Low-pulse ultrasonic physiotherapy device for treating primary sjogren syndrome

Abstract

The invention relates to the technical field of medical instruments, in particular to a low-pulse ultrasonic physiotherapy device for treating primary sjogren syndrome. The device comprises a multi-modal medical image fusion and gland intelligent segmentation module, a gland specificity three-dimensional scanning path planning module, a tissue acoustic characteristic real-time compensation and dynamic focusing correction module and a non-thermal effect guided pulse parameter intelligent optimization module. According to the invention, through accurate positioning of a gland structure, intelligent planning of a scanning path, real-time compensation of acoustic characteristics of tissues, optimization of non-thermal effect parameters, real-time monitoring of functional response and closed-loop adjustment of treatment parameters, the system can be applied to treatment of the glands. According to the method, accurate, individualized and non-invasive treatment on salivary glands and lacrimal glands is achieved, precise gland targeting with millimeter-level precision is achieved, especially glands with complex branch structures can be comprehensively covered, and meanwhile sensitive structures such as facial nerves can be avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, and in particular to a low-pulse ultrasonic physiotherapy device for treating primary Sjögren's syndrome. Background Art

[0002] Primary Sjögren's syndrome (SS) is a common autoimmune disease characterized by the progressive destruction of exocrine glands, leading to symptoms such as dry mouth and dry eyes. Current clinical treatments include medication, artificial tears and saliva substitutes, and local glandular injections, but these methods all have limitations.

[0003] Regarding medication, immunosuppressants and glucocorticoids can reduce inflammation, but long-term use may cause systemic side effects. Cholinergic agonists such as pilocarpine hydrochloride can promote secretion, but their effectiveness is limited and is associated with multiple adverse reactions. Artificial substitutes only temporarily relieve symptoms and do not improve glandular function. Local injections into the gland require repeated procedures and carry the risk of infection, bleeding, and nerve damage.

[0004] Existing ultrasound therapy technologies primarily focus on the thermal effects of high-intensity focused ultrasound (HIFU), which is used for tissue ablation. This approach is unsuitable for conditions like Sjögren's syndrome, where glandular function preservation and restoration are crucial. Studies have shown that low-intensity ultrasound may promote cellular function through non-thermal effects, but existing devices lack the ability to precisely target glandular structures and are unable to dynamically adjust treatment parameters based on individual functional responses.

[0005] Therefore, there is an urgent need for a low-pulse ultrasound therapy device that can precisely target the glandular-specific anatomical structure of Sjögren's syndrome, utilize a non-thermal effect mechanism, and adjust treatment parameters in real time according to the glandular function response. Summary of the Invention

[0006] The purpose of the present invention is to provide a low-pulse ultrasound therapy device for the treatment of primary Sjögren's syndrome. By accurately positioning the glandular structure, intelligently planning the scanning path, real-time compensation of tissue acoustic characteristics, optimization of non-thermal effect parameters, real-time monitoring of functional response and closed-loop adjustment of treatment parameters, accurate, individualized and non-invasive treatment of salivary glands and lacrimal glands can be achieved.

[0007] The present invention provides a low-pulse ultrasound physiotherapy device for treating primary Sjögren's syndrome, comprising:

[0008] Multimodal medical image fusion and gland intelligent segmentation module, which is used to obtain multimodal medical image data of the patient's glands, perform image registration and automatic gland segmentation, and generate a three-dimensional gland model;

[0009] a gland-specific 3D scanning path planning module, communicatively connected to the multimodal medical image fusion and gland intelligent segmentation module, configured to receive the 3D gland model, analyze the gland morphological characteristics and functional area distribution based on the 3D gland model, and generate a gland-specific 3D scanning path;

[0010] a tissue acoustic characteristics real-time compensation and dynamic focus correction module, which is in communication with the gland-specific three-dimensional scanning path planning module and is used to receive the gland-specific three-dimensional scanning path, construct a tissue acoustic model, calculate a phase compensation value, and achieve precise focusing;

[0011] a non-thermal effect guided pulse parameter intelligent optimization module, in communication with the tissue acoustic characteristics real-time compensation and dynamic focus correction module, for determining the non-thermal effect guided pulse parameters based on the glandular status assessment results;

[0012] a glandular function response feedback closed-loop treatment control module, which is in communication with the non-thermal effect-guided pulse parameter intelligent optimization module and the tissue acoustic characteristics real-time compensation and dynamic focus correction module, and is used to monitor glandular function response data in real time and dynamically adjust the pulse parameters and the phase compensation value based on the glandular function response data;

[0013] The multi-channel ultrasonic transducer driving module is communicatively connected to the real-time compensation and dynamic focusing correction module for tissue acoustic characteristics, the non-thermal effect-guided pulse parameter intelligent optimization module, and the closed-loop treatment control module for glandular function response feedback, and is used to receive the phase compensation value and the pulse parameters and control the phased array ultrasonic transducer to generate focused ultrasonic waves.

[0014] Preferably, the multimodal medical image fusion and gland intelligent segmentation module includes:

[0015] An image preprocessing unit, configured to perform denoising, grayscale normalization, and contrast enhancement on the multimodal medical image data;

[0016] A multimodal image registration unit, which is used to perform coarse registration using a rigid transformation based on anatomical landmark matching and fine registration using a non-rigid registration based on mutual information, aligning images of different modalities to a unified coordinate system;

[0017] The gland intelligent segmentation unit is used to automatically segment the glands in the registered medical images using a deep learning network to identify the main gland structure, internal duct system, and surrounding important anatomical structures;

[0018] Interactive segmentation correction unit, which provides doctors with an interactive interface and supports manual review and correction of automatic segmentation results;

[0019] The three-dimensional model reconstruction unit is used to generate a three-dimensional gland model based on the segmentation results and mark the degree of inflammation, degree of fibrosis and functional area attributes.

[0020] Preferably, the gland-specific three-dimensional scanning path planning module includes:

[0021] a gland morphology analysis unit, configured to perform skeletonization processing on the three-dimensional gland model, extract the gland branch structure, and perform hierarchical division;

[0022] Functional area mapping unit, used to identify different functional areas based on enhanced MRI signal characteristics, evaluate inflammatory activity and functional preservation, and generate functional area labeling data;

[0023] A treatment prioritization unit is used to assign treatment priorities to different areas based on inflammatory activity and functional preservation, and to mark sensitive protection areas;

[0024] A scanning path generating unit, configured to select an adaptive scanning mode for glandular structures at different levels and generate a three-dimensional scanning path;

[0025] The path optimization and verification unit is used to optimize the generated scanning path to ensure the balance between coverage, treatment time and safety, and perform path feasibility verification.

[0026] Preferably, the tissue acoustic characteristics real-time compensation and dynamic focus correction module includes:

[0027] A tissue acoustic model construction unit is used to construct a multi-level tissue acoustic model based on the segmentation results and assign sound velocity, attenuation coefficient and density parameters to different tissues;

[0028] An acoustic wave propagation analysis unit, used to analyze the acoustic wave propagation path from each array element to the target focus using a ray tracing method and calculate the cumulative delay;

[0029] A phase compensation calculation unit is used to calculate the phase compensation value of each array element according to the sound wave propagation analysis result and generate a phase compensation matrix;

[0030] A real-time focus monitoring unit, which is used to send low-energy detection pulses at predetermined intervals, analyze the echo signals, and evaluate the focus position accuracy;

[0031] The dynamic correction unit is used to update the phase compensation matrix based on the real-time focus monitoring results to achieve dynamic correction of the focus position.

[0032] Preferably, the non-thermal effect-guided pulse parameter intelligent optimization module includes:

[0033] Non-thermal effect mechanism modeling unit, used to establish parameter relationship models of micromechanical stress effect, acoustic pore effect and acoustic microfluidic effect;

[0034] Glandular status assessment unit, used to grade and evaluate glandular inflammatory activity, degree of fibrosis, and degree of functional preservation;

[0035] a parameter matching unit for selecting an initial pulse parameter range, including frequency, sound intensity, pulse repetition frequency, pulse width, and duty cycle, based on the glandular status assessment result;

[0036] A multi-objective parameter optimization unit is used to maximize non-thermal effects while minimizing thermal effects to generate the optimal pulse parameter combination;

[0037] Thermal effect monitoring unit, used to predict and monitor temperature changes during treatment to ensure that safety thresholds are not exceeded.

[0038] Preferably, the closed-loop treatment control module for glandular function response feedback includes:

[0039] Glandular function monitoring unit, used to monitor changes in saliva or tear secretion rate in real time using a micro-flow sensor;

[0040] Response curve analysis unit, used to extract characteristic parameters such as baseline value, response latency, rise rate, peak response and maintenance time from monitoring data;

[0041] Individualized response model unit, used to establish an individualized glandular function response dynamics model based on response characteristics;

[0042] A treatment strategy generation unit, which is used to dynamically generate the optimal treatment strategy based on the individualized response model and preset treatment goals;

[0043] The parameter adjustment unit is used to automatically adjust the pulse parameters and treatment time according to the response situation to achieve closed-loop control.

[0044] Preferably, the multi-channel ultrasonic transducer driving module includes:

[0045] A phase control unit, configured to receive the phase compensation value and control the phase delay of each array element;

[0046] A pulse control unit, configured to receive the pulse parameters and control the frequency, intensity, pulse repetition frequency, pulse width and duty cycle of the ultrasonic wave;

[0047] A multi-channel signal generation unit, used to generate a driving signal for each array element;

[0048] A power amplifying unit, used for amplifying the power of the driving signal;

[0049] Impedance matching unit, used to perform electrical impedance matching to improve energy transmission efficiency;

[0050] The safety monitoring unit is used to monitor the system operation status in real time to ensure that the system operates within the safety parameter range.

[0051] Preferably, the tissue acoustic characteristics real-time compensation and dynamic focus correction module is further used for:

[0052] Controlling the phased array ultrasonic transducer to form a multi-focal point or a focal spot of a specific shape, including a linear focal spot, a planar focal spot, a curved focal spot, or a volume-covered focal spot;

[0053] Adjust focus depth, focus position and focus size in real time;

[0054] Compensate for the refraction and reflection effects of sound waves at different tissue interfaces;

[0055] The focus position error is calculated in real time, and the correction process is triggered when the error exceeds a preset threshold.

[0056] Preferably, the parameter range of the non-thermal effect-guided pulse parameter intelligent optimization module is:

[0057] Frequency range: 1.0-3.5MHz;

[0058] Sound intensity range: 30-120W / cm²;

[0059] Pulse repetition frequency range: 20-50Hz;

[0060] Pulse width range: 100-500μs;

[0061] Duty cycle range: 0.2-2.0%;

[0062] Among them, higher frequency, lower sound intensity and lower duty cycle are used for mildly atrophic glands; lower frequency, higher sound intensity and higher duty cycle are used for severely atrophic glands.

[0063] Preferably, the closed-loop treatment control module for glandular function response feedback further comprises:

[0064] Efficacy evaluation unit, used to evaluate treatment efficacy based on the objective secretion rate improvement percentage and changes in subjective symptom scores;

[0065] Prognostic prediction unit, used to predict the long-term efficacy maintenance time and functional recovery degree based on early response characteristics;

[0066] Treatment plan recording unit, used to record complete treatment parameters, response data and efficacy evaluation results;

[0067] Long-term follow-up management unit, used to arrange follow-up plans and collect long-term efficacy data;

[0068] The knowledge base updating unit is used to continuously optimize treatment strategies based on treatment data and follow-up results to form an experience knowledge base.

[0069] The beneficial effects of the present invention include:

[0070] 1. Achieve precise gland targeting with millimeter-level accuracy, especially for glands with complex branching structures, achieving comprehensive coverage while avoiding sensitive structures such as the facial nerve, significantly improving treatment safety and effectiveness;

[0071] 2. Treatment is based on non-thermal effect mechanisms to avoid additional damage to glandular tissue caused by thermal injury, and promotes the recovery of glandular function through the synergistic effects of micromechanical stress effect, sonoporation effect and acoustic microfluidic effect;

[0072] 3. By real-time monitoring of glandular function responses and closed-loop adjustment of treatment parameters, personalized precision treatment can be achieved, avoiding overtreatment and undertreatment, and maximizing the benefit / risk ratio;

[0073] 4. Non-invasive treatment method, no need for anesthesia, no risk of infection, good patient tolerance, suitable for repeated treatment and long-term maintenance treatment;

[0074] 5. Fill the technical gap in the field of physical therapy for Sjögren's syndrome and provide new treatment options for patients who are not suitable for or unwilling to receive long-term drug treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 This is a schematic diagram of the system architecture of a low-pulse ultrasound physiotherapy device for treating primary Sjögren's syndrome according to the present invention;

[0076] Figure 2 Schematic diagram of the structure of the multimodal medical image fusion and gland intelligent segmentation module of the present invention;

[0077] Figure 3 This is a schematic diagram of the structure of the gland-specific three-dimensional scanning path planning module of the present invention;

[0078] Figure 4 Schematic diagram of the structure of the real-time compensation and dynamic focus correction module of tissue acoustic characteristics of the present invention;

[0079] Figure 5 This is a schematic diagram of the structure of the non-thermal effect-oriented pulse parameter intelligent optimization module of the present invention;

[0080] Figure 6 This is a schematic diagram of the structure of the closed-loop treatment control module for glandular function response feedback of the present invention;

[0081] Figure 7 Schematic diagram of the structure of the multi-channel ultrasonic transducer driving module of the present invention;

[0082] Figure 8 A schematic diagram of a treatment process in one embodiment of the present invention;

[0083] Figure 9 Schematic diagram of the phased array ultrasonic transducer system of the present invention;

[0084] Figure 10 Schematic diagram of glandular function response curve in one embodiment of the present invention. DETAILED DESCRIPTION

[0085] Please refer to the attached Figure 1-10 The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood by those skilled in the art that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention.

[0086] like Figure 1 As shown in the figure, the present invention provides a low-pulse ultrasound therapy device for treating primary Sjögren's syndrome, comprising a multimodal medical image fusion and glandular intelligent segmentation module 1, a gland-specific 3D scanning path planning module 2, a tissue acoustic property real-time compensation and dynamic focus correction module 3, a non-thermal effect-guided pulse parameter intelligent optimization module 4, a closed-loop treatment control module with glandular function response feedback 5, and a multi-channel ultrasonic transducer drive module 6. Each module is interconnected via a standardized data interface to form a complete treatment system.

[0087] like Figure 2 As shown, the multimodal medical image fusion and gland intelligent segmentation module 1 is used to acquire multimodal medical image data of a patient's glands, perform image registration and automatic gland segmentation, and generate a three-dimensional gland model. This module includes an image preprocessing unit 11, a multimodal image registration unit 12, a gland intelligent segmentation unit 13, an interactive segmentation correction unit 14, and a three-dimensional model reconstruction unit 15.

[0088] The image preprocessing unit 11 is used to perform denoising, grayscale standardization and contrast enhancement on multimodal medical image data. In one embodiment of the present invention, the image preprocessing unit 11 supports image data obtained by various imaging methods including B-ultrasound, MRI, CT, CBCT, etc. For images with large noise, an adaptive Gaussian filtering algorithm is used for denoising, which can reduce the noise by more than 60%. For images acquired by different devices and at different times, grayscale standardization is performed to ensure that the grayscale value range is consistent, which is convenient for subsequent analysis. Preferably, all images are resampled to a voxel resolution of 0.5mm to ensure consistent spatial resolution. In addition, histogram equalization technology is used to enhance the contrast between the gland and the surrounding tissue, making the gland structure clearer and more discernible.

[0089] The multimodal image registration unit 12 is used to perform coarse registration using a rigid transformation based on anatomical landmark matching and fine registration using non-rigid registration based on mutual information, aligning the images of different modalities to a unified coordinate system. In this embodiment of the present invention, the coarse registration process first identifies key anatomical landmarks (such as the mandibular angle, zygomatic arch, and nasolabial groove), then calculates the optimal rigid transformation matrix to achieve preliminary spatial alignment. The fine registration process divides the image into an 8×8×8 grid, calculates the local deformation field within each grid, and smoothes the deformation field using B-spline interpolation to ensure anatomical continuity. Registration quality is evaluated based on the average distance error of the landmarks (targeted to be less than 0.5 mm), the mutual information value (greater than 90% compared to standard registration), and the physician's visual score (no less than 4 points on a 5-point scale).

[0090] The gland intelligent segmentation unit 13 is used to perform automatic gland segmentation on the registered medical images using a deep learning network to identify the main gland structure, internal duct system, and surrounding important anatomical structures. In a preferred embodiment of the present invention, the following deep learning architecture is used for segmentation:

[0091] The encoder consists of a five-layer convolutional network with feature channels doubling from 64 to 1024 layer by layer; the decoder consists of a five-layer deconvolutional network with feature channels halved layer by layer. Each encoder feature map is directly connected to the corresponding decoding layer via skip connections. A spatial attention module is added at the skip connections to highlight glandular boundary features. The network model was trained using multimodal images (MRI + US) of 300 patients with Sjögren's syndrome. The dataset was expanded tenfold through rotation, scaling, flipping, and brightness adjustment. The loss function uses a combination of Dice loss, cross-entropy loss, and boundary-aware loss. The learning rate was initially set to 0.001 and gradually decayed based on validation set performance.

[0092] The interactive segmentation correction unit 14 provides a physician interface, enabling manual review and correction of automated segmentation results. This unit includes a 3D MPR display (simultaneously displaying axial, sagittal, and coronal views), a volume rendering view (stereoscopically displaying the relationship between the gland and surrounding structures), and an interactive toolbar (correction toolset). Correction algorithms include adaptive region growing based on user markers, fine-tuning boundaries using the level set method, and a multi-level correction process that supports coarse-to-fine adjustments. To ensure real-time response, the system utilizes GPU-accelerated computing, keeping correction response times under 100ms. It also precomputes candidate regions to reduce interaction latency. A multi-resolution strategy allows for rapid low-resolution processing of large regions.

[0093] The 3D model reconstruction unit 15 generates a 3D glandular model based on the segmentation results, labeling the degree of inflammation, fibrosis, and functional area attributes. This unit first converts the voxel labels into a triangular mesh (using the MarchingCubes algorithm), then performs mesh simplification and smoothing to reduce the number of triangles by 30-50%. The model data structure includes geometric information (vertex coordinates, normal vectors, triangle connectivity), attribute information (tissue type, lesion severity, functional score), and topological information (glandular branching structure and ductal system connectivity). The final model is stored in the standardized VTK / STL format to support subsequent processing.

[0094] like Figure 3 As shown, the gland-specific 3D scanning path planning module 2 is communicatively connected to the multimodal medical image fusion and gland intelligent segmentation module 1. It receives a 3D gland model, analyzes gland morphology and functional area distribution based on the 3D gland model, and generates a gland-specific 3D scanning path. This module includes a gland morphology analysis unit 21, a functional area mapping unit 22, a treatment priority division unit 23, a scanning path generation unit 24, and a path optimization verification unit 25.

[0095] The glandular morphology analysis unit 21 is used to perform skeletonization on the 3D glandular model, extract the glandular branching structure, and perform hierarchical segmentation. In one embodiment of the present invention, the skeletonization extraction method first calculates the shortest distance from the glandular interior point to the boundary (distance transformation), then identifies the local maximum points in the distance field (ridge extraction), then removes redundant branches while maintaining topological consistency (skeleton refinement), and finally identifies the main ductal system based on diameter and connectivity (trunk identification). Based on branch diameter, the glandular structure is divided into four levels: the first level of main ducts (diameter greater than 1.5 mm), the second level of secondary branch ducts (diameter 0.8-1.5 mm), the third level of small branch ducts (diameter 0.3-0.8 mm), and the fourth level of alveolar clusters (diameter less than 0.3 mm). Feature parameters such as branch angle, branch length, branch density, and volume distribution are also calculated to provide basic data for subsequent path planning.

[0096] The functional region mapping unit 22 is used to identify different functional regions based on enhanced MRI signal characteristics, assess inflammatory activity and functional preservation, and generate functional region labeling data. In a preferred embodiment of the present invention, the functional region identification method uses enhanced MRI perfusion assessment to classify glandular regions into early enhancement regions (areas with high blood supply), delayed enhancement regions (areas with fibrosis), and low perfusion regions (areas with reduced function). Inflammation assessment based on T2-weighted signals classifies glandular regions into high-signal regions (areas with active inflammation) and low-signal regions (areas with fibrosis or atrophy). Furthermore, secretory activity assessment based on functional imaging classifies glandular regions into high-activity regions (areas with preserved secretory function) and low-activity regions (areas with reduced function). The functional assessment results are mapped onto a three-dimensional model, and inflammatory activity, fibrosis degree, and functional preservation degree are labeled on a four-level scale (0-3 points).

[0097] The treatment priority division unit 23 is used to assign treatment priorities to different areas based on inflammatory activity and functional preservation, and to mark sensitive protection areas. In this embodiment of the present invention, the priority scoring system divides glandular regions into four categories: areas with high inflammatory activity and good functional preservation are the highest priority (function-preserving areas); areas with high inflammatory activity and decreased functional capacity are high priority (inflammation-reducing areas); areas with low inflammatory activity and moderate functional preservation are medium priority (function-maintaining areas); and areas with low inflammatory activity and functional loss are low priority (late-stage atrophy areas). Furthermore, the facial nerve and its branches are automatically designated as protection zones, major blood vessels as avoidance zones, the temporomandibular joint as a restricted energy zone, and the tissues surrounding the tympanic membrane as a restricted zone.

[0098] The scanning path generation unit 24 is used to select an adaptive scanning mode for different levels of glandular structure and generate a three-dimensional scanning path. In a preferred embodiment of the present invention, the path generation strategy uses different scanning modes based on the characteristics of the glandular structure: a continuous line scanning mode along the main duct centerline is used for the main duct; a radial scanning mode based on branch points is used for secondary branches; a gridded volume coverage mode is used for small branch areas; and a spiral or convoluted coverage mode is used for the alveolar cluster area.

[0099] The path optimization and verification unit 25 is used to optimize the generated scanning path to ensure a balance between coverage, treatment time, and safety, and to perform path feasibility verification. In this embodiment of the present invention, path optimization objectives include maximizing treatment coverage (target tissue coverage greater than 95%), minimizing treatment time (optimizing total path length), avoiding sensitive areas (maintaining a safe distance greater than 3 mm from sensitive structures), and ensuring uniform energy distribution (maintaining spacing between adjacent path points between 0.5 and 1.0 mm). Path smoothing and constraints include curvature constraints (maximum curvature radius greater than 5 mm, avoiding sharp turns), speed constraints (movement speed between adjacent points less than 10 mm / s²), acceleration constraints (rate of change of velocity less than 5 mm / s²), and smoothing (using cubic spline interpolation to ensure path smoothness). Preferably, the treatment sequence is optimized according to a "mainline catheter first" strategy (treating the main duct first, then the branches), a "deep to shallow" strategy (treating deep tissue first, then superficial tissue), and a "prioritization" strategy (treating treatments based on potential for functional preservation). At the same time, the path is verified, including collision detection (checking whether the path crosses the restricted area), coverage analysis (calculating the coverage percentage of the target tissue), energy distribution simulation (predicting the energy deposition distribution in each area) and treatment time estimation (based on path length and dwell time).

[0100] like Figure 4 As shown, the real-time tissue acoustic property compensation and dynamic focus correction module 3 is in communication with the gland-specific 3D scanning path planning module 2. It is used to receive the gland-specific 3D scanning path, construct a tissue acoustic model, calculate phase compensation values, and achieve precise focusing. This module includes a tissue acoustic model construction unit 31, an acoustic wave propagation analysis unit 32, a phase compensation calculation unit 33, a real-time focus monitoring unit 34, and a dynamic correction unit 35.

[0101] The tissue acoustic model construction unit 31 is used to construct a multi-layer tissue acoustic model based on the segmentation results, assigning sound velocity, attenuation coefficient, and density parameters to different tissues. In one embodiment of the present invention, tissue classification and parameterization classifies human head and neck tissue into the following categories: skin layer (thickness 1-2 mm, sound velocity approximately 1720 m / s, attenuation approximately 2.0 dB / cm / MHz), fat layer (large thickness variation, sound velocity approximately 1450 m / s, attenuation approximately 0.8 dB / cm / MHz), muscle layer (sound velocity varies in different directions, averaging approximately 1580 m / s, attenuation approximately 1.5 dB / cm / MHz), glandular tissue (sound velocity approximately 1540 m / s, attenuation approximately 1.0 dB / cm / MHz), and bone structure (sound velocity approximately 3500 m / s, attenuation approximately 8.0 dB / cm / MHz). Patient-specific parameter estimation establishes a patient-specific acoustic parameter table by inferring tissue type based on image grayscale values ​​and correcting for individual differences through test pulse feedback. The 3D acoustic model is represented by voxelization with a resolution of 0.5 mm isovoxels to ensure the expression of fine structures. Each voxel is assigned with sound velocity, attenuation, density, and impedance values.

[0102] The acoustic wave propagation analysis unit 32 is used to analyze the acoustic wave propagation path from each array element to the target focus using a ray tracing method and calculate the cumulative delay. In a preferred embodiment of the present invention, the ray tracing method first starts from each array element and calculates the ideal straight line path to the target focus. Then, Snell's law is applied at different tissue interfaces to calculate the refraction effect, while considering the reflection loss and calculating the energy transfer efficiency. The wavefront delay calculation includes calculating the cumulative delay on each path, considering the phase offset caused by tissue velocity differences, and establishing a delay mapping table from the array element to the focus. The path optimization selection evaluates the energy transfer efficiency of each possible path, selects the path combination with the least energy attenuation, and balances coverage uniformity and energy efficiency.

[0103] The phase compensation calculation unit 33 is used to calculate the phase compensation value for each array element based on the results of the acoustic wave propagation analysis and generate a phase compensation matrix. In one embodiment of the present invention, static phase compensation calculates the initial phase compensation value based on the anatomical structure, assigns an initial delay time to each array element, and constructs an array element-delay mapping table for initial focusing. The adaptive phase compensation algorithm includes: basic delay calculation (taking into account the geometric distance from the array element to the target point and the difference in sound speed), heterogeneous tissue compensation (calculating additional delay based on the acoustic model), real-time feedback correction (adjusting the compensation value based on the probe pulse echo), and smooth transition processing (avoiding sudden changes in compensation values ​​between adjacent treatment points).

[0104] The real-time focus monitoring unit 34 is used to send low-energy probe pulses at predetermined intervals, analyze the echo signals, and assess focus position accuracy. In a preferred embodiment of the present invention, echo signal analysis includes amplitude analysis (reflecting energy deposition efficiency), phase analysis (assessing focus position accuracy), and spectrum analysis (detecting nonlinear effects). Sound field visualization includes real-time sound field intensity distribution, focus quality scoring (clarity, symmetry, size), and quantitative deviation display (actual vs. ideal).

[0105] The dynamic correction unit 35 is used to update the phase compensation matrix based on real-time focus monitoring results, enabling dynamic correction of the focal position. In one embodiment of the present invention, the dynamic phase update mechanism transmits low-energy probe pulses every 50 ms, analyzes echo signal characteristics (arrival time, amplitude, and phase), calculates the deviation between the actual focal position and the target position, updates the phase compensation value, and corrects the focal position. The automatic error correction mechanism automatically initiates correction when a deviation exceeding a 0.3mm threshold is detected. Large deviations (greater than 1mm) trigger a treatment pause and a warning. Operator intervention is required after three consecutive correction failures.

[0106] In addition, the real-time compensation of tissue acoustic characteristics and dynamic focus correction module 3 is also used to control the phased array ultrasonic transducer to form multiple focal spots or focal spots of specific shapes, including linear focal spots, surface focal spots, curved focal spots or volume coverage focal spots; adjust the focus depth, focus position and focus size in real time; compensate for the sound wave refraction and reflection effects of different tissue interfaces; calculate the focus position error in real time, and trigger the correction process when the error exceeds a preset threshold.

[0107] In a preferred embodiment of the present invention, the multi-focus control strategy includes: dividing the array into multiple sub-arrays, each independently focusing on a different target point; forming different focal spots alternately over time; and dynamically adjusting the energy ratio of each focal spot based on treatment needs. Specific focal spot shapes can be generated, including linear focal spots (arranging multiple adjacent focal spots along a specified direction), planar focal spots (forming an array of evenly distributed focal spots within a plane), curved focal spots (arranging a sequence of focal spots along a specified curved path), and volume coverage (structured focal spot distribution within three dimensions).

[0108] like Figure 5 As shown, the non-thermal effect-guided pulse parameter intelligent optimization module 4 is in communication with the tissue acoustic properties real-time compensation and dynamic focus correction module 3, and is used to determine the non-thermal effect-guided pulse parameters based on the glandular state assessment results. This module includes a non-thermal effect mechanism modeling unit 41, a glandular state assessment unit 42, a parameter matching unit 43, a multi-objective parameter optimization unit 44, and a thermal effect monitoring unit 45.

[0109] The non-thermal effect mechanism modeling unit 41 is used to establish parameter relationship models for micromechanical stress effect, sonoporation effect, and acoustic microfluidic effect. In one embodiment of the present invention, the mechanism of action of the micromechanical stress effect is that ultrasound causes tissue microvibration, activating mechanically sensitive ion channels. The influencing factors include frequency, pulse duration, and sound pressure. The optimal parameter range is a frequency of 2-3MHz and a pulse width of 100-300μs. The expected effect is to promote the influx of Ca²⁺ into alveolar cells and activate secretory function. The mechanism of action of the sonoporation effect is that ultrasound forms recoverable tiny pores on the cell membrane. The influencing factors include sound intensity, duty cycle, and pulse repetition frequency. The optimal parameter range is a sound intensity of 50-100W / cm² and a duty cycle of 0.5-2%. The expected effect is to increase membrane permeability and promote the exchange of nutrients and signal molecules. The mechanism of action of the acoustic microfluidic effect is that ultrasound generates directional microflow in liquid. The influencing factors include frequency, sound intensity and pulse repetition frequency. The optimal parameter range is PRF20-50Hz and sound intensity 30-80W / cm². The expected effect is to enhance microcirculation, eliminate inflammatory factors and improve blood supply.

[0110] The glandular status assessment unit 42 is used to grade and assess the glandular inflammatory activity, degree of fibrosis, and degree of functional retention. In a preferred embodiment of the present invention, the glandular status assessment system includes inflammatory activity grading (Grade 0: no obvious inflammation; Grade I: mild inflammation, localized mild redness and swelling; Grade II: moderate inflammation, diffuse redness and swelling; Grade III: severe inflammation, significant redness and swelling, possibly accompanied by pain), fibrosis / atrophy grading (Grade 0: normal glandular structure; Grade I: mild atrophy, volume reduction less than 30%; Grade II: moderate atrophy, volume reduction 30-60%; Grade III: severe atrophy, volume reduction greater than 60%), and functional scoring (Grade 0: functional loss, basal secretion volume less than 10% of normal; Grade I: severe reduction, basal secretion volume 10-30%; Grade II: moderate reduction, basal secretion volume 30-60%; Grade III: mild reduction, basal secretion volume greater than 60%).

[0111] The parameter matching unit 43 is used to select an initial pulse parameter range according to the glandular status evaluation result, including frequency, sound intensity, pulse repetition frequency, pulse width and duty cycle. In one embodiment of the present invention, the parameter matching strategy sets different parameter ranges according to different glandular states: for glands with mild atrophy and high inflammatory activity, the frequency is 2.5-3.0 MHz, the sound intensity is 30-50 W / cm², the PRF is 20-30 Hz, the pulse width is 100-200 μs, and the duty cycle is 0.2-0.6%. The treatment focus is on inhibiting inflammation and protecting function; for glands with moderate atrophy and moderate inflammation, the frequency is 2.0-2.5 MHz, the sound intensity is 50-80 W / cm², the PRF is 30-40 Hz, the pulse width is 200-300 μs, and the duty cycle is 0.6-1.0%. The treatment focus is on balancing anti-inflammation and functional activation; for glands with severe atrophy and low inflammation, the frequency is 1.5-2.0 MHz, the sound intensity is 80-120 W / cm², the PRF is 40-50 Hz, the pulse width is 300-500 μs, and the duty cycle is 1.0-2.0%. The treatment focus is on maximizing functional activation.

[0112] The multi-objective parameter optimization unit 44 is used to maximize non-thermal effects while minimizing thermal effects, generating an optimal pulse parameter combination. In a preferred embodiment of the present invention, optimization objectives include maximizing non-thermal effects (mechanical stress, acoustic pores, and acoustic microfluidics), minimizing thermal effects (temperature rise), maximizing treatment depth coverage, minimizing treatment time, and maximizing patient comfort. The parameter optimization method includes initial parameter set generation (preselecting parameter ranges based on glandular status), parameter combination evaluation (simulating and calculating multi-objective scores for each combination), parameter tuning (optimizing towards maximizing non-thermal effects under temperature constraints), and generating the optimal parameter set (frequency, intensity, PRF, pulse width, duty cycle, and treatment time). Individualized adjustment strategies include patient feedback adjustment (fine-tuning parameters based on patient comfort feedback), real-time response adjustment (adjusting parameters based on immediate glandular function responses), and cumulative effect adjustment (adjusting subsequent parameters based on the cumulative dose during treatment).

[0113] The thermal effect monitoring unit 45 is used to predict and monitor temperature changes during treatment to ensure that safety thresholds are not exceeded. In one embodiment of the present invention, the heat accumulation prediction model uses tissue acoustic properties, ultrasound parameters, and treatment time as input parameters. It utilizes a multi-factor model that considers energy deposition, heat diffusion, and blood flow heat dissipation to generate predictions. The model outputs a three-dimensional temperature distribution prediction, the location of the highest temperature point, and critical structural temperatures. The real-time temperature monitoring scheme includes temperature estimation using changes in diagnostic ultrasound echo signals (active monitoring), detection of changes in acoustic emission signals (passive monitoring), and infrared thermal imaging and patient subjective feedback (auxiliary monitoring). The automatic adjustment mechanism sets temperature thresholds to less than 3°C in the core area and less than 1°C in the sensitive area. When the threshold is reached at 80%, an alert is issued and parameters are adjusted. Treatment is automatically paused if the safety threshold is exceeded and resumed after cooling. The PRF or duty cycle is dynamically adjusted based on temperature trends.

[0114] In a preferred embodiment of the present invention, the parameter ranges of the non-thermal effect-guided pulse parameter intelligent optimization module 4 are: frequency range 1.0-3.5 MHz; sound intensity range 30-120 W / cm²; pulse repetition frequency range 20-50 Hz; pulse width range 100-500 μs; duty cycle range 0.2-2.0%. Mild glandular atrophy uses a higher frequency, lower sound intensity, and lower duty cycle; severe glandular atrophy uses a lower frequency, higher sound intensity, and higher duty cycle.

[0115] like Figure 6 As shown, the closed-loop treatment control module 5 for glandular function response feedback is connected to the non-thermal effect-guided pulse parameter intelligent optimization module 4 and the tissue acoustic characteristics real-time compensation and dynamic focus correction module 3. It is used to monitor glandular function response data in real time and dynamically adjust pulse parameters and phase compensation values ​​based on glandular function response data. This module includes a glandular function monitoring unit 51, a response curve analysis unit 52, an individualized response model unit 53, a treatment strategy generation unit 54, and a parameter adjustment unit 55.

[0116] The gland function monitoring unit 51 is used to monitor the changes in saliva or tear secretion rate in real time using a micro-flow sensor. In one embodiment of the present invention, salivary gland secretion monitoring uses a micro-flow sensor placed at the duct opening to measure saliva flow. The sensor sensitivity is 0.01 ml / min, the response time is less than 5 seconds, data acquisition is continuous sampling, the sampling frequency is 2 Hz, and parameter calculations include basal secretion rate, post-stimulation secretion rate, and secretion duration. Lacrimal gland function monitoring combines optical coherence tomography technology to measure tear film thickness, infrared temperature measurement technology to evaluate tear evaporation rate, conductivity measurement-based monitoring of tear osmotic pressure, and automatic recording of blinking frequency through image recognition technology. Other related parameter monitoring includes monitoring local blood perfusion using Doppler blood flow imaging technology, monitoring local tissue oxygenation using near-infrared spectroscopy technology, monitoring temperature changes using infrared thermal imaging, and recording patients' subjective symptoms using an electronic visual analog rating scale.

[0117] The response curve analysis unit 52 is used to extract characteristic parameters such as baseline value, response latency, rise rate, peak response, and maintenance time from the monitoring data. In a preferred embodiment of the present invention, the response curve feature extraction includes baseline value (basal secretion rate before treatment), response latency (the time from the start of treatment to the start of secretion rate increase), rise rate (the speed of secretion rate increase), peak response (maximum secretion rate increase percentage), maintenance time (the duration that the secretion rate remains above 80% of the peak value), and recovery time (the time it takes to return from the peak value to the baseline).

[0118] The personalized response model unit 53 is used to establish a personalized glandular function response dynamics model based on response characteristics. In one embodiment of the present invention, personalized model parameterization includes initial response estimation based on historical data and patient characteristics, real-time data fitting using a sliding window to update model parameters, and prediction correction by comparing predicted values ​​with actual responses and adjusting model parameters. Response classification and typing categorizes patients into rapid response (short latency, rapid rise, short duration), slow persistent response (long latency, slow rise, long duration), mixed response (medium latency, rapid rise, medium duration), and low response (low response amplitude, no distinct peak).

[0119] The treatment strategy generation unit 54 is used to dynamically generate an optimal treatment strategy based on the individualized response model and pre-set treatment goals. In a preferred embodiment of the present invention, treatment goal adaptation adjusts the treatment plan based on the patient's response type: for rapid response, treatment frequency is reduced and single treatment duration is increased; for slow, persistent response, treatment frequency is increased while maintaining a moderate treatment duration; for mixed response, treatment frequency and duration are balanced; for slow response, sound intensity is increased, treatment duration is extended, and treatment intervals are shortened. Dynamic treatment plan generation includes real-time parameter adjustment within a single treatment (short-term adjustment), plan optimization within a treatment course (mid-term adjustment), and strategy adjustment across multiple treatment courses (long-term adjustment).

[0120] The parameter adjustment unit 55 is used to automatically adjust the pulse parameters and treatment time based on the response, achieving closed-loop control. In one embodiment of the present invention, the parameter adjustment rules include: if the response is insufficient, increase the sound intensity by 5-10 W / cm², increase the PRF by 5-10 Hz, and extend the treatment time by 20-30%; if the response is too strong, reduce the sound intensity by 5-10 W / cm², reduce the PRF by 5-10 Hz, and shorten the treatment time by 10-20%; if fatigue occurs, increase the rest interval, change the treatment area, and reduce the treatment frequency.

[0121] In a preferred embodiment of the present invention, the closed-loop treatment control module 5 for glandular function response feedback also includes an efficacy evaluation unit, a prognosis prediction unit, a treatment plan recording unit, a long-term follow-up management unit, and a knowledge base update unit. The efficacy evaluation unit is used to evaluate the treatment effect based on the objective secretion rate improvement percentage and the change in subjective symptom score. The prognosis prediction unit is used to predict the long-term duration of efficacy and the degree of functional recovery based on early response characteristics. The treatment plan recording unit is used to record complete treatment parameters, response data, and efficacy evaluation results. The long-term follow-up management unit is used to arrange follow-up plans and collect long-term efficacy data. The knowledge base update unit is used to continuously optimize the treatment strategy based on treatment data and follow-up results to form an empirical knowledge base.

[0122] like Figure 7 As shown, the multi-channel ultrasonic transducer driver module 6 is communicatively connected to the real-time tissue acoustic property compensation and dynamic focus correction module 3, the non-thermal effect-guided pulse parameter intelligent optimization module 4, and the glandular function response feedback closed-loop treatment control module 5. It is used to receive phase compensation values ​​and pulse parameters and control the phased array ultrasonic transducer to generate focused ultrasound waves. This module includes a phase control unit 61, a pulse control unit 62, a multi-channel signal generation unit 63, a power amplification unit 64, an impedance matching unit 65, and a safety monitoring unit 66.

[0123] The phase control unit 61 is used to receive the phase compensation value and control the phase delay of each array element. In one embodiment of the present invention, the phase control accuracy is 0-360°, the resolution is less than 1°, and precise phase control is achieved through a high-precision digital delay line.

[0124] The pulse control unit 62 receives pulse parameters and controls the frequency, intensity, pulse repetition frequency, pulse width, and duty cycle of the ultrasound. In a preferred embodiment of the present invention, the pulse control unit utilizes a high-precision timer to achieve precise control of a minimum pulse width of 50 μs, a maximum PRF of 100 Hz, and a duty cycle range of 0.1-10%.

[0125] The multi-channel signal generation unit 63 is used to generate the driving signal for each array element. In one embodiment of the present invention, digital signal synthesis (DDS) technology is used to generate high-precision waveforms, support complex pulse envelopes, and control clock jitter within 1ns.

[0126] The power amplifier unit 64 is used to amplify the driving signal. In a preferred embodiment of the present invention, a high-efficiency Class D amplifier is used, with a maximum output power of 2W per channel and a total power control within 500W.

[0127] The impedance matching unit 65 is used to perform electrical impedance matching to improve energy transmission efficiency. In one embodiment of the present invention, a dynamic impedance matching network is used to automatically adapt to different operating frequencies and load conditions to ensure maximum energy transmission efficiency.

[0128] The safety monitoring unit 66 is used to monitor the system's operating status in real time, ensuring that the system operates within safe parameters. In a preferred embodiment of the present invention, the safety monitoring unit monitors parameters such as current, voltage, and temperature of each channel in real time, and sets multiple safety thresholds. Once the safety range is exceeded, the protection mechanism is immediately triggered to ensure the safety of the equipment and patients.

[0129] like Figure 8 As shown, the workflow of the low-pulse ultrasound physiotherapy device for treating primary Sjögren's syndrome of the present invention mainly includes a pre-diagnosis preparation stage, a treatment planning stage, a treatment execution stage, and a follow-up and optimization stage.

[0130] During the pre-diagnosis preparation stage, the patient's basic information (age, gender, course of disease, etc.) is first entered, previous treatment history and medication status are collected, the symptom score related to Sjögren's syndrome (dry mouth, dry eyes, etc.) is recorded, and the baseline data of glandular function (basal secretion rate, secretion rate after stimulation) are collected; then high-resolution MRI images (T1, T2, enhanced scan), ultrasound images (B-ultrasound, Doppler) and optional CT images (to evaluate skeletal relationships) are obtained, and a preliminary quality check is performed on all images; finally, a pre-treatment evaluation is performed to analyze the degree of glandular atrophy and inflammatory activity, evaluate the local anatomical structure characteristics (facial nerve course, vascular distribution), estimate the difficulty and risk of treatment, and determine the initial treatment strategy (target gland, treatment sequence).

[0131] During the treatment planning stage, multimodal imaging data is first imported, image preprocessing (denoising, standardization, etc.) is performed, multimodal image registration is performed, and AI is started to automatically segment the gland and surrounding important structures. The doctor reviews and corrects the segmentation results to generate an accurate three-dimensional gland model; then the gland morphological characteristics are analyzed (skeletonization is used to extract branch structures), functional areas are marked according to the enhanced characteristics, the distribution of inflammatory activity is evaluated, treatment priority areas are marked, and sensitive areas that need to be avoided (facial nerve, blood vessels, etc.) are marked; then a preliminary scanning path is generated based on the gland morphology and functional area division, the path is optimized to balance coverage and treatment time, and the path is checked to see if it avoids sensitive areas. The treatment process is simulated, the energy distribution is estimated, and the doctor reviews and confirms the final treatment path; finally, the initial parameters (frequency, sound intensity, PRF, etc.) are automatically recommended based on the gland status, and individualized adjustments are made according to the patient's characteristics. Safety limits (maximum sound intensity, maximum temperature rise, etc.) are preset, treatment interruption conditions and emergency stop thresholds are set, and the treatment plan is saved to the system database.

[0132] During the treatment execution phase, the patient is positioned and secured, coupling agent is applied (to ensure good acoustic wave transmission), the treatment head is positioned and aligned, the glandular function monitoring device is installed, and a system self-test and parameter confirmation are performed. A low-energy probe pulse is then sent, the echo signal is analyzed, the focal position is confirmed, tissue acoustic property compensation values ​​are calculated, the phase compensation matrix is ​​adjusted, the focus is optimized, and calibration is repeated until the required accuracy (less than 0.3mm error) is achieved. Treatment then begins according to the planned pathway, with real-time monitoring of glandular function response (changes in secretion rate) and temperature changes in the treatment area. Focus position correction is performed every 50ms, and treatment parameters are dynamically adjusted based on the response. Parameters and response data throughout the entire process are recorded. The glandular function response curve is analyzed, individualized response model parameters are updated, the optimal treatment dose and time are predicted, parameters at subsequent treatment points are automatically adjusted, treatment progress and expected results are displayed, and possible adverse reactions are monitored and indicated. Finally, after the treatment pathway is fully covered or the preset response target is achieved, a post-treatment evaluation scan is performed, complete treatment parameters and response data are saved, a treatment report (coverage, energy distribution, response curve) is generated, and the data is uploaded to the patient's electronic medical record system.

[0133] During the follow-up and optimization stage, short-term follow-up evaluations are first conducted 24 hours, 72 hours, and 7 days after treatment to record symptom improvement, measure changes in glandular function, evaluate possible adverse reactions, and collect patients' subjective experience feedback; then, long-term effect tracking is carried out with monthly follow-up (for the first 3 months) and every 3 months thereafter, to comprehensively evaluate objective indicators and subjective feelings, record the duration of effects and decay patterns, and establish an individualized long-term response model; then, the previous treatment data and follow-up results are analyzed to identify the best response parameter combination, optimize the parameter settings for the next treatment, adjust the treatment frequency and interval, and update the individualized treatment strategy; finally, the treatment data of all patients are summarized, the parameter-effect relationship pattern is analyzed, the best treatment strategy for different types of patients is identified, the system algorithms and models are continuously improved, and a treatment experience knowledge base is formed.

[0134] The working principle and effects of the present invention are described below through a specific embodiment.

[0135] like Figure 9As shown, the phased array ultrasonic transducer system employed in this invention comprises a 128×128 array structure (16,384 elements), with element dimensions of 1.0×1.0 mm (side length). The array has a slightly concave shape (focal length 100 mm), and the total array dimensions are approximately 130×130 mm. The elements are made of PZT-5H piezoelectric ceramic, backed by a highly sound-absorbing polymer composite. A double-layer matching design optimizes energy transfer efficiency. The system operates in a frequency range of 1.0-3.5 MHz, with a maximum output power of 2 W per element and a total power controllable within 500 W. Regarding sound field characteristics, the focal spot size is frequency-dependent, approximately 1.0×1.0×3.0 mm at 2 MHz. The focal length is adjustable from 20 to 150 mm, with side lobe suppression greater than -20 dB, a steering angle range of ±30°, and a maximum sound intensity (spatial peak) of 150 W / cm².

[0136] In one patient treatment example, a 54-year-old woman, diagnosed with primary Sjögren's syndrome seven years prior, presented with severe dry mouth and dry eyes, with poor response to existing medications. MRI (T1, T2, and enhanced scans) and ultrasound images were first obtained. Multimodal medical image fusion and intelligent gland segmentation were then used to generate an accurate three-dimensional gland model. Glandular assessment revealed moderate atrophy of the parotid and submandibular glands (approximately 40% volume reduction) with moderate inflammatory activity, resulting in a functional score of Grade II (moderate reduction, with a basal secretion rate of approximately 45% of normal).

[0137] The gland-specific 3D scanning path planning module analyzes the gland's branching structure, identifying the main duct (approximately 1.7 mm in diameter) and multiple secondary branch ducts (0.9-1.2 mm in diameter). Functional area mapping reveals a high signal area (active inflammation) in the upper portion of the parotid gland and low perfusion (reduced function) in the lower portion. Based on this, the system categorizes glandular regions into different treatment priorities and automatically marks the facial nerve pathway as a protected area (maintaining a safe distance of at least 5 mm from the treatment area). The generated scanning path first covers the main duct, then the secondary branches, and finally the alveolar cluster area, achieving a total coverage rate of 97%. The estimated treatment time is 25 minutes per side.

[0138] Based on the glandular status assessment results, the non-thermal effect-guided pulse parameter intelligent optimization module recommends the following initial parameters: frequency 2.2MHz, intensity 60W / cm², PRF 35Hz, pulse width 250μs, and duty cycle 0.9%. The real-time tissue acoustic property compensation and dynamic focus correction module constructs a patient-specific acoustic model and calculates phase compensation values, achieving an initial focusing accuracy of 0.2mm.

[0139] After the treatment begins, the closed-loop treatment control module of glandular function response feedback monitors the changes in saliva secretion rate in real time. Figure 10As shown, the patient exhibited a typical "mixed" response profile: a response occurred approximately 30 seconds after treatment began (medium latency), followed by a rapid increase in secretion rate, peaking at 210% of baseline at 2 minutes, maintaining this peak for approximately 5 minutes before slowly declining. Based on this response profile, the system automatically adjusted parameters: after the peak response, the sound intensity was reduced to 50 W / cm², the PRF was increased to 40 Hz, and the duty cycle was adjusted to 0.8% to maintain a high secretion rate. Throughout the treatment, the acoustic field focal position was automatically corrected every 50 ms, with a maximum deviation within 0.3 mm, and the temperature rise in the treatment area did not exceed 2.5°C.

[0140] Immediately after the completion of unilateral parotid gland treatment, an increase of approximately 120% in saliva secretion rate was observed, and the patient's dry mouth symptom score (0-10 points, the higher the score, the more severe the symptoms) dropped from 8 points before treatment to 4 points. Follow-up one week later showed that the secretion rate remained at around 160% of the baseline, and the symptom score stabilized at 5 points. At the one-month follow-up, the secretion rate was 130% of the baseline, and the symptom score was 6 points. Based on the initial treatment response characteristics, the system recommends treatment every 2 weeks, with 6 consecutive times as a course of treatment. It is expected that after completing a course of treatment, the secretory function can be restored to 150-180% of the baseline and maintained for 3-4 months.

[0141] The above embodiments fully demonstrate that the present invention achieves effective treatment of the glands of patients with Sjögren's syndrome through innovative technologies such as precise targeting, non-thermal effect mechanism and closed-loop feedback control, and significantly improves the patients' secretory function and clinical symptoms.

[0142] Those skilled in the art should understand that the present invention is not limited to the specific embodiments described above. Various modifications and improvements can be made without departing from the basic concept of the present invention, and these modifications and improvements should also be considered within the scope of protection of the present invention.

Claims

1. A low-pulse ultrasound physiotherapy device for treating primary Sjögren's syndrome, characterized in that: include: Multimodal medical image fusion and gland intelligent segmentation module, which is used to obtain multimodal medical image data of the patient's glands, perform image registration and automatic gland segmentation, and generate a three-dimensional gland model; a gland-specific 3D scanning path planning module, communicatively connected to the multimodal medical image fusion and gland intelligent segmentation module, configured to receive the 3D gland model, analyze the gland morphological characteristics and functional area distribution based on the 3D gland model, and generate a gland-specific 3D scanning path; a tissue acoustic characteristics real-time compensation and dynamic focus correction module, which is in communication with the gland-specific three-dimensional scanning path planning module and is used to receive the gland-specific three-dimensional scanning path, construct a tissue acoustic model, calculate a phase compensation value, and achieve precise focusing; a non-thermal effect guided pulse parameter intelligent optimization module, in communication with the tissue acoustic characteristics real-time compensation and dynamic focus correction module, for determining the non-thermal effect guided pulse parameters based on the glandular status assessment results; a glandular function response feedback closed-loop treatment control module, which is in communication with the non-thermal effect-guided pulse parameter intelligent optimization module and the tissue acoustic characteristics real-time compensation and dynamic focus correction module, and is used to monitor glandular function response data in real time and dynamically adjust the pulse parameters and the phase compensation value based on the glandular function response data; The multi-channel ultrasonic transducer driving module is communicatively connected to the real-time compensation and dynamic focusing correction module for tissue acoustic characteristics, the non-thermal effect-guided pulse parameter intelligent optimization module, and the closed-loop treatment control module for glandular function response feedback, and is used to receive the phase compensation value and the pulse parameters and control the phased array ultrasonic transducer to generate focused ultrasonic waves.

2. The low-pulse ultrasonic therapy device according to claim 1, characterized in that: The multimodal medical image fusion and gland intelligent segmentation module includes: An image preprocessing unit, configured to perform denoising, grayscale normalization, and contrast enhancement on the multimodal medical image data; A multimodal image registration unit, which is used to perform coarse registration using a rigid transformation based on anatomical landmark matching and fine registration using a non-rigid registration based on mutual information, aligning images of different modalities to a unified coordinate system; The gland intelligent segmentation unit is used to automatically segment the glands in the registered medical images using a deep learning network to identify the main gland structure, internal duct system, and surrounding important anatomical structures; Interactive segmentation correction unit, which provides doctors with an interactive interface and supports manual review and correction of automatic segmentation results; The three-dimensional model reconstruction unit is used to generate a three-dimensional gland model based on the segmentation results and mark the degree of inflammation, degree of fibrosis and functional area attributes.

3. The low-pulse ultrasonic therapy device according to claim 1, characterized in that: The gland-specific three-dimensional scanning path planning module includes: a gland morphology analysis unit, configured to perform skeletonization processing on the three-dimensional gland model, extract the gland branch structure, and perform hierarchical division; Functional area mapping unit, used to identify different functional areas based on enhanced MRI signal characteristics, evaluate inflammatory activity and functional preservation, and generate functional area labeling data; A treatment prioritization unit is used to assign treatment priorities to different areas based on inflammatory activity and functional preservation, and to mark sensitive protection areas; A scanning path generating unit, configured to select an adaptive scanning mode for glandular structures at different levels and generate a three-dimensional scanning path; The path optimization and verification unit is used to optimize the generated scanning path to ensure the balance between coverage, treatment time and safety, and perform path feasibility verification.

4. The low-pulse ultrasonic therapy device according to claim 1, characterized in that: The tissue acoustic characteristics real-time compensation and dynamic focus correction module includes: A tissue acoustic model construction unit is used to construct a multi-level tissue acoustic model based on the segmentation results and assign sound velocity, attenuation coefficient and density parameters to different tissues; An acoustic wave propagation analysis unit, used to analyze the acoustic wave propagation path from each array element to the target focus using a ray tracing method and calculate the cumulative delay; A phase compensation calculation unit is used to calculate the phase compensation value of each array element according to the sound wave propagation analysis result and generate a phase compensation matrix; A real-time focus monitoring unit, which is used to send low-energy detection pulses at predetermined intervals, analyze the echo signals, and evaluate the focus position accuracy; The dynamic correction unit is used to update the phase compensation matrix based on the real-time focus monitoring results to achieve dynamic correction of the focus position.

5. The low-pulse ultrasonic therapy device according to claim 1, characterized in that: The non-thermal effect-guided pulse parameter intelligent optimization module includes: Non-thermal effect mechanism modeling unit, used to establish parameter relationship models of micromechanical stress effect, acoustic pore effect and acoustic microfluidic effect; Glandular status assessment unit, used to grade and evaluate glandular inflammatory activity, degree of fibrosis, and degree of functional preservation; a parameter matching unit for selecting an initial pulse parameter range, including frequency, sound intensity, pulse repetition frequency, pulse width, and duty cycle, based on the glandular status assessment result; A multi-objective parameter optimization unit is used to maximize non-thermal effects while minimizing thermal effects to generate the optimal pulse parameter combination; Thermal effect monitoring unit, used to predict and monitor temperature changes during treatment to ensure that safety thresholds are not exceeded.

6. The low-pulse ultrasonic therapy device according to claim 1, characterized in that: The closed-loop treatment control module for glandular function response feedback includes: Glandular function monitoring unit, used to monitor changes in saliva or tear secretion rate in real time using a micro-flow sensor; Response curve analysis unit, used to extract characteristic parameters such as baseline value, response latency, rise rate, peak response and maintenance time from monitoring data; Individualized response model unit, used to establish an individualized glandular function response dynamics model based on response characteristics; A treatment strategy generation unit, which is used to dynamically generate the optimal treatment strategy based on the individualized response model and preset treatment goals; The parameter adjustment unit is used to automatically adjust the pulse parameters and treatment time according to the response situation to achieve closed-loop control.

7. The low-pulse ultrasonic therapy device according to claim 1, characterized in that: The multi-channel ultrasonic transducer driving module includes: A phase control unit, configured to receive the phase compensation value and control the phase delay of each array element; A pulse control unit, configured to receive the pulse parameters and control the frequency, intensity, pulse repetition frequency, pulse width and duty cycle of the ultrasonic wave; A multi-channel signal generation unit, used to generate a driving signal for each array element; A power amplifying unit, used for amplifying the power of the driving signal; Impedance matching unit, used to perform electrical impedance matching to improve energy transmission efficiency; The safety monitoring unit is used to monitor the system operation status in real time to ensure that the system operates within the safety parameter range.

8. The low-pulse ultrasonic therapy device according to claim 1, characterized in that: The tissue acoustic characteristics real-time compensation and dynamic focus correction module is further used for: Controlling the phased array ultrasonic transducer to form a multi-focal point or a focal spot of a specific shape, including a linear focal spot, a planar focal spot, a curved focal spot, or a volume-covered focal spot; Adjust focus depth, focus position and focus size in real time; Compensate for the refraction and reflection effects of sound waves at different tissue interfaces; The focus position error is calculated in real time, and the correction process is triggered when the error exceeds a preset threshold.

9. The low-pulse ultrasonic therapy device according to claim 5, characterized in that: The parameter range of the non-thermal effect-guided pulse parameter intelligent optimization module is: Frequency range: 1.0-3.5MHz; Sound intensity range: 30-120W / cm²; Pulse repetition frequency range: 20-50Hz; Pulse width range: 100-500μs; Duty cycle range: 0.2-2.0%; Among them, higher frequency, lower sound intensity and lower duty cycle are used for mildly atrophic glands; lower frequency, higher sound intensity and higher duty cycle are used for severely atrophic glands.

10. The low-pulse ultrasonic therapy device according to claim 6, characterized in that: The closed-loop treatment control module for glandular function response feedback also includes: Efficacy evaluation unit, used to evaluate treatment efficacy based on the objective secretion rate improvement percentage and changes in subjective symptom scores; Prognostic prediction unit, used to predict the long-term efficacy maintenance time and functional recovery degree based on early response characteristics; Treatment plan recording unit, used to record complete treatment parameters, response data and efficacy evaluation results; Long-term follow-up management unit, used to arrange follow-up plans and collect long-term efficacy data; The knowledge base updating unit is used to continuously optimize treatment strategies based on treatment data and follow-up results to form an experience knowledge base.

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