An image velocimetry system for blood vessels, a method for blood vessel lesion risk assessment, a blood vessel detection device-nanoparticle composition and applications thereof

Abstract

The application discloses a kind of image velocimetry system for blood vessel, the method for blood vessel pathological change risk assessment, blood vessel detection device-nanoparticle composition and its application, it is related to image processing field, the system includes: targeted visualization nanoparticle administration unit, double-ring scanning optical probe, CMOS imaging device, image acquisition and double-domain correlation processing module, coupling mechanics parameter calculation module.The application utilizes double-ring scanning optical probe to combine external CMOS imaging device, realizes the efficient transceiving and transmission of nanoparticle fluorescence signal;By performing digital image correlation and microscopic particle image velocimetry on image sequence, finally obtain the time synchronization data of blood vessel wall deformation, near-wall blood flow velocity and shear stress and other mechanical parameters, and based on this, the assessment and early warning of blood vessel pathological change risk are carried out.

Description

Technical Field

[0001] This invention relates to the field of image processing, specifically to an image velocimetry system for blood vessels, a method for assessing the risk of vascular lesions, a vascular detection device-nanoparticle composition, and its applications. Background Technology

[0002] In the diagnosis and intervention of cardiovascular and cerebrovascular diseases, the structural integrity of the vessel wall is closely related to the hemodynamic characteristics within the vessel. Numerous studies have shown that there is a coupling effect between vessel 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 usually only measure blood flow or vessel wall deformation information separately, making it difficult to simultaneously acquire vessel wall deformation and proximal blood flow velocity fields under in-situ conditions.

[0003] To overcome the aforementioned challenges, the coupling of digital image correlation (DIC) technology with microparticle image velocimetry (μPIV) technology has gradually emerged as a promising research approach. However, achieving simultaneous DIC-μPIV measurement in a living environment (especially within blood vessels) still requires addressing the following technical challenges:

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

[0005] 2. How to effectively label and track blood vessel wall and blood flow tracer particles in the blood flow environment while maintaining sufficient biocompatibility and imaging contrast;

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

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

[0008] The purpose of this invention is to provide an image velocity measurement system for blood vessels, a method for assessing the risk of vascular lesions, a vascular detection device-nanoparticle composition and its application, in order to solve the problems mentioned in the background art.

[0009] To achieve the above objectives, the present invention provides the following technical solution:

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

[0011] A targeted visualization nanoparticle drug delivery unit is used to inject micro / nanoparticles with endothelial adhesion and fluorescence visibility into a target blood vessel lumen.

[0012] A dual-ring scanning optical probe is used to achieve excitation light emission and fluorescence signal reception within the blood vessel lumen. The outer ring emits excitation light, while the inner ring receives fluorescence signals and transmits them to an external imaging device.

[0013] A CMOS imaging device is used to acquire image sequences corresponding to the aforementioned fluorescence signals;

[0014] The image acquisition and dual-domain correlation processing module is used to simultaneously execute a digital image correlation algorithm on the image sequence to obtain the blood vessel wall displacement / strain field, and a microparticle image velocimetry algorithm to obtain the 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 flow velocity field, and to visualize the output on the user interface.

[0016] As a preferred embodiment of the present invention, the micro / nano particles have a particle size of 50–300 nm and are covalently grafted with specific peptide ligands on their 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 excitation wavelength to improve the imaging signal-to-noise ratio.

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

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

[0020] As a preferred embodiment of the present invention: the coupled mechanical parameter calculation module is equipped 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.

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

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

[0023] b) Insert the dual-ring scanning optical probe into the target vascular segment through a catheter and start the scan;

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

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

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

[0027] f) Perform 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) Based on coupled mechanical parameters and preset thresholds, assess plaque vulnerability, stent restenosis, or risk of graft failure.

[0029] As a preferred embodiment of the present invention: a vascular detection device-nanoparticle composition, comprising the aforementioned system and a fluorescent targeted nanoparticle formulation used in conjunction with it.

[0030] As a preferred embodiment of the present invention: the nanoparticle formulation is a lyophilized 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 employing the system:

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

[0034] Monitor for signs of dysfunction in bypass graft vessels;

[0035] Assess changes in intracranial aneurysm wall tension;

[0036] Medical scenarios requiring simultaneous detection of vessel wall strain and near-wall blood flow.

[0037] Compared with the prior art, the beneficial effects of the present invention are:

[0038] 1. Small size and wide applicability: By combining a dual-ring scanning optical probe with an external CMOS imaging system, the probe's outer diameter can be reduced while maintaining image resolution, which is beneficial for use in narrow or tortuous blood vessels.

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

[0040] 3. Nanoparticle targeted tracking: Micro / nanoparticles have endothelial cell adhesion and are fluorescently labeled, which can form a clearly visible fluorescent signal on and near the blood vessel 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 the interventional surgical environment. Combined with the threshold warning function, it can help the operator to promptly determine the potential risks of plaque vulnerability, stent restenosis, or graft vessel failure. Detailed Implementation

[0042] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] In this embodiment of the invention, an image velocimetry system for blood vessels includes:

[0044] A targeted visualization nanoparticle drug delivery unit is used to inject micro / nanoparticles with endothelial adhesion and fluorescence visibility into a target blood vessel lumen.

[0045] A dual-ring scanning optical probe is used to achieve excitation light emission and fluorescence signal reception within the blood vessel lumen. The outer ring emits excitation light, while the inner ring receives fluorescence signals and transmits them to an external imaging device.

[0046] A CMOS imaging device is used to acquire image sequences corresponding to the aforementioned fluorescence signals;

[0047] The image acquisition and dual-domain correlation processing module is used to simultaneously execute a digital image correlation algorithm on the image sequence to obtain the blood vessel wall displacement / strain field, and a microparticle image velocimetry algorithm to obtain the 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 flow velocity field, and to visualize the output on the user interface.

[0049] Furthermore, the micro / nanoparticles have a particle size of 50–300 nm and are covalently grafted with specific peptide ligands on their 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 wavelength to improve the imaging signal-to-noise ratio.

[0051] Furthermore, the dual-ring scanning optical probe adopts a coaxial optical path structure and has circumferential scanning and axial movement functions to achieve full-range imaging of 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, iteration count, or correlation threshold in the DIC and μPIV algorithms based on image quality.

[0053] Furthermore, the coupled mechanical parameter calculation module is equipped with an early warning function. When the combined parameters of shear stress and principal strain exceed a preset risk threshold, a visual alarm is triggered.

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

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

[0056] b) Insert the dual-ring scanning optical probe into the target vascular segment through a catheter and start the scan;

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

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

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

[0060] f) Perform 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) Based on coupled mechanical parameters and preset thresholds, assess plaque vulnerability, stent restenosis, or risk of graft failure.

[0062] Furthermore, the present invention also provides a vascular detection device-nanoparticle composition, comprising the aforementioned system and a fluorescent targeted nanoparticle formulation used in conjunction with it.

[0063] As a preferred embodiment of the present invention: the nanoparticle formulation is a lyophilized 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 said system:

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

[0066] Monitor for signs of dysfunction in bypass graft vessels;

[0067] Assess changes in intracranial aneurysm wall tension;

[0068] Medical scenarios requiring simultaneous detection of vessel wall strain and near-wall blood flow.

[0069] This invention discloses an integrated DIC-μPIV system for detecting vascular strain-flow coupling, the complete operation of which includes the following steps:

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

[0071] The targeted visualization nanoparticles used in this invention are polymer-based composite micro / nanoparticles with a particle size in the range of 50–300 nm. The core of the particle can be polylactic-co-glycolic acid copolymer (PLGA) or polycaprolactone (PCL) as a biodegradable substrate. 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 localization specificity and residence time near the wall.

[0072] Embedding fluorescent dyes within the particles is recommended, using organic fluorophores with high quantum yield and strong stability, such as NileRed, Rhodamine B, or FITC (fluorescein isothiocyanate). FITC, in particular, has an excitation wavelength of 488–495 nm and an emission peak of approximately 520–530 nm, which, when matched with a 532 nm excitation light source, can effectively improve the system's imaging signal-to-noise ratio. To avoid photobleaching, an external anti-photodegradation coating (such as a PEG derivative) is recommended to protect the fluorescent molecules.

[0073] Prior to injection, resuspend the lyophilized formulation in 0.9% sodium chloride injection (pH 7.4) under aseptic conditions to prepare a homogeneous dispersion suspension of 0.5–1.0 mg / mL. Stir magnetically or sonicate for 10–30 seconds to prevent particle aggregation. A 10F catheter system is recommended, as it offers good flexibility and luminal permeability, making it suitable for precise delivery to the injection site during interventional procedures.

[0074] Target vessels are typically sites requiring lesion risk assessment, such as coronary arteries, carotid arteries, renal arteries, or peripheral arteries, especially areas with implanted stents, grafts, or atherosclerotic plaques. After particle injection, allow the particles to remain in place for 1–2 minutes to allow them to adhere to the endothelial surface and stabilize. During this time, blood flow can be temporarily blocked or the flow rate can be reduced via retrograde low-pressure flushing to optimize adhesion.

[0075] The attachment effect can be preliminarily verified by irradiating the particle area with low-intensity excitation light (laser power less than 5 mW, using continuous mode): turn on the excitation light source, collect 3-5 frames of fluorescence images through an imaging device, and analyze the change in signal intensity in the target area. If the fluorescence signal remains uniform and stable within 3 seconds (variation < 10%), it can be regarded as meeting the attachment standard, and then the next image acquisition process can be entered.

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

[0077] The double-ring scanning optical probe supporting this invention is an integrated optical sensing device with a micro coaxial structure, designed specifically for fluorescence imaging within blood vessels. Its structure includes: an outer-ring optical fiber channel for transmitting excitation light (typically 532 nm laser), and an inner-ring optical fiber channel for collecting fluorescence signals (520-560 nm emission). The two achieve a coaxial emission-reception path through a central optical collimation system, and a micro prism is embedded to achieve lateral irradiation and collection, ensuring that the blood vessel wall and the near-wall area can be irradiated and detected.

[0078] The front-end diameter of the probe is controlled within the range of 2.5-3.0 mm, and the length does not exceed 25 cm. The outer shell is coated with a flexible medical polymer (such as Pebax), having good bending performance and biocompatibility. The optical fiber uses a low-loss quartz optical fiber, with a minimum bending radius < 10 mm, suitable for curved and complex blood vessel channels such as coronary arteries and cerebral arteries. The entire probe is connected to a dedicated micro-drive system, with the following two degrees of freedom control capabilities:

[0079] Axial propulsion adjustment: precisely control the longitudinal advancement and retreat of the probe within the catheter through a stepper motor drive module, with a minimum step size of 0.1 mm;

[0080] Circumferential rotational scanning: The end of the probe is linked with a micro-rotary motor, enabling 360° full-angle scanning or scanning of a set angular segment, for constructing a circumferential imaging profile of the blood vessel wall.

[0081] During operation, first send the probe into the target blood vessel segment through a coaxial catheter channel (it is recommended to use an 8-10F triple-lumen catheter), and determine its positioning position through an intraoperative imaging navigation system (such as angiography or real-time IVUS echo). The head end of the probe is equipped with a radiopaque marker ring for spatial positioning under X-ray.

[0082] After positioning, start the laser excitation module. The excitation light power can be adjusted within the range of 1-20 mW / cm 2 , and the recommended initial setting is 10 mW / cm 2 , and it is emitted in continuous mode. The laser light source reaches the tissue around the blood vessel wall through the outer-ring optical fiber, exciting the fluorescent nanoparticles embedded or attached to the vascular endothelium to emit fluorescence signals.

[0083] The fluorescence signal is received by the inner-loop optical fiber and guided to the external CMOS imaging device via a multimode optical fiber. To improve signal quality, a bandpass filter (center wavelength 550nm, bandwidth 40nm) is integrated inside the probe to shield against excitation light interference, retaining only the emitted signal. The entire probe positioning and excitation process is completed within 2 minutes, followed by the image acquisition stage.

[0084] (3) Image acquisition:

[0085] The image acquisition stage of this invention employs a high-frame-rate, high-sensitivity CMOS imaging device in conjunction with a probe scanning system to acquire fluorescence images of the blood vessel wall and near-wall flow field. A high-speed CMOS camera with research-grade performance (such as the Photron FASTCAM Mini AX100 or Basler boost series) is recommended for this imaging device, and its key performance parameters are as follows:

[0086] Spatial resolution: 2048×2048 pixels;

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

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

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

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

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

[0092] To achieve coordinated excitation and acquisition, 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 stepping, CMOS camera acquisition frequency, and image buffer storage, achieving 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 to study the instantaneous changes in the interaction between the local blood vessel wall and blood flow;

[0094] Helical scanning acquisition mode: The probe constructs temporal-spatial combined image data of the vascular segment by axial advancement and circumferential rotation, which is used for three-dimensional mechanical field reconstruction.

[0095] The acquisition process is typically set to last 1–3 seconds, covering at least one complete cardiac cycle (reference value approximately 1.0–1.2 s). To ensure data sufficiency, it is recommended that each acquisition contain at least 500 frames, and the image sequence should include the following two types of information:

[0096] Image of statically attached particles: Fluorescent nanoparticles distributed on the surface of vascular endothelium, moving with the periodic deformation of the vascular wall, used for DIC analysis;

[0097] Flowing particle image: Suspended particles distributed in the blood flow undergo inter-frame displacement as they move with the blood flow, used for μPIV velocity field reconstruction.

[0098] During image acquisition, the laser power must be kept constant, and the camera employs 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 sequences or .raw binary format, facilitating subsequent parallel processing by DIC and μPIV algorithms. The system supports background noise suppression (through empty field image subtraction) and temperature drift correction during acquisition to ensure consistent image quality.

[0099] (4) Image processing and strain-flow 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), and can perform two types of image analysis tasks simultaneously:

[0101] (11) Digital image correlation analysis:

[0102] The DIC algorithm is used to evaluate minute deformations in the blood vessel wall region caused by pressure changes during the cardiac cycle, calculating sub-pixel-level displacement and strain information. The analysis process is as follows:

[0103] ① Image preprocessing: Image enhancement (histogram equalization or adaptive filtering) is performed on the static particle signal region to improve the clarity of particle boundaries;

[0104] ② Window division and cross-correlation calculation: Divide the wall area into multiple overlapping windows (typical window size is 32×32 pixels, overlap rate is 50%), perform gray-level cross-correlation calculation on adjacent frames, and use quadratic interpolation or Gaussian fitting to achieve sub-pixel registration accuracy.

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

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

[0107]

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

[0109] (22) Microparticle image velocimetry analysis (μPIV):

[0110] The μPIV algorithm is used to extract the motion trajectories 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 between static wall regions and moving particle regions using intensity threshold and Fourier spectrum screening methods;

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

[0113] ③ Velocity vector extraction: The instantaneous velocity is calculated by combining the offset value Δd corresponding to the main peak within each window with the inter-frame time Δt.

[0114]

[0115] ④ Velocity field interpolation and filtering: Dense velocity vector map is reconstructed using bicubic interpolation, and pseudo vectors are removed using median filtering or standard deviation elimination algorithms;

[0116] ⑤ Shear stress calculation: In the region near the wall, the velocity gradient is estimated using the first derivative, and then the shear stress τ is calculated.

[0117]

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

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

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

[0121] Wall Shear Stress (WSS, denoted as r);

[0122] Principal strain (ε1) of the vessel wall;

[0123] Pulsatile pressure rate (ΔP / Δt).

[0124] ① Time registration and point alignment

[0125] All image data are timestamped (1 μs resolution) and paired based on frame number and spatial pixel index. The system aligns data from multiple analysis windows within the same spatial region at the same time point, forming 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 indices.

[0128] ② Calculation of shear stress τ:

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

[0130]

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

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

[0133] To reduce the impact of boundary discontinuities, shear stress was calculated only within the range of 0-100 μm from the vessel wall and local smoothing was applied.

[0134] ③ Calculation of principal strain ε1

[0135] The principal strain is obtained from the two-dimensional strain tensor output by the DIC algorithm and is defined as the maximum eigenvalue of the tensor:

[0136]

[0137] Where, ε x ε y , where is the normal strain along the principal axis; γ is the shear strain component; and eig[·] is the eigenvalue solution function.

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

[0139] The system uses a simplified one-dimensional incompressible Navier-Stokes model, combined with velocity change information, to estimate the rate of change of local pressure.

[0140]

[0141] Where ρ is the blood density, set to 1050 kg / m³. 3 ; The velocity derivative with respect to time is calculated based on the velocity field across multiple frames; This represents the axial velocity gradient. The model assumes local laminar flow and slow changes in vascular rigidity.

[0142] ⑤ Coupling parameter matrix and index extraction

[0143] After outputting the triplet values ​​at each time point and for each observation window, the system can construct a coupled map of the flow field in the blood vessel wall:

[0144] Spatial heat map: Two-dimensional distribution of each parameter within a blood vessel segment;

[0145] Time curve: The trend of parameter changes at a selected point or region;

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

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

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

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

[0150] The proportion of high-risk coupling zones (the volume percentage of regions that meet the threshold τ>50kPa and ε1>3%).

[0151] This data will be pushed to the visualization module and used to make judgments based on the risk warning mechanism set up in the next step.

[0152] (6) Visualization and Risk Identification

[0153] The various indicators output by the coupled mechanical parameter calculation module will be 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 a visualization library based on OpenGL / VTK) with the clinical user interface, providing multimodal and interactive display methods, supporting rapid intraoperative interpretation and postoperative data archiving and analysis.

[0154] ①Visual output format:

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

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

[0157] The two-dimensional distribution plots of shear stress (τ), principal strain (ε1), and pulsating pressure change rate (ΔP / Δt) are displayed.

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

[0159] The layer overlay function supports displaying both blood vessel outline and biomechanical parameter layers simultaneously.

[0160] 2. Vector field overlay:

[0161] Displays blood flow velocity vector diagram and strain direction diagram, with options to display vector density and normalize its magnitude;

[0162] Users can click on the area of ​​interest to zoom in and view local vector details, and then analyze them in conjunction with the positional relationship of the walls.

[0163] 3. Trend chart:

[0164] Provides time-varying curves of mechanical parameters at a single observation point / region within a selected time point or period;

[0165] ECG synchronization markers can be superimposed to analyze the phase correspondence with the cardiac cycle;

[0166] It supports exporting to CSV, PDF, or image formats.

[0167] 4. 3D Coupled 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 lesion areas; it supports the clustering and classification of high-risk areas based on principal component analysis (PCA) or linear discriminant analysis (LDA).

[0169] ② Risk 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 determination logic: If any pixel region simultaneously satisfies the following two conditions:

[0172] Shear stress τ≥50kPa;

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

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

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

[0176] It is displayed on the interface with a flashing red frame;

[0177] Trigger a sound or vibration alert;

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

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

[0180] Example 1: System Structure and Working Mechanism

[0181] The system described in this invention includes the following core modules:

[0182] The system described in this invention includes the following core modules:

[0183] 1. Targeted Visualized Nanoparticle Drug Delivery Unit

[0184] The nanoparticles used in this system have a particle size ranging from 50 to 300 nm and are made from biodegradable polymer substrates 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 wavelengths in the range of 520–560 nm, to complement the 532 nm excitation light source used in the system and enhance the imaging signal-to-noise ratio. The particles are stored as lyophilized powder and resuspended in sterile saline before use to a working concentration of 0.5–1.0 mg / mL. Injection is performed using a 10F guiding catheter system (such as the ShuttleSelect catheter), inserted into the target vessel segment (such as the coronary or carotid artery) via the femoral or radial artery. After injection, the particles are allowed to stand for 1–2 minutes to ensure stable adhesion to the vessel wall.

[0185] 2. Dual-ring scanning optical probe

[0186] The probe employs a coaxial dual-ring structure with an overall diameter controlled to ≤2.0mm to accommodate standard interventional catheter lumens. The outer ring uses a fiber optic channel to transmit excitation light (532nm), while the inner ring incorporates a multimode fiber array or microlens system to receive emitted fluorescence signals. The probe features 0–360° continuous circumferential rotation and a maximum axial advance capability of 20mm, achieved through precise control via a stepper motor and encoder. A low-pass filter is integrated at the probe output to shield against excitation light leakage and optimize fluorescence acquisition purity.

[0187] 3. CMOS imaging device

[0188] The system uses an external high-speed CMOS camera (e.g., 2048×2048 resolution, ≥5000fps frame rate) to receive fluorescence signals via an optical fiber path, and is integrated with the probe rotation and laser synchronization control module. The camera employs a global shutter mode to avoid image distortion during high-speed motion. The acquisition controller supports ECG synchronous 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 in real time to the image processing server via Gigabit Ethernet or PCIe interface. The processing flow includes:

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

[0192] Microparticle image velocimetry (μPIV) analysis: Using a two-frame cross-correlation, window iterative optimization, and background filtering algorithm, the velocity vector of suspended particles in the near-wall region is reconstructed, and a two-dimensional velocity field and local shear stress map are output.

[0193] 5. Coupled Mechanical Parameter Calculation Module

[0194] This module registers the DIC and μPIV results according to 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 strain along the maximum principal axis is obtained by solving the eigenvalues ​​of the strain tensor.

[0197] The rate of change of pulsating pressure ΔP / Δt: obtained by back-calculation using the Navier–Stokes one-dimensional simplified model.

[0198] All parameters are output in the form of graphs, time curves, and three-dimensional coupled feature space. If τ·ε1 > 50 kPa·%, the system will trigger an alert mechanism, highlighting the suspected lesion area on the interface and generating a log record.

[0199] Example 2: Clinical Use Procedure

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

[0201] 1. Under sterile conditions 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 (such as the proximal left anterior descending artery) through an interventional catheter (10F) and let it stand for 1–2 minutes to complete endothelial surface adhesion;

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

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

[0205] 5. After processing by the DIC and μPIV analysis modules, the images generate vessel wall strain maps and blood flow velocity maps;

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

[0207] Doctors use the imaging results to determine whether to intervene immediately (such as re-implanting a stent or expanding the area), or to save the data for postoperative follow-up and individualized 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 implemented 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 exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, it is intended that all variations falling within the meaning and scope of equivalents of the claims be included within the present invention.

[0209] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. An image velocimetry system for blood vessels, characterized in that, include: 1) Targeted visualization nanoparticle drug delivery unit, used to inject micro / nanoparticles with endothelial adhesion and fluorescence visibility into the target blood vessel lumen. The micro / nanoparticles have a particle size of 50-300 nm, use polylactic acid-glycolic acid copolymer or polycaprolactone as the substrate, and covalently graft integrin targeting peptide ligands on the particle surface to selectively adhere to vascular endothelial cells. The particles are embedded with an organic fluorescent dye with an excitation wavelength of 488-495 nm and a fluorescence emission peak at 520-560 nm. 2) Dual-ring scanning coaxial optical probe, used to realize excitation light emission and fluorescence signal reception in the blood vessel lumen, including an outer ring fiber channel and an inner ring fiber channel, wherein the outer ring fiber channel transmits 532 nm excitation light, and the inner ring fiber channel receives fluorescence signals in the 520-560 nm band, and realizes full-range imaging of the target blood vessel segment in the circumferential and longitudinal directions through circumferential scanning and axial movement. 3) A CMOS imaging device is used to acquire image sequences corresponding to the fluorescence signals transmitted by the dual-ring scanning coaxial optical probe. The frame rate of the imaging device is adjustable from 1000 to 5000 frames per second, and it adopts a global shutter working mode. 4) Image acquisition and dual-domain correlation processing module, connected to the CMOS imaging device, is used to simultaneously execute digital image correlation algorithm on the same time axis of the image sequence to obtain the displacement field and strain field of the blood vessel wall in the wall speckle region formed by micro / nano particles attached to the surface of the blood vessel endothelium, and to execute microparticle image velocimetry algorithm to obtain the blood flow velocity field and shear stress field. 5) Coupled mechanical parameter calculation and early warning module, connected to the image acquisition and dual-domain correlation processing module, is used to calculate the coupling parameters of blood flow shear stress, wall principal strain and pulsating pressure based on the time synchronization of the strain field and flow velocity field, and to visualize the output on the user interface.

2. The system according to claim 1, characterized in that, The digital image correlation algorithm uses a 32×32 pixel overlapping sub-window to perform gray-level cross-correlation analysis on the blood vessel wall region, and the microparticle image velocimetry algorithm uses a 64×64 pixel overlapping sub-window to perform fast Fourier transform cross-correlation analysis on the near-wall flow field region.

3. The system according to claim 1, characterized in that, The dual-ring scanning coaxial optical probe is driven by a stepper motor to achieve continuous circumferential scanning from 0 to 360 degrees, with an axial advance step length of not less than 0.1 mm.

4. The system according to claim 1, characterized in that, The coupled mechanical parameter calculation and early warning module, based on the calculation of shear stress τ and principal strain ε1, also estimates the pulsating pressure change rate ΔP / Δt based on the one-dimensional simplified Navier-Stokes equations and the time derivative of the velocity field, and constructs a three-dimensional coupled feature space with shear stress τ, principal strain ε1 and pulsating pressure change rate ΔP / Δt as variables.

5. The system according to claim 1, characterized in that, The image acquisition and dual-domain correlation processing module can adaptively adjust the window size, number of iterations, or correlation threshold in the digital image correlation algorithm and microparticle image velocimetry algorithm according to the image quality.

6. The system according to claim 1, characterized in that, The CMOS imaging device is synchronized with the electrocardiogram signal to ensure that the image sequence covers at least one complete cardiac cycle.

7. A method for assessing the risk of vascular lesions based on image sequences acquired by the system according to any one of claims 1-6, characterized in that, include: a) Obtain a sequence of fluorescence images acquired in the target vascular segment using the system described in any one of claims 1-6; b) Perform a digital image correlation algorithm on the speckle region of the blood vessel wall in the fluorescence image sequence to obtain the displacement field and principal strain field of the blood vessel wall; c) Perform the μPIV algorithm on the image sequence to obtain the blood flow velocity field and shear stress distribution; d) Perform time synchronization registration on the strain field and velocity field obtained in steps b) and c), and calculate the coupled mechanical parameters of shear stress τ, principal strain ε1 and pulsating pressure change rate ΔP / Δt; e) Compare the coupling mechanical parameters with a preset risk threshold. If the preset risk threshold is exceeded, mark the corresponding blood vessel wall area as a high-risk area and provide a visual prompt on the user interface.

8. A vascular detection device-nanoparticle composition, characterized in that, The invention includes the image velocimetry system for blood vessels as described in any one of claims 1-6 and the fluorescent targeted nanoparticle formulation used in conjunction with it, wherein the fluorescent targeted nanoparticle formulation is a lyophilized powder containing polylactic acid-glycolic acid copolymer or polycaprolactone substrate, integrin targeting peptide, and fluorescent dye with emission peak located at 520-560 nm.

9. The composition according to claim 8, characterized in that, Before use, the lyophilized fluorescent targeted nanoparticle powder is dissolved in 0.9% sodium chloride injection to prepare a suspension of 0.5-1.0 mg / mL, and then injected into the target vascular segment via an 8-10F catheter system.

10. The application of the system according to any one of claims 1-6 in medical scenarios such as assessing the risk of restenosis after coronary artery stenting, monitoring signs of dysfunction of bypass graft vessels, evaluating changes in intracranial aneurysm wall tension, or simultaneously detecting vessel wall strain and proximal blood flow.

Images