Background Art

[0002] In the diagnosis and intervention of cardiovascular and cerebrovascular diseases, the structural integrity of the vascular wall is closely related to the intravascular hemodynamic characteristics. Numerous studies have demonstrated a coupling effect between vascular wall strain (especially principal strain) and mechanical parameters such as blood flow shear stress, which is of great significance for assessing plaque vulnerability, predicting restenosis after stent placement, and early detection of vascular graft dysfunction. However, existing methods can typically only measure blood flow or vessel wall deformation information independently, making it difficult to simultaneously acquire vessel wall deformation and near-wall blood flow velocity fields in situ.

[0003] To overcome these challenges, coupling digital image correlation (DIC) with microparticle image velocimetry (μPIV) has emerged as a promising research method. However, achieving simultaneous DIC-μPIV measurements in vivo (especially within blood vessels) requires addressing the following technical challenges:

[0004] 1. How to effectively transmit excitation light and fluorescence signals through tiny catheters or probes and achieve high-resolution near-wall imaging;

[0005] 2. How to effectively label and track vascular walls and blood flow tracer particles in a blood flow environment while maintaining adequate biocompatibility and imaging contrast;

[0006] 3. How to achieve reliable coupling of DIC and μPIV algorithms and high-speed processing based on high-frame-rate, high-resolution data acquisition?

[0007] 4. In an actual interventional surgical environment, how to visualize measured mechanical indicators such as shear stress, principal strain, and pulsating pressure in real time and perform risk analysis. Summary of the Invention

[0008] The purpose of the present invention is to provide a blood vessel image velocimetry system, a method for vascular lesion risk assessment, a blood vessel detection device-nanoparticle composition and its application, so as to solve the problems raised in the above background technology.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] An image velocimetry system for a blood vessel, comprising:

[0011] Targeted visualization nanoparticle delivery unit, used to inject micro / nanoparticles with endothelial adhesion and fluorescence visibility into the target blood vessel lumen;

[0012] A dual-ring scanning optical probe is used to achieve excitation light emission and fluorescence signal reception in the blood vessel cavity, wherein the outer ring emits excitation light and the inner ring receives the fluorescence signal and transmits it to an external imaging device;

[0013] A CMOS imaging device, used to collect image sequences corresponding to the above-mentioned fluorescence signals;

[0014] An image acquisition and dual-domain correlation processing module is used to simultaneously execute a digital image correlation algorithm on the image sequence to obtain a vascular wall displacement / strain field, and a microparticle image velocimetry algorithm to obtain a near-wall blood flow velocity / shear stress field;

[0015] The coupled mechanical parameter calculation module is used to calculate the coupled parameters of blood flow shear stress, wall principal strain and pulsating pressure based on the time synchronization of the strain field and the velocity field, and visualize the output on the user interface.

[0016] As a preferred embodiment of the present invention, the micro / nanoparticles have a particle size of 50-300 nm, and specific peptide ligands are covalently grafted onto the surface to selectively adhere to vascular endothelial cells.

[0017] As a preferred embodiment of the present invention, the fluorescence emission peak of the micro / nanoparticles is located at 520-560 nm, which matches the wavelength of the excitation light to improve the imaging signal-to-noise ratio.

[0018] As a preferred solution of the present invention: the dual-annular scanning optical probe adopts a coaxial optical path structure and has circumferential scanning and axial movement functions, which is used to achieve full-range circumferential and longitudinal imaging within the blood vessel segment.

[0019] As a preferred solution of the present invention: the image acquisition and dual-domain correlation processing module can adaptively adjust parameters and dynamically adjust the window size, number of iterations or correlation threshold in the DIC and μPIV algorithms according to image quality.

[0020] As a preferred solution of the present invention: the coupled mechanical parameter calculation module is provided with an early warning function, which triggers a visual alarm prompt when the combined parameter of shear stress and principal strain exceeds a preset risk threshold.

[0021] As a preferred embodiment of the present invention: a method for assessing the risk of vascular lesions using the system comprises the following steps:

[0022] a) injecting fluorescent targeting nanoparticles into the target blood vessel lumen;

[0023] b) inserting the dual-ring scanning optical probe into the target blood vessel segment through the catheter and starting scanning;

[0024] c) acquiring synchronous fluorescence image sequences using a CMOS imaging device;

[0025] d) executing a DIC algorithm on the image sequence to obtain a blood vessel wall strain field;

[0026] e) executing a μPIV algorithm on the image sequence to obtain blood flow velocity field and shear stress distribution;

[0027] f) performing a time-synchronous analysis on the results obtained in steps d) and e) to calculate the coupled mechanical parameters of blood flow shear stress, principal strain, and pulsating pressure;

[0028] g) Determine the risk of plaque vulnerability, stent restenosis, or vascular graft dysfunction based on coupled mechanical parameters and preset thresholds.

[0029] As a preferred embodiment of the present invention: a blood vessel detection device-nanoparticle combination, including the above-mentioned system and a fluorescent targeting nanoparticle preparation used in conjunction with the system.

[0030] As a preferred embodiment of the present invention, the nanoparticle preparation is a freeze-dried powder, which is dissolved in physiological saline before use and injected into the target blood vessel through a catheter.

[0031] As a preferred embodiment of the present invention:

[0032] An application using the system:

[0033] Determine the risk of restenosis after coronary artery stenting;

[0034] Monitor bypass grafts for signs of dysfunction;

[0035] Evaluate changes in intracranial aneurysm wall tension;

[0036] Medical scenarios where both vascular wall strain and near-wall blood flow need to be detected simultaneously.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] 1. Small size and strong applicability: By coordinating the dual-ring scanning optical probe with external CMOS imaging, the outer diameter of the probe can be reduced while ensuring image resolution, which is conducive to use in narrow or curved blood vessels.

[0039] 2. Synchronous detection: Images collected at the same time are used for both DIC and μPIV analysis, which can obtain time-synchronized data on vessel wall deformation and blood flow velocity field, enabling accurate measurement of coupled mechanical parameters.

[0040] 3. Nanoparticle targeted tracing: Micro / nanoparticles have endothelial cell adhesion and are fluorescently labeled, which can form clearly visible fluorescent signals on the vascular wall and near the wall, providing good contrast for the DIC-μPIV algorithm.

[0041] 4. Real-time analysis and risk assessment: The system can perform real-time imaging and calculations in an interventional surgical setting. Combined with the threshold warning function, it can help the surgeon promptly determine the potential risks of plaque vulnerability, stent restenosis, or graft dysfunction. DETAILED DESCRIPTION

[0042] The following is a clear and complete description of the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0043] In an embodiment of the present invention, a blood vessel image velocimetry system includes:

[0044] Targeted visualization nanoparticle delivery unit, used to inject micro / nanoparticles with endothelial adhesion and fluorescence visibility into the target blood vessel lumen;

[0045] A dual-ring scanning optical probe is used to achieve excitation light emission and fluorescence signal reception in the blood vessel cavity, wherein the outer ring emits excitation light and the inner ring receives the fluorescence signal and transmits it to an external imaging device;

[0046] A CMOS imaging device, used to collect image sequences corresponding to the above-mentioned fluorescence signals;

[0047] An image acquisition and dual-domain correlation processing module is used to simultaneously execute a digital image correlation algorithm on the image sequence to obtain a vascular wall displacement / strain field, and a microparticle image velocimetry algorithm to obtain a near-wall blood flow velocity / shear stress field;

[0048] The coupled mechanical parameter calculation module is used to calculate the coupled parameters of blood flow shear stress, wall principal strain and pulsating pressure based on the time synchronization of the strain field and the velocity field, and visualize the output on the user interface.

[0049] Furthermore, the micro / nanoparticles have a particle size of 50-300 nm, and specific peptide ligands are covalently grafted onto the surface to selectively adhere to vascular endothelial cells.

[0050] Furthermore, the fluorescence emission peak of the micro / nanoparticles is located at 520–560 nm, which matches the excitation light wavelength to improve the imaging signal-to-noise ratio.

[0051] Furthermore, the dual-annular scanning optical probe adopts a coaxial optical path structure and has the functions of circumferential scanning and axial movement, so as to realize full-range imaging in the circumferential and longitudinal directions within the blood vessel segment.

[0052] Furthermore, the image acquisition and dual-domain correlation processing module can adaptively adjust parameters and dynamically adjust the window size, number of iterations or correlation threshold in the DIC and μPIV algorithms according to image quality.

[0053] Furthermore, the coupling mechanical parameter calculation module is provided with an early warning function, which triggers a visual alarm prompt when the combined parameters of shear stress and principal strain exceed a preset risk threshold.

[0054] Furthermore, a method for assessing the risk of vascular lesions using the system comprises the following steps:

[0055] a) injecting fluorescent targeting nanoparticles into the target blood vessel lumen;

[0056] b) inserting the dual-ring scanning optical probe into the target blood vessel segment through the catheter and starting scanning;

[0057] c) acquiring synchronous fluorescence image sequences using a CMOS imaging device;

[0058] d) executing a DIC algorithm on the image sequence to obtain a blood vessel wall strain field;

[0059] e) executing a μPIV algorithm on the image sequence to obtain blood flow velocity field and shear stress distribution;

[0060] f) performing a time-synchronous analysis on the results obtained in steps d) and e) to calculate the coupled mechanical parameters of blood flow shear stress, principal strain, and pulsating pressure;

[0061] g) Determine the risk of plaque vulnerability, stent restenosis, or vascular graft dysfunction based on coupled mechanical parameters and preset thresholds.

[0062] Furthermore, the present invention also provides a blood vessel detection device-nanoparticle combination, including the above-mentioned system and a fluorescent targeted nanoparticle preparation used in conjunction with the system.

[0063] As a preferred embodiment of the present invention, the nanoparticle preparation is a freeze-dried powder, which is dissolved in physiological saline before use and injected into the target blood vessel through a catheter.

[0064] Furthermore, the present invention also provides an application using the system:

[0065] Determine the risk of restenosis after coronary artery stenting;

[0066] Monitor bypass grafts for signs of dysfunction;

[0067] Evaluate changes in intracranial aneurysm wall tension;

[0068] Medical scenarios where both vascular wall strain and near-wall blood flow need to be detected simultaneously.

[0069] The present invention provides an integrated DIC-μPIV system for vascular strain-blood flow coupling detection, and its complete operation process includes the following steps:

[0070] (1) Preparation and injection of fluorescent targeted nanoparticles:

[0071] The targeted visualization nanoparticles used in the present invention are polymer-based composite micro / nanoparticles with a particle size in the range of 50–300 nm. The particle core can use polylactic acid-co-glycolic acid (PLGA) or polycaprolactone (PCL) as a biodegradable substrate, and its surface is covalently coupled with specific peptides (such as arginine-glycine-aspartic acid sequence, RGD peptide) to enhance the selective binding ability with vascular endothelial cell integrin receptors, thereby improving the positioning specificity and the retention time near the wall.

[0072] Fluorescent dyes embedded within the particles are recommended for high-quantum-yield, stable organic fluorophores, such as NileRed, Rhodamine B, or FITC (fluorescein isothiocyanate). FITC has an excitation wavelength of 488–495 nm and an emission peak of approximately 520–530 nm. When paired with a 532 nm excitation light source, it effectively improves the system's imaging signal-to-noise ratio. To prevent photobleaching, it is recommended to protect the fluorescent molecules with an anti-light-fading coating (such as a PEG derivative).

[0073] Prior to injection, the lyophilized preparation should be resuspended in 0.9% sodium chloride injection (pH 7.4) under a sterile operating environment to a uniformly dispersed suspension of 0.5–1.0 mg / mL. Magnetic stirring or ultrasonic agitation should be used for 10–30 seconds to prevent particle aggregation. A 10F catheter system is recommended, as it offers excellent flexibility and lumen permeability, making it suitable for precise delivery of particles to the injection site during interventional procedures.

[0074] The target vessel is typically a site requiring lesion risk assessment, such as the coronary, carotid, renal, or peripheral arteries, particularly in areas with existing stents or grafts or atherosclerotic plaques. After injection, the particles are allowed to sit for 1–2 minutes to allow them to adhere to and stabilize on the endothelial surface. During this time, temporary blood flow occlusion or retrograde low-pressure irrigation can be used to reduce flow and optimize adhesion.

[0075] Adhesion can be initially verified by illuminating the particle area with low-intensity excitation light (laser power less than 5mW, using continuous mode). Turn on the excitation light source, capture 3–5 fluorescence images using an imaging device, and analyze changes in signal intensity in the target area. If the fluorescence signal remains uniform and stable (variation <10%) within 3 seconds, adhesion is considered satisfactory and the next step of image acquisition can be performed.

[0076] (2) Positioning of the dual-ring scanning optical probe and excitation light irradiation:

[0077] The dual-ring scanning optical probe used in this invention is a miniature coaxial integrated optical sensing device designed specifically for intravascular fluorescence imaging. Its structure comprises an outer ring fiber channel for transmitting excitation light (typically a 532nm laser) and an inner ring fiber channel for collecting fluorescence signals (emissions at 520–560nm). These two channels form a coaxial transmit-receive path through a central optical collimation system. An embedded microprism enables lateral illumination and collection, ensuring that the vessel wall and near-wall areas can be illuminated and detected.

[0078] The probe tip has a diameter within the range of 2.5–3.0 mm and a length not exceeding 25 cm. The outer shell is coated with a flexible medical polymer (such as Pebax) for excellent bending properties and biocompatibility. The optical fiber utilizes low-loss quartz optical fiber with a minimum bend radius of <10 mm, making it suitable for use in complex and curved vascular channels such as coronary and cerebral arteries. The entire probe is connected to a dedicated micro-drive system, enabling control capabilities in the following two degrees of freedom:

[0079] Axial advancement adjustment: The stepper motor drive module precisely controls the longitudinal advancement and retreat of the probe in the catheter, with a minimum step length of 0.1mm.

[0080] Circumferential rotation scanning: The end of the probe is linked to a micro-rotation motor, which can achieve 360° full-angle scanning or set angle segment scanning to construct circumferential imaging sections of the blood vessel wall.

[0081] During the procedure, the probe is first advanced into the target vascular segment via a coaxial catheter channel (an 8–10 French triple-lumen catheter is recommended). Its position is confirmed using an intraoperative imaging navigation system (such as angiography or IVUS real-time echocardiography). A radiopaque marker ring is placed at the probe tip to facilitate spatial positioning under X-rays.

[0082] After positioning is completed, start the laser excitation module. The excitation light power can be 1–20mW / cm 2 The recommended initial setting is 10mW / cm 2 The laser light source is delivered to the tissue around the blood vessel wall through the outer ring optical fiber, exciting the fluorescent nanoparticles embedded in or attached to the vascular endothelium and emitting fluorescent signals.

[0083] Fluorescence signals are received by an internal fiber ring and guided via a multimode fiber to an external CMOS imaging device. To improve signal quality, a bandpass filter (centered at 550 nm, with a bandwidth of 40 nm) is integrated within the probe to shield against interference from excitation light, retaining only the emission signal. The entire probe positioning and excitation process is completed within 2 minutes, followed by image acquisition.

[0084] (3) Image acquisition:

[0085] The image acquisition process in the present system utilizes a high-frame-rate, high-sensitivity CMOS imaging device, working in conjunction with a probe scanning system, to capture fluorescence images of the vascular wall and near-wall flow field. A high-speed CMOS camera with scientific-grade performance (such as the Photron FASTCAM Mini AX100 or Basler boost series) is recommended for this imaging device. Its key performance parameters are as follows:

[0086] Spatial resolution: 2048 × 2048 pixels;

[0087] Pixel size: approximately 5.5 μm × 5.5 μm;

[0088] Dynamic range: 12-bit grayscale depth;

[0089] Frame rate adjustable range: 1000–5000 frames per second (fps), with a typical setting of 2000fps;

[0090] Exposure time: 20–200 μs, adjustable;

[0091] Shutter mode: Global shutter to prevent image blur caused by high-speed motion.

[0092] To achieve excitation-acquisition coordination, the system is equipped with a synchronization controller (e.g., an FPGA-based trigger control unit) that can simultaneously control the laser emission module, probe rotation step, CMOS camera acquisition frequency, and image buffer storage to achieve timing alignment (clock error <1μs). The probe scanning and imaging system can be set to one of the following two acquisition modes:

[0093] Fixed-point high-speed acquisition mode: The probe remains stationary and only time series acquisition is performed, which is used to study the instantaneous changes in the interaction between local blood vessel walls and blood flow;

[0094] Spiral scanning acquisition mode: The probe constructs time-space joint image data of the vascular segment by axial advancement + circumferential rotation for three-dimensional mechanical field recovery.

[0095] The acquisition process is usually set to last 1–3 seconds, covering at least one complete cardiac cycle (reference value is approximately 1.0–1.2 seconds). To ensure data adequacy, it is recommended that the number of image frames collected each time be no less than 500. The image sequence includes the following two types of information:

[0096] Static particle images: Fluorescent nanoparticles distributed on the surface of the vascular endothelium move with the periodic deformation of the vascular wall and are used for DIC analysis;

[0097] Flow particle image: Suspended particles distributed in the blood flow undergo inter-frame displacement as the blood flows, and are used for μPIV velocity field reconstruction.

[0098] Laser power must be maintained constant during image acquisition, and the camera utilizes an automatic gain compensation mechanism to optimize signal quality. Image data is stored in real time to a high-performance SSD cache in uncompressed 16-bit tiff sequence or .raw binary format, facilitating subsequent parallel processing with DIC and μPIV algorithms. The system supports background noise suppression (via empty field image subtraction) and temperature drift correction during acquisition to ensure consistent image quality.

[0099] (4) Image processing and strain-velocity analysis:

[0100] The acquired fluorescence image sequences are imported into the image processing module via a high-speed data channel. The system supports a GPU-accelerated image processing engine (NVIDIA GPUs with CUDA architecture or OpenCL general-purpose platforms are recommended), which can simultaneously perform two types of image analysis tasks:

[0101] (11) Digital image correlation analysis:

[0102] The DIC algorithm is used to evaluate the subtle deformation of the blood vessel wall caused by pressure changes during the cardiac cycle and calculate sub-pixel displacement and strain information. The analysis process is as follows:

[0103] ① Image preprocessing: Perform image enhancement (histogram equalization or adaptive filtering) on ​​the static particle signal area to improve the clarity of particle boundaries;

[0104] ② Window division and cross-correlation operation: Multiple overlapping windows are divided in the wall area (typical window size is 32×32 pixels, overlap ratio is 50%), grayscale cross-correlation calculation is performed on adjacent frames, and quadratic interpolation or Gaussian fitting is used to achieve sub-pixel registration accuracy;

[0105] ③Displacement vector solution: Obtain the displacement vector (u, v) of each window by searching for extreme points, in pixels;

[0106] ④ Strain field reconstruction: The strain tensor ε is derived from the displacement field through numerical differentiation (central difference or fitted derivative), and the principal strain ε1 and shear strain γ components are further calculated:

[0107]

[0108] The strain map is output as a two-dimensional vector field and a pseudo-color heat map, with a resolution consistent with the image window division.

[0109] (22) Microparticle Image Velocimetry (μPIV):

[0110] The μPIV algorithm is used to extract the motion trajectory of particles in the blood flow between frames, thereby deriving the velocity field and shear stress distribution. The analysis process is as follows:

[0111] ① Flow zone identification: Distinguish static wall and moving particle areas through intensity threshold and Fourier spectrum screening method;

[0112] ② Cross-correlation processing: Divide the analysis window (e.g., 64 × 64 pixels, 50% overlap) in the near-wall region (<100 μm from the endothelium), and perform fast Fourier transform (FFT) cross-correlation on adjacent frames.

[0113] ③ Velocity vector extraction: The offset value Δd corresponding to the main peak in each window is combined with the inter-frame time Δt to calculate the instantaneous velocity:

[0114]

[0115] ④ Velocity field interpolation and filtering: bicubic interpolation is used to reconstruct the dense velocity vector map, and median filtering or standard deviation elimination algorithm is used to remove pseudo vectors;

[0116] ⑤ Shear stress calculation: In the area close to the wall, the velocity gradient is estimated by the first-order derivative, and then the shear stress τ is calculated:

[0117]

[0118] Where μ is the blood dynamic viscosity, which defaults to 3.5 mPa·s; the y direction is the normal direction to the blood vessel wall, and the derivative is obtained by linear fitting of the local velocity.

[0119] (5) Calculation of coupling mechanical parameters:

[0120] The strain field (DIC) and velocity field (μPIV) data output by the image processing module are registered temporally and spatially with a unified frame number and image coordinates before entering the coupled mechanical parameter calculation module. The core goal of this module is to calculate and establish the coupling relationship between the following three key parameters:

[0121] Blood flow shear stress (Wall Shear Stress, WSS, denoted as r);

[0122] Principal Strain (ε1) of the vascular wall;

[0123] Pulsatile Pressure Rate (ΔP / Δt).

[0124] ① Time registration and point alignment

[0125] All image data is time-stamped (1μs resolution) and paired based on frame number and spatial pixel index. The system aligns data from multiple analysis windows in the same image spatial region at the same time point to form a coupled observation point matrix. Each observation point corresponds to a set of data triplets:

[0126] (τ ij ,ε 1ij , ΔP ij / Δt)

[0127] Where i and j represent the image coordinate grid index.

[0128] ②Calculation of shear stress τ:

[0129] The shear stress is calculated from the velocity field gradient obtained by μPIV as follows:

[0130]

[0131] Wherein, μ is the dynamic viscosity of blood, which is 3.5 MPa·s by default or can be dynamically corrected by the temperature correction function;

[0132] is the velocity gradient of blood flow in the normal direction near the wall, obtained by first-order difference or local fitting.

[0133] To reduce the influence of boundary discontinuity, shear stress was calculated only within the range of 0–100 μm from the vessel wall and local smoothing was performed.

[0134] ③Calculation of principal strain ε1

[0135] The principal strains are obtained from the two-dimensional strain tensor output by the DIC algorithm and are defined as the largest eigenvalue of this tensor:

[0136]

[0137] Among them, ε x , ε y , is the normal strain in the principal axis direction; γ is the shear strain component; eig[·] is the eigenvalue solution function.

[0138] ④ Estimation of pulsating pressure change rate Δp / Δt

[0139] The system uses a simplified one-dimensional incompressible Navier-Stokes model and combines velocity change information to estimate the local pressure change rate:

[0140]

[0141] Where ρ is the blood density, which is set to 1050 kg / m 3 ; is the time derivative of velocity, calculated based on multi-frame velocity field; is the axial velocity gradient. This model assumes local laminar flow and slow changes in vascular stiffness.

[0142] ⑤ Coupling parameter matrix and index extraction

[0143] After outputting the triplet value at each moment and each observation window, the system can construct a coupled map of the blood vessel wall and the flow field:

[0144] Spatial heat map: two-dimensional distribution of each parameter within the vessel segment;

[0145] Time curve: parameter change trend of selected points or areas;

[0146] Three-dimensional coupling map: Draw a scatter distribution or fitted surface with (τ, ε1, ΔP / Δt) as the axis to identify abnormal aggregation or lesion precursors.

[0147] In addition, the system automatically calculates the following indicators:

[0148] Peak shear stress (τ max ) and maximum principal strain Synchronicity;

[0149] Strain-shear stress coupling strength indicators (such as Pearson correlation coefficient);

[0150] The proportion of high-risk coupling areas (the volume proportion of the area that meets the threshold τ>50kPa and ε1>3%).

[0151] These data will be pushed to the visualization module and provide a basis for judgment based on the risk warning mechanism to be set in the next step.

[0152] (6) Visualization and risk identification

[0153] The various indicators output by the coupled mechanical parameter calculation module are transmitted in real time to the system's visualization terminal for graphical presentation and risk identification. This module integrates a structured image rendering engine (such as an OpenGL / VTK-based visualization library) with the clinical user interface, providing multimodal, interactive display methods, supporting rapid intraoperative interpretation and postoperative data archiving and analysis.

[0154] ①Visual output form:

[0155] The visualization module includes the following core display functions:

[0156] 1. Two-dimensional pseudo-color heat map:

[0157] Displays the two-dimensional distribution of shear stress (τ), principal strain (ε1), and pulsating pressure change rate (ΔP / Δt);

[0158] The color range supports linear or logarithmic scaling, and users can customize threshold color markers (such as red warning areas);

[0159] The layer overlay function supports the simultaneous presentation of vascular contours and mechanical parameter layers.

[0160] 2. Vector field map overlay:

[0161] Display blood flow velocity vector diagram and strain direction diagram, and choose whether to display vector density and magnitude normalization;

[0162] Users can click on the area of ​​interest to zoom in and view the local vector details, and analyze them in combination with the wall position relationship.

[0163] 3. Trend curve chart:

[0164] Provides a time-varying curve of mechanical parameters at a single observation point / area within a selected time point or cycle;

[0165] Can superimpose ECG synchronization markers to analyze the phase correspondence with the cardiac cycle;

[0166] Supports export to CSV, PDF or image formats.

[0167] 4. 3D coupling scatter plot / surface plot:

[0168] The three parameters of shear stress, principal strain and pulsating pressure are mapped into a three-dimensional scatter plot to reveal the clustering trend of the lesion area; it supports clustering and classification of high-risk areas based on principal component analysis (PCA) or linear discriminant analysis (LDA).

[0169] ②Risk identification and alarm mechanism

[0170] The system has a built-in configurable risk identification algorithm that can analyze various coupling indicators in real time and provide automatic alarm prompts. The default strategy is as follows:

[0171] 1. Single-point judgment logic: If any pixel area meets the following two conditions at the same time:

[0172] Shear stress τ ≥ 50 kPa;

[0173] If the principal strain ε1 is ≥ 3.0%, the point is marked as a “high-risk coupling point”.

[0174] 2. Regional risk concentration: If the number of consecutive adjacent high-risk points exceeds the set threshold (such as a 5×5 pixel area), the system will identify it as a "potential lesion area."

[0175] 3. Dynamic alarm prompts: Once a high-risk area is identified, the system will:

[0176] It appears as a flashing red frame on the interface;

[0177] Trigger sound or vibration alerts;

[0178] Generate an alarm record and write it into the log system;

[0179] Push summary information to the operator's display screen or auxiliary terminal (such as tablet, AR glasses).

[0180] Example 1: System structure and working mechanism

[0181] The system of the present invention includes the following core modules:

[0182] The system of the present invention includes the following core modules:

[0183] 1. Targeted Visualization Nanoparticle Drug Delivery Unit

[0184] The nanoparticles used in this system range in size from 50–300 nm and are based on biodegradable polymers such as PLGA or PCL. Their surfaces are covalently modified with integrin-targeting peptides (such as the RGD sequence) to achieve selective adhesion to vascular endothelial cells. Fluorescent dyes (such as FITC or Rhodamine B) are embedded within the particles, emitting at wavelengths of 520–560 nm to complement the system's 532 nm excitation light source and enhance the imaging signal-to-noise ratio. The particles are stored as a lyophilized powder and are resuspended in sterile saline at a working concentration of 0.5–1.0 mg / mL. The injection is performed using a 10F guiding catheter system (such as the ShuttleSelect catheter) via the femoral or radial artery into the target vascular segment (such as the coronary or carotid artery). The particles are allowed to rest for 1–2 minutes after injection to ensure stable adhesion to the vessel wall.

[0185] 2.Dual ring scanning optical probe

[0186] The probe adopts a coaxial dual-ring structure, with an overall diameter controlled at ≤2.0mm to adapt to the standard interventional catheter lumen diameter. The outer ring fiber channel transmits excitation light (532nm), and the inner ring is equipped with a multimode fiber array or microlens system to receive and transmit fluorescence signals. The probe has a 0–360° continuous circumferential rotation function and an axial propulsion capacity of up to 20mm, combined with a stepper motor and encoder for precise control. A low-pass filter is integrated at the output end of the probe to shield excitation light leakage and optimize the purity of fluorescence collection.

[0187] 3.CMOS imaging device

[0188] The system uses an external high-speed CMOS camera (e.g., 2048×2048 resolution, ≥5000 fps) to receive fluorescence signals via an optical fiber path. This camera is integrated with the probe rotation and laser synchronization control module. The camera uses a global shutter to avoid image distortion caused by high-speed motion. The acquisition controller supports ECG synchronization input to ensure that image data is aligned with the cardiac cycle.

[0189] 4. Image acquisition and dual-domain correlation processing module

[0190] The acquired image sequences are transmitted to the image processing server in real time via Gigabit Ethernet or PCIe interface. The processing flow includes:

[0191] Digital image correlation (DIC) analysis: Identify the natural speckle characteristics of fluorescent particles in the vascular wall area, extract the wall displacement vector field through sub-pixel matching between 32×32 pixel sub-windows, and further solve for the principal strain distribution.

[0192] Microparticle Image Velocimetry (μPIV) analysis: Dual-frame cross-correlation, window iterative optimization, and background filtering algorithms are used to reconstruct the velocity vectors of suspended particles in the near-wall region, outputting a two-dimensional velocity field and local shear stress map.

[0193] 5. Coupling mechanical parameter calculation module

[0194] This module aligns DIC and μPIV results based on image timestamps and spatial coordinates, and calculates the following key metrics based on a multi-parameter fitting model:

[0195] Shear stress τ: calculated based on the normal gradient of the μPIV velocity field and blood viscosity;

[0196] Principal strain ε1: The maximum principal axis strain is obtained by solving the eigenvalue of the strain tensor;

[0197] Pulsating pressure change rate ΔP / Δt: obtained by inverse deduction from the Navier–Stokes one-dimensional simplified model.

[0198] All parameters are output as graphs, time curves, and three-dimensional coupled feature spaces. If τ·ε1>50kPa·% in a certain area, the system triggers an alert, highlights the suspected lesion area on the interface, and generates a log record.

[0199] Example 2: Clinical use process

[0200] The clinical application process of this system is as follows:

[0201] 1. Under a sterile environment before surgery, resuspend the lyophilized nanoparticles at a concentration of 0.5 mg / mL to prepare 2 mL of working solution;

[0202] 2. Inject the particles into the target vessel segment (e.g., proximal left anterior descending artery) via an interventional catheter (10F) and allow them to sit for 1–2 minutes to allow for complete endothelial attachment.

[0203] 3. Insert the dual-ring optical probe into the catheter and advance it to the target area, achieving precise positioning through X-ray marking or ultrasound guidance;

[0204] 4. Start the laser emission and high-speed imaging system, and continuously collect fluorescence image sequences for 2 seconds (≥500 frames);

[0205] 5. The images are processed by the DIC and μPIV analysis modules to generate vascular wall strain maps and blood flow velocity maps;

[0206] 6. The coupled mechanics module outputs a shear stress-principal strain-pressure change map in real time. If any combination of indicators exceeds the clinical threshold, the system automatically highlights it on the display interface and issues an audible warning.

[0207] Based on the imaging results, doctors decide whether to intervene immediately (such as re-stent implantation or dilation treatment) or save the data for postoperative follow-up and personalized predictive modeling.

[0208] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations that come within the meaning and range of equivalents of the claims be embraced therein.

[0209] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. An image velocimetry system for blood vessels, characterized in that: include: Targeted visualization nanoparticle delivery unit, used to inject micro / nanoparticles with endothelial adhesion and fluorescence visibility into the target blood vessel lumen; A dual-ring scanning optical probe is used to achieve excitation light emission and fluorescence signal reception in the blood vessel cavity, wherein the outer ring emits excitation light and the inner ring receives the fluorescence signal and transmits it to an external imaging device; A CMOS imaging device, used to collect image sequences corresponding to the above-mentioned fluorescence signals; An image acquisition and dual-domain correlation processing module is used to simultaneously execute a digital image correlation algorithm on the image sequence to obtain a vascular wall displacement / strain field, and a microparticle image velocimetry algorithm to obtain a near-wall blood flow velocity / shear stress field; The coupled mechanical parameter calculation module is used to calculate the coupled parameters of blood flow shear stress, wall principal strain and pulsating pressure based on the time synchronization of the strain field and the velocity field, and visualize the output on the user interface.

2. The image velocimetry system for blood vessels according to claim 1, characterized in that: The micro / nanoparticles have a particle size of 50-300 nm, and specific peptide ligands are covalently grafted onto the surface of the particles so as to selectively adhere to vascular endothelial cells.

3. The image velocimetry system for blood vessels according to claim 2, characterized in that: The fluorescence emission peak of the micro / nanoparticles is located at 520-560 nm, which matches the excitation light wavelength to improve the imaging signal-to-noise ratio.

4. The image velocimetry system for blood vessels according to claim 3, characterized in that: The dual-annular scanning optical probe adopts a coaxial optical path structure and has the functions of annular scanning and axial movement, and is used to achieve full-range imaging in the circumferential and longitudinal directions within the blood vessel segment.

5. The image velocimetry system for blood vessels according to any one of claim 4, characterized in that: The image acquisition and dual-domain correlation processing module can adaptively adjust parameters and dynamically adjust the window size, number of iterations or correlation threshold in the DIC and μPIV algorithms according to image quality.

6. The image velocimetry system for blood vessels according to any one of claim 4, characterized in that: The coupled mechanical parameter calculation module is provided with an early warning function, which triggers a visual alarm prompt when the combined parameters of shear stress and principal strain exceed a preset risk threshold.

7. A method for assessing the risk of vascular lesions using the system according to any one of claims 1 to 6, characterized in that: The following steps are involved: a) injecting fluorescent targeting nanoparticles into the target blood vessel lumen; b) inserting the dual-ring scanning optical probe into the target blood vessel segment through the catheter and starting scanning; c) acquiring synchronous fluorescence image sequences using a CMOS imaging device; d) executing a DIC algorithm on the image sequence to obtain a blood vessel wall strain field; e) executing a μPIV algorithm on the image sequence to obtain blood flow velocity field and shear stress distribution; f) performing a time-synchronous analysis on the results obtained in steps d) and e) to calculate the coupled mechanical parameters of blood flow shear stress, principal strain, and pulsating pressure; g) Determine the risk of plaque vulnerability, stent restenosis, or vascular graft dysfunction based on coupled mechanical parameters and preset thresholds.

8. A blood vessel detection device-nanoparticle combination, comprising the system according to any one of claims 1 to 6 and a fluorescent targeted nanoparticle preparation used in conjunction therewith.

9. The composition according to claim 8, wherein The nanoparticle preparation is a freeze-dried powder, which is dissolved in physiological saline before use and injected into the target blood vessel through a catheter.

10. Use of the system according to any one of claims 1 to 6: Determine the risk of restenosis after coronary artery stenting; Monitor bypass grafts for signs of dysfunction; Evaluate changes in intracranial aneurysm wall tension; Medical scenarios where both vascular wall strain and near-wall blood flow need to be detected simultaneously.

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