Local anesthesia dosage control system based on CFD and PC-MRI coupling and working method thereof

Abstract

The invention relates to a local anesthesia dosage control system based on CFD (Computational Fluid Dynamics) and PC-MRI (Personal Computer-Magnetic Resonance Imaging) coupling and a working method thereof, and the system comprises an information collection unit which is used for collecting physical examination and medical evaluation information of a patient; the geometric unit is used for acquiring a T2 weighted MRI image sequence; the calculation model unit is used for determining the range of a lumbar, thoracic and vertebral segment calculation domain; a measurement unit for phase encoding using PC-MRI; the cerebrospinal fluid dynamic unit is used for acquiring an initial flow field of cerebrospinal fluid flow of the spinal canal of the patient; the dosage selection unit is used for selecting the injection dosage of the local anesthetic; the intrathecal administration calculation unit is used for establishing coupling analysis to obtain a local anesthetic concentration value of a blocking plane; and the dose evaluation unit is used for quantitatively evaluating the concentration value of the local anesthetic. The system is beneficial for improving the accuracy and safety of local anesthesia medication.

Description

Technical Field

[0001] This invention relates to the field of local anesthetic dosage assessment and control technology, specifically to a local anesthetic dosage control system based on CFD and PC-MRI coupling and its working method. Background Technology

[0002] In recent years, with the increasing aging of the population and the popularization of painless childbirth techniques, the application of spinal anesthesia has been growing. However, accurately selecting the anesthetic dosage is crucial to ensuring the effectiveness and safety of anesthesia. Excessive local anesthetic may lead to respiratory and circulatory depression in patients, seriously threatening their lives; while insufficient dosage may result in inadequate anesthesia of the surgical area, increasing surgical risks and causing discomfort and pain to patients.

[0003] Currently, the implementation of spinal anesthesia relies primarily on the physician's experience and judgment, lacking effective means to dynamically monitor the distribution of intrathecal local anesthetics. This limits the precise control of the anesthetic dosage. Without real-time monitoring capabilities, physicians struggle to avoid excessive diffusion of the local anesthetic or failure to provide sufficient blockage, thus increasing the risk of complications.

[0004] The application of computational fluid dynamics (CFD) technology, particularly in drug motion analysis, offers a new solution to this problem. CFD analysis allows for the quantitative analysis of drug transport in cerebrospinal fluid, helping anesthesiologists more precisely adjust the dosage of injected drugs during spinal anesthesia and avoid excessive or insufficient drug diffusion. This method can provide effective sensory blockade in the shortest possible time, significantly reducing the risk of complications. Traditional CFD spinal canal simulation faces limitations such as unclear cerebrospinal fluid boundary conditions, difficulties in model building, and the inability to accurately simulate real human structures. Furthermore, clinical variability and individual specificity make determining the correlation between drug dosage and sensory blockade in spinal anesthesia even more challenging. Summary of the Invention

[0005] The purpose of this invention is to provide a local anesthetic dosage control system based on CFD and PC-MRI coupling and its working method, which is beneficial to improving the accuracy and safety of local anesthetic administration.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is: a local anesthetic dosage control system based on CFD and PC-MRI coupling, comprising:

[0007] The information collection unit is used to collect patient physical examination and medical assessment information;

[0008] Geometric units are used to acquire T2-weighted MRI image sequences;

[0009] The computational model unit is used to determine the range of the computational domain for the lumbar and thoracic vertebral segments.

[0010] Measurement unit for phase encoding using PC-MRI;

[0011] The cerebrospinal fluid dynamics unit is used to obtain the initial flow field of cerebrospinal fluid flow in the patient's spinal canal.

[0012] Dosage selection unit, used to select the injection dose of local anesthetic;

[0013] An intrathecal drug delivery calculation unit is used to establish a coupled analysis to obtain the local anesthetic concentration value at the blockade plane; and

[0014] Dosage assessment unit, used to quantitatively assess the concentration of local anesthetic drugs.

[0015] The present invention also provides a method for operating the above-mentioned local anesthetic dosage control system based on CFD and PC-MRI coupling, comprising the following steps:

[0016] S1. Collect patient physical examination and medical assessment information through the information collection unit;

[0017] S2. T2-weighted MRI image sequences are obtained through geometric units, the patient's MRI images are analyzed, and the spinal canal geometry is reconstructed by segmenting the images;

[0018] S3. In the calculation model unit, the range of the calculation domain of the lumbar and thoracic vertebrae is determined according to the position of each vertebra on the patient's spine.

[0019] S4. In the measurement unit, 4D PC-MRI is used to measure the cerebrospinal fluid flow data at the axial position of the patient's spinal canal;

[0020] S5. In the cerebrospinal fluid dynamics unit, a CFD calculation model of the patient's intrathecal space is established using Fluent software to perform cerebrospinal fluid flow analysis during each cardiac cycle and obtain the initial cerebrospinal fluid flow field of the patient's spinal canal.

[0021] S6. In the dosage selection unit, select the initial local anesthetic dosage for injection;

[0022] S7. In the intrathecal drug delivery calculation unit, import the three-dimensional model of the spinal canal and establish a coupling analysis: In the calculation model of intrathecal injection and delivery of local anesthetics in the patient, the selected initial injection volume of local anesthetics is used as the drug inlet boundary condition. In the preoperative cerebrospinal fluid pulsation flow analysis model of the patient's spinal canal, the peak cerebrospinal fluid flow rate at the axial position measured by 4D PC-MRI is used as the cerebrospinal fluid inlet boundary condition and the cerebrospinal fluid flow field under normal physiological conditions is used as the initial condition.

[0023] S8. In the dosage assessment unit, the concentration value of the local anesthetic is quantitatively assessed based on the calculation results of step S7.

[0024] Furthermore, step S1 specifically includes the following steps:

[0025] S11. Collect information on the patient's physical examination and medical assessment, including information on age, weight, body type, medical history and current health status;

[0026] S12. Organize, analyze, and classify the patients' surgical categories, and extract characteristic information;

[0027] S13. Collect previous clinical cases of spinal anesthesia, including drug delivery in different clinical surgeries, the range of drug dosage and the time of onset of the blocking response;

[0028] S14. Input the data information obtained in steps S11-S13 into the information acquisition unit.

[0029] Furthermore, step S2 specifically includes the following steps:

[0030] S21. In the geometric unit, a standard 16-channel coil 3T scanner is used to acquire multiple sagittal high-resolution T2-weighted MRI images of a supine patient in a free-breathing state from T6 to S1; the field of view size is adjusted according to the anatomical dimensions of the chest, lumbar, and sacral regions of different patients.

[0031] S22. Use the segmentation tool to segment the MRI images of the chest and waist along the axis, segmenting the T6-S1 region; exclude high signal regions near the epidural space in the MRI images; after segmentation, export each segmentation result as a .STL file.

[0032] S23. Transfer the segmentation results into Blender software for rigid body translation to align the sliced ​​models, create a surface profile mesh of the original geometry, and improve the geometric accuracy of the surface mesh through offset and smoothing.

[0033] Furthermore, step S3 specifically includes the following steps:

[0034] S31. In the computational model unit, based on the position of each vertebra on the spine in the midsagittal MR image of the patient, determine the characteristics of spinal canal scoliosis in the T6-S1 part of the lumbar and thoracic spine and the range of the computational domain.

[0035] S32. Process the surface mesh through reverse engineering, fill the vertebral canal computational domain, and establish each vertebral plane according to the vertebral body position.

[0036] Furthermore, step S4 specifically includes the following steps:

[0037] S41. In the measurement unit, a 3T MRI scanner is used to perform 4D PC-MRI measurements on the patient; the patient lies supine on a scanning bed with a standard 16-channel head and neck coil.

[0038] S42. The flow velocity coding direction is performed in front-back, foot-head and left-right. The 4D PC flow sequence of each patient is aligned in the sagittal plane, and the 3D stack covers the entire lumbar and thoracic vertebral segment.

[0039] S43. Quantify the cerebrospinal fluid flow at six axial positions of the lumbar and thoracic vertebrae during a cardiac cycle, and select the axial position with the largest flow peak as the inlet boundary condition for the CFD simulation of cerebrospinal fluid flow.

[0040] Furthermore, step S5 specifically includes the following steps:

[0041] S51. In the cerebrospinal fluid dynamics unit, import the patient's intrathecal space model, and perform mesh discretization on the computational domain in Fluent Meshing software. Generate a CFD computational model with appropriate density by adjusting the local and global mesh sizes.

[0042] S52. Create a new patient-specific intrathecal space CFD calculation project in Fluent software, set the Fluent calculation kernel to 3d, enable double precision, set the viscosity model to laminar flow, and enable the transient simulation option.

[0043] S53. Set the arachnoid wall type, the inlet and outlet boundary conditions for cerebrospinal fluid flow, and determine the simulation time step based on the cerebrospinal fluid flow change pattern during the patient's diastolic and systolic phases.

[0044] S54. Conduct Fluent calculations, post-process the calculation results, and provide the initial flow field of cerebrospinal fluid flow in the spinal canal during one cardiac cycle.

[0045] Furthermore, step S6 specifically includes the following steps:

[0046] S61. In the dosage selection unit, select the type and concentration of local anesthetic according to the actual clinical surgery.

[0047] S62. Select the initial local anesthetic dose and injection duration.

[0048] Furthermore, step S7 specifically includes the following steps:

[0049] S71. In the intrathecal drug delivery calculation unit, import the three-dimensional model of the spinal canal, select the puncture plane, create the geometric features of the needle tube, determine the size of the calculation domain based on the thoracic and lumbar region of the MRI image, and perform meshing on the calculation domain.

[0050] S72. Create a new patient-specific intrathecal injection and delivery calculation project for local anesthetics in Fluent software. Set the Fluent calculation kernel to 3d, enable double precision, set the viscosity model to laminar flow, the flow model to Mixture multiphase, the phase volume fraction format type to Implicit, the phase interface modeling to Dispersed mode, and enable the SlipVelocity option.

[0051] S73. In the calculation model of intrathecal injection and delivery of local anesthetics for individual patients, the initial injection volume and average injection time of the selected local anesthetics are used as the drug inlet boundary conditions. In the preoperative cerebrospinal fluid pulsation flow analysis model of the spinal canal of patients, the peak cerebrospinal fluid flow rate at the axial position measured by 4D PC-MRI is used as the cerebrospinal fluid inlet boundary condition and the cerebrospinal fluid flow field under normal physiological conditions is used as the initial condition.

[0052] S74. Perform calculations on the intrathecal injection and delivery of local anesthetics for individual patients to obtain the concentration values ​​of local anesthetics at the blockade plane.

[0053] Furthermore, step S8 specifically includes the following steps:

[0054] S81. In the dosage assessment unit, the concentration value of the local anesthetic at the target blocking plane in the calculation result of step S7 is assessed. When the target blocking plane reaches the effective drug concentration, step S82 is performed. If the judgment criteria are not met, the dosage is increased or decreased and then the process returns to step S6 to re-enter the dosage.

[0055] S82. Determine the total simulated injection volume and record the total onset time of the drug.

[0056] S83. Collect clinical usage feedback, further optimize and adjust the local anesthetic dosage model, and then construct a patient-based local anesthetic dosage plan.

[0057] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a local anesthetic dosage control system based on CFD and PC-MRI coupling and its working method. The present invention integrates CFD and MRI sequences into one system, which can take into account the individual differences of patients and the needs of patients requiring emergency analgesia for drug onset time, realize continuous optimization and adjustment of the medication process simulation, thereby improving the accuracy and safety of local anesthetic medication, and providing patients with a safer and more effective spinal anesthesia surgery plan. Attached Figure Description

[0058] Figure 1 This is a block diagram illustrating the implementation principle of the local anesthetic dosage control system based on CFD and PC-MRI coupling according to an embodiment of the present invention.

[0059] Figure 2 This is a flowchart illustrating the implementation of the local anesthetic dosage control system based on CFD and PC-MRI coupling according to an embodiment of the present invention.

[0060] Figure 3 This is a flowchart illustrating the implementation of medication dosage control during spinal anesthesia for a lower limb surgical patient in an embodiment of the present invention.

[0061] Figure 4 It is the cerebrospinal fluid velocity function during one cardiac cycle of a lower limb surgery patient in an embodiment of the present invention. Detailed Implementation

[0062] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0063] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0064] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0065] like Figure 1 As shown, this embodiment provides a local anesthetic dosage control system based on CFD and PC-MRI coupling, including: an information acquisition unit, a geometric unit, a calculation model unit, a measurement unit, a cerebrospinal fluid dynamics unit, a dosage selection unit, an intrathecal drug delivery calculation unit, and a dosage assessment unit.

[0066] The information collection unit is used to collect patient physical examination and medical assessment information.

[0067] The geometric unit is used to acquire T2-weighted MRI image sequences.

[0068] The computational model unit is used to determine the range of the computational domain for the lumbar and thoracic vertebrae.

[0069] The measurement unit is used for phase encoding using PC-MRI.

[0070] The cerebrospinal fluid dynamics unit is used to obtain the initial flow field of cerebrospinal fluid flow in the patient's spinal canal.

[0071] The dosage selection unit is used to select the local anesthetic injection dosage.

[0072] The intrathecal drug delivery calculation unit is used to establish a coupling analysis to obtain the local anesthetic concentration value of the blocking plane.

[0073] The dosage assessment unit is used to quantitatively assess the concentration of local anesthetic drugs.

[0074] like Figure 2 As shown, this embodiment also provides a method for operating the above-mentioned local anesthetic dosage control system based on CFD and PC-MRI coupling, including the following steps:

[0075] S1. Collect patient physical examination and medical assessment information through the information collection unit.

[0076] In this embodiment, step S1 specifically includes the following steps:

[0077] S11. Conduct a physical examination and medical assessment of the patient, and collect relevant information including age, weight, body type, medical history and current health status, anonymously examining the information.

[0078] S12. Organize, analyze, and classify the patient's surgical categories (such as lower limb, bladder and urinary system, cesarean section, etc.) and extract characteristic information.

[0079] S13. Collect clinical cases of spinal anesthesia from previous procedures, analyze drug delivery in different clinical surgeries, and record the range of drug dosage and the time of onset of the blocking response.

[0080] S14. Input the data information obtained in steps S11-S13 into the information acquisition unit.

[0081] S2. T2-weighted MRI image sequences are obtained through geometric units, the patient's MRI images are analyzed, and the spinal canal geometry is reconstructed by segmenting the images.

[0082] In this embodiment, step S2 specifically includes the following steps:

[0083] S21. In the geometric unit, multiple sagittal high-resolution T2-weighted MRI images of the T6-S1 region were acquired from a supine patient in a free-breathing state using a standard 16-channel coil 3T scanner. The field of view size was adjusted according to the anatomical dimensions of the thoracic, lumbar, and sacral regions of different patients. The planar voxel resolution was approximately 0.5mm × 0.5mm, the slice thickness was 1mm, the slice spacing was set to 0.5mm, the echo time and repetition time were ~2ms and ~5ms, respectively, and the total imaging time was within half an hour.

[0084] S22. Use the segmentation tool to segment the MRI images of the chest and waist along the axial direction, segmenting the region from T6 to S1. Exclude high-signal areas near the epidural space in the MRI images. After segmentation, export each segmentation result as a .STL file.

[0085] S23. Transfer the segmentation results into Blender software for rigid body translation to align the sliced ​​models, create a surface profile mesh of the original geometry, and improve the geometric accuracy of the surface mesh through offset and smoothing.

[0086] S3. In the calculation model unit, the range of the calculation domain for the lumbar and thoracic vertebrae is determined according to the position of each vertebra on the patient's spine.

[0087] In this embodiment, step S3 specifically includes the following steps:

[0088] S31. In the computational model unit, based on the position of each vertebra on the spine in the midsagittal MR image of the patient, determine the characteristics of the spinal canal scoliosis in the T6-S1 region of the lumbar and thoracic spine and the range of the computational domain.

[0089] S32. Process the surface mesh through reverse engineering, fill the vertebral canal computational domain, and establish each vertebral plane according to the vertebral body position.

[0090] S4. In the measurement unit, 4D PC-MRI is used to measure the cerebrospinal fluid flow data at the axial position of the patient's spinal canal.

[0091] In this embodiment, step S4 specifically includes the following steps:

[0092] S41. In the measurement unit, a 3T MRI scanner is used to perform 4D PC-MRI measurements on the patient. The patient lies supine on a scanning bed with a standard 16-channel head and neck coil, and the scan time is approximately 10 minutes (depending on each patient's heart rate and velocity-encoded gradient flow factor).

[0093] S42. The flow velocity coding direction is performed in front-back, foot-head and left-right directions. The 4D PC flow sequence of each patient is aligned in the sagittal plane, and the 3D stack covers the entire lumbar and thoracic vertebral segment.

[0094] S43. Quantify the cerebrospinal fluid flow at six axial positions of the lumbar and thoracic vertebrae during a cardiac cycle, and select the axial position with the largest flow peak as the inlet boundary condition for the CFD simulation of cerebrospinal fluid flow.

[0095] S5. In the cerebrospinal fluid dynamics unit, a CFD calculation model of the patient's intrathecal space is established using Fluent software to perform cerebrospinal fluid flow analysis during each cardiac cycle and obtain the initial cerebrospinal fluid flow field of the patient's spinal canal.

[0096] In this embodiment, step S5 specifically includes the following steps:

[0097] S51. In the cerebrospinal fluid dynamics unit, import the patient's intrathecal space model, and perform mesh discretization on the computational domain in Fluent Meshing software. Generate a CFD computational model with appropriate density by adjusting the local and global mesh sizes.

[0098] S52. Create a new patient-specific intrathecal CFD calculation project in Fluent software, set the Fluent calculation kernel to 3d, enable double precision, set the viscosity model to laminar flow, and enable the transient simulation option.

[0099] S53. Set the arachnoid wall type, the inlet and outlet boundary conditions for cerebrospinal fluid flow, and determine the simulation time step based on the changes in cerebrospinal fluid flow during the patient's diastolic and systolic phases.

[0100] S54. Conduct Fluent calculations, post-process the calculation results, and provide the initial flow field of cerebrospinal fluid flow in the spinal canal during one cardiac cycle.

[0101] S6. In the dosage selection unit, select the initial local anesthetic dosage for injection.

[0102] In this embodiment, step S6 specifically includes the following steps:

[0103] S61. In the dosage selection unit, select the type and concentration of local anesthetic according to the actual clinical surgery, such as 0.5% or 0.75% ropivacaine.

[0104] S62. Based on factors such as the patient's height, age, weight, operation duration, analgesia level, puncture level, and needle insertion method, select the initial local anesthetic dosage and injection duration.

[0105] S7. In the intrathecal drug delivery calculation unit, import the three-dimensional model of the spinal canal and establish a coupling analysis: In the calculation model of intrathecal injection and delivery of local anesthetics in the patient, the selected initial injection volume of local anesthetic is used as the drug inlet boundary condition. In the preoperative cerebrospinal fluid pulsation flow analysis model of the patient's spinal canal, the peak cerebrospinal fluid flow rate at the axial position measured by 4D PC-MRI is used as the cerebrospinal fluid inlet boundary condition, and the cerebrospinal fluid flow field under normal physiological conditions is used as the initial condition.

[0106] In this embodiment, step S7 specifically includes the following steps:

[0107] S71. In the intrathecal drug delivery calculation unit, import the three-dimensional model of the spinal canal, select the puncture plane, create the geometric features of the needle tube, determine the size of the calculation domain based on the thoracic and lumbar region of the MRI image, and perform meshing on the calculation domain.

[0108] S72. In Fluent software, create a new patient-specific intrathecal injection and delivery calculation project for local anesthetics. Set the Fluent calculation kernel to 3d, enable double precision, set the viscosity model to laminar flow, the flow model to Mixture multiphase, the phase volume fraction format type to Implicit, the phase interface modeling to Dispersed mode, and enable the SlipVelocity option.

[0109] S73. In the calculation model of intrathecal injection and delivery of local anesthetics for individual patients, the initial injection volume and average injection duration of the selected local anesthetic are used as the drug inlet boundary conditions. In the preoperative cerebrospinal fluid pulsation flow analysis model of the spinal canal of patients, the peak cerebrospinal fluid flow rate at the axial position measured by 4D PC-MRI is used as the cerebrospinal fluid inlet boundary condition, and the cerebrospinal fluid flow field under normal physiological conditions is used as the initial condition.

[0110] S74. Perform calculations on the intrathecal injection and delivery of local anesthetics for individual patients to obtain the concentration values ​​of local anesthetics at the blockade plane.

[0111] S8. In the dosage assessment unit, the concentration value of the local anesthetic is quantitatively assessed based on the calculation results of step S7.

[0112] In this embodiment, step S8 specifically includes the following steps:

[0113] S81. In the dosage assessment unit, the concentration value of the local anesthetic at the target blocking plane in the calculation result of step S7 is assessed. When the target blocking plane reaches the effective drug concentration, step S82 is performed. If the judgment standard is not met, the dosage is increased or decreased and then the process returns to step S6 to re-enter the dosage.

[0114] S82. Determine the total simulated injection dosage and record the total onset time of the drug.

[0115] S83. Collect clinical usage feedback, further optimize and adjust the local anesthetic dosage model, and then construct a patient-based local anesthetic dosage plan.

[0116] The following example, using a lower limb surgery patient undergoing spinal anesthesia at a certain hospital, further details the implementation process of this system. Figure 3 As shown, the working method of the local anesthetic dosage control system based on CFD and PC-MRI coupling, that is, the implementation process of controlling the dosage of medication during spinal anesthesia for this patient using this system, includes the following steps:

[0117] S1. In the information collection unit, collect physical examination and medical assessment information of patients undergoing spinal anesthesia, specifically including the following sub-implementation steps:

[0118] S11. The patient submitted a written informed consent form and was found to have no allergies to local anesthetics or non-steroidal anti-inflammatory drugs, no infection near the puncture site, no known coagulation disorders, no specific cardiovascular disease, no chronic pain, and no use of pain medication.

[0119] S12. Organize, analyze and classify the examination and evaluation information of the lower limb surgery patient, and extract characteristic information, including the patient's height of 171mm, age of 59 years, weight of 124kg, normal operation time expected to be within 20 minutes, analgesia level set at T10, puncture plane at L4-5 intervertebral foramen space, and needle insertion perpendicular to the coronal plane.

[0120] S13. Collect previous clinical cases of spinal anesthesia, analyze the drug delivery situation in lower limb clinical surgery, and record the drug dosage range as 3-5ml and the onset of the blocking reaction within 15-20 minutes.

[0121] S2. Within the geometric unit, acquire T2-weighted MRI image sequences, analyze the patient's MRI images, and reconstruct the spinal canal geometry by segmenting the images. This includes the following sub-implementation steps:

[0122] S21. With the patient in a supine position and breathing freely, 100 sagittal high-resolution T2-weighted MRI images of the T6-S1 region were acquired using a standard 16-channel coil 3T scanner. The field of view was 30cm × 30cm × 3.4cm (thoracic, lumbar, and sacral regions), the planar voxel resolution was approximately 0.5mm × 0.5mm, the slice thickness was 1mm, the slice spacing was 0.5mm, the echo time and repetition time were 2.1ms and 5.5ms, respectively, and the total imaging time was within half an hour.

[0123] S22. The MRI image sets of the chest and waist are manually segmented using a semi-automatic contrast-based segmentation tool in the axial direction, and the segmentation region is T6-S1. The model segmentation excludes the high signal region close to the epidural space in the T2-weighted image set. After the segmentation is completed, each segmentation result is exported in .STL file format and Gaussian smoothing option is applied (standard deviation = 0.80, maximum approximation error = 0.03).

[0124] S23. During the acquisition of MR images, there is relative movement between different image sequences. Rigid body translation is performed in Blender software to align the sliced ​​models. The uneven vertex positions are manually adjusted to create a surface profile mesh with the original geometry. The geometric accuracy of the surface mesh is improved by offset and smoothing. The values ​​of the offset and smoothing coefficients are 0.05 and 0.90, respectively.

[0125] S3. In the calculation model unit, the range of the calculation domain for the lumbar and thoracic vertebrae is determined based on the position of each vertebra on the patient's spine. This includes the following sub-implementation steps:

[0126] S31. Based on the position of each vertebra in the spine in the midsagittal MRI image of the patient, determine the characteristics of spinal canal scoliosis in the T6-S1 part of the lumbar and thoracic spine and the range of the calculation domain.

[0127] S32. In SpaceClaim software, the surface mesh is processed by reverse engineering to fill the vertebral canal computational domain, and the planes of each vertebra are established according to the vertebral body position.

[0128] S4. Measure the cerebrospinal fluid flow data in the axial position of the spinal canal using 4D PC-MRI, specifically including the following sub-implementation steps:

[0129] S41. A 3T MRI scanner is used to perform 4D PC-MRI measurements on the patient. The patient will lie supine on a scanning bed with a standard 16-channel head and neck coil. The scanning time is about 10 minutes.

[0130] S42. The flow velocity coding direction is performed in front-back, foot-head and left-right. The 4D PC flow sequence of each patient is aligned in the sagittal plane, and the 3D stack covers the entire lumbar and thoracic vertebral segment.

[0131] S43. Quantify the cerebrospinal fluid (CSF) flow at six axial positions of the lumbar and thoracic vertebrae during one cardiac cycle. Select the axial position with the largest flow peak as the inlet boundary condition for the CFD simulation of CSF flow. Convert the cross-sectional area at the peak position into a velocity function and fit it into a six-term Fourier series form, such as... Figure 4 As shown.

[0132] S5. In the cerebrospinal fluid dynamics unit, a CFD calculation model of the patient's intrathecal space is established using Fluent software. Cerebrospinal fluid flow analysis is performed during each cardiac cycle to obtain the initial flow field of cerebrospinal fluid in the patient's spinal canal. This includes the following sub-implementation steps:

[0133] S51. Import the patient's intrathecal space model. Due to the complexity of the spinal canal computational domain, the computational domain is discretized into an unstructured mesh in Fluent Meshing software to allow it to freely and appropriately conform to the irregular wall. Considering that the Reynolds number in the flow within the spinal canal is much lower than 2000, three prism layers are generated at the wall, and the overall mesh size does not exceed 5mm.

[0134] S52. Open Fluent software and create a new patient-specific intrathecal space CFD calculation project. Set the Fluent calculation kernel to 3d, enable double precision, set the viscosity model to laminar flow, and enable the transient simulation option.

[0135] S53. Set the arachnoid membrane wall to be slip-free, apply the peak cerebrospinal fluid flow rate in the axial position to the inlet of the cerebrospinal fluid flow, and set the outlet gauge pressure to zero. Figure 4 The study investigated the changes in cerebrospinal fluid velocity during diastole and systole in patients with cerebrospinal fluid disease, and determined the simulation time step to be T / 100 = 0.01 s.

[0136] S54. Perform Fluent computation tasks, post-process the computation results, and provide the initial flow field of cerebrospinal fluid in the patient's spinal canal.

[0137] S6. In the dosage selection unit, the anesthesiologist selects the initial dose of local anesthetic based on clinical experience, which includes the following implementation steps:

[0138] S61. The anesthesiologist selects 0.75% ropivacaine as the local anesthetic for lower limb surgery.

[0139] S62. Based on clinical experience and considering factors such as the patient's height, age, weight, operation duration, analgesia level, puncture level, and needle insertion method, the initial local anesthetic dose is selected as 4 mL, and the injection time is 10 s.

[0140] S7. In the numerical calculation unit for intrathecal drug administration, import the three-dimensional model of the spinal canal and establish a coupling analysis: In the calculation model of intrathecal injection and delivery of local anesthetic in the patient, the initial injection volume of local anesthetic selected based on the anesthesiologist's experience is used as the drug inlet boundary condition. In the preoperative cerebrospinal fluid pulsation flow analysis model of the patient's spinal canal, the peak cerebrospinal fluid flow rate at the axial position measured by 4D PC-MRI is used as the cerebrospinal fluid inlet boundary condition, and the cerebrospinal fluid flow field under normal physiological conditions is used as the initial condition. The specific implementation steps include the following:

[0141] S71. Open Fluent software and create a new patient-specific intrathecal injection and delivery calculation project for local anesthetics. Set the Fluent calculation kernel to 3D, enable double precision, set the viscosity model to laminar flow, the flow model to Mixture multiphase, the phase volume fraction format type to Implicit, and the phase interface modeling to Dispersed mode. Enable the SlipVelocity option. Use the PISO format in the pressure-velocity coupled solver to simulate and solve the flow equation and the secondary phase volume fraction equation. Use the unit-based least squares method for gradient interpolation. Use PRESTO! (pressure interleaving term) for pressure discretization, the momentum discretization method to second-order upwind, and the volume fraction to first-order upwind discretization format. The sub-relaxation factor value is the software default. The normalization convergence criteria for velocity, continuity, momentum, and phase volume fraction are all 1E-05.

[0142] S72. Import the 3D model of the spinal canal, select the puncture plane as the L4-5 mid-plane, create the geometric features of the needle tube, the puncture needle model is 26G, the inner diameter of the tube is 3mm, the puncture depth is 1mm, the axial length of the computational domain is determined to be 340mm based on the thoracolumbar region of the MRI image, the computational domain is meshed, the overall mesh size does not exceed 5mm, the area near the needle tube is locally densified, the size is set to 0.2mm, and 3 prism layers are generated on the wall.

[0143] S73. In the calculation model of intrathecal injection and delivery of local anesthetics for individual patients, the initial injection volume and average injection time of local anesthetics selected based on the anesthesiologist's experience are used as the drug inlet boundary conditions. In the preoperative cerebrospinal fluid pulsation flow analysis model of the patient's spinal canal, the peak cerebrospinal fluid flow rate at the axial position measured by 4D PC-MRI is used as the cerebrospinal fluid inlet boundary condition and the cerebrospinal fluid flow field calculated using Fluent is used as the initial condition.

[0144] S74. Perform calculations on the intrathecal injection and delivery of local anesthetics for individual patients to obtain the concentration values ​​of local anesthetics at the blockade plane.

[0145] S8. In the dosage assessment unit, a quantitative assessment of the local anesthetic concentration value is carried out based on the calculation results, specifically including the following sub-implementation steps:

[0146] S81. Evaluate the concentration value of the local anesthetic at the target blocking plane in the calculation results. When the target blocking plane reaches the effective drug concentration, proceed to step S82. If the judgment criteria are not met, adjust the drug dosage and return to the implementation unit S6 to re-enter the drug dosage.

[0147] S82. Determine the total simulated injection volume and record the total onset time of the drug.

[0148] S83. The recommended dosage derived from simulation and theoretical analysis will be validated in a clinical setting; the dosage selection model will be further adjusted and optimized by observing actual analgesic effects and side effects.

[0149] S84. Collect clinical usage feedback, continuously optimize and adjust the medication model to make it more accurate and effective, and then construct a reference scheme for selecting the main medication dosage for patients with spinal anesthesia.

[0150] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A local anesthetic dosage control system based on CFD and PC-MRI coupling, characterized in that, include: The information collection unit is used to collect patient physical examination and medical assessment information; Geometric units are used to acquire T2-weighted MRI image sequences; The computational model unit is used to determine the range of the computational domain for the lumbar and thoracic vertebral segments. Measurement unit for phase encoding using PC-MRI; The cerebrospinal fluid dynamics unit is used to obtain the initial flow field of cerebrospinal fluid flow in the patient's spinal canal. Dosage selection unit, used to select the injection dose of local anesthetic; Intrathecal drug delivery calculation unit, used to establish coupling analysis to obtain the local anesthetic concentration value of the blocking plane; as well as Dosage assessment unit, used to quantitatively assess the concentration of local anesthetic drugs.

2. The working method of the local anesthetic dosage control system based on CFD and PC-MRI coupling according to claim 1, characterized in that, Includes the following steps: S1. Collect patient physical examination and medical assessment information through the information collection unit; S2. T2-weighted MRI image sequences are obtained through geometric units, the patient's MRI images are analyzed, and the spinal canal geometry is reconstructed by segmenting the images; S3. In the calculation model unit, the range of the calculation domain of the lumbar and thoracic vertebrae is determined according to the position of each vertebra on the patient's spine. S4. In the measurement unit, 4D PC-MRI is used to measure the cerebrospinal fluid flow data at the axial position of the patient's spinal canal; S5. In the cerebrospinal fluid dynamics unit, a CFD calculation model of the patient's intrathecal space is established using Fluent software to perform cerebrospinal fluid flow analysis during each cardiac cycle and obtain the initial cerebrospinal fluid flow field of the patient's spinal canal. S6. In the dosage selection unit, select the initial local anesthetic dosage for injection; S7. In the intrathecal drug delivery calculation unit, import the three-dimensional model of the spinal canal and establish a coupling analysis: In the calculation model of intrathecal injection and delivery of local anesthetics in the patient, the selected initial injection volume of local anesthetics is used as the drug inlet boundary condition. In the preoperative cerebrospinal fluid pulsation flow analysis model of the patient's spinal canal, the peak cerebrospinal fluid flow rate at the axial position measured by 4D PC-MRI is used as the cerebrospinal fluid inlet boundary condition and the cerebrospinal fluid flow field under normal physiological conditions is used as the initial condition. S8. In the dosage assessment unit, the concentration value of the local anesthetic is quantitatively assessed based on the calculation results of step S7.

3. The working method of the local anesthetic dosage control system based on CFD and PC-MRI coupling according to claim 2, characterized in that, Step S1 specifically includes the following steps: S11. Collect information on the patient's physical examination and medical assessment, including information on age, weight, body type, medical history and current health status; S12. Organize, analyze, and classify the patients' surgical categories, and extract characteristic information; S13. Collect previous clinical cases of spinal anesthesia, including drug delivery in different clinical surgeries, the range of drug dosage and the time of onset of the blocking response; S14. Input the data information obtained in steps S11-S13 into the information acquisition unit.

4. The working method of the local anesthetic dosage control system based on CFD and PC-MRI coupling according to claim 2, characterized in that, Step S2 specifically includes the following steps: S21. In the geometric unit, a standard 16-channel coil 3T scanner is used to acquire multiple sagittal high-resolution T2-weighted MRI images of a supine patient in a free-breathing state from T6 to S1; the field of view size is adjusted according to the anatomical dimensions of the chest, lumbar and sacral regions of different patients; S22. Use the segmentation tool to segment the MRI images of the chest and waist along the axis, segmenting the T6-S1 region; segment and exclude high signal regions in the MRI images that are close to the epidural space; after segmentation, export each segmentation result as a .STL file. S23. Transfer the segmentation results into Blender software for rigid body translation to align the sliced ​​models, create a surface profile mesh of the original geometry, and improve the geometric accuracy of the surface mesh through offset and smoothing.

5. The working method of the local anesthetic dosage control system based on CFD and PC-MRI coupling according to claim 2, characterized in that, Step S3 specifically includes the following steps: S31. In the computational model unit, based on the position of each vertebra on the spine in the midsagittal MR image of the patient, determine the characteristics of spinal canal scoliosis in the T6-S1 part of the lumbar and thoracic spine and the range of the computational domain. S32. Process the surface mesh through reverse engineering, fill the vertebral canal computational domain, and establish each vertebral plane according to the vertebral body position.

6. The working method of the local anesthetic dosage control system based on CFD and PC-MRI coupling according to claim 2, characterized in that, Step S4 specifically includes the following steps: S41. In the measurement unit, a 3T MRI scanner is used to perform 4D PC-MRI measurements on the patient; the patient lies supine on a scanning bed with a standard 16-channel head and neck coil. S42. The flow velocity coding direction is performed in front-back, foot-head and left-right. The 4D PC flow sequence of each patient is aligned in the sagittal plane, and the 3D stack covers the entire lumbar and thoracic vertebral segment. S43. Quantify the cerebrospinal fluid flow at six axial positions of the lumbar and thoracic vertebrae during a cardiac cycle, and select the axial position with the largest flow peak as the inlet boundary condition for the CFD simulation of cerebrospinal fluid flow.

7. The working method of the local anesthetic dosage control system based on CFD and PC-MRI coupling according to claim 2, characterized in that, Step S5 specifically includes the following steps: S51. In the cerebrospinal fluid dynamics unit, import the patient's intrathecal space model, and perform mesh discretization on the computational domain in Fluent Meshing software. Generate a CFD computational model with appropriate density by adjusting the local and global mesh sizes. S52. Create a new patient-specific intrathecal space CFD calculation project in Fluent software, set the Fluent calculation kernel to 3d, enable double precision, set the viscosity model to laminar flow, and enable the transient simulation option. S53. Set the arachnoid wall type, the inlet and outlet boundary conditions for cerebrospinal fluid flow, and determine the simulation time step based on the cerebrospinal fluid flow change pattern during the patient's diastolic and systolic phases. S54. Conduct Fluent calculations, post-process the calculation results, and provide the initial flow field of cerebrospinal fluid flow in the spinal canal during one cardiac cycle.

8. The working method of the local anesthetic dosage control system based on CFD and PC-MRI coupling according to claim 2, characterized in that, Step S6 specifically includes the following steps: S61. In the dosage selection unit, select the type and concentration of local anesthetic according to the actual clinical surgery. S62. Select the initial local anesthetic dose and injection duration.

9. The working method of the local anesthetic dosage control system based on CFD and PC-MRI coupling according to claim 2, characterized in that, Step S7 specifically includes the following steps: S71. In the intrathecal drug delivery calculation unit, import the three-dimensional model of the spinal canal, select the puncture plane, create the geometric features of the needle tube, determine the size of the calculation domain based on the thoracic and lumbar region of the MRI image, and perform meshing on the calculation domain. S72. Create a new patient-specific intrathecal injection and delivery calculation project for local anesthetics in Fluent software. Set the Fluent calculation kernel to 3d, enable double precision, set the viscosity model to laminar flow, the flow model to Mixture multiphase, the phase volume fraction format type to Implicit, the phase interface modeling to Dispersed mode, and enable the SlipVelocity option. S73. In the calculation model of intrathecal injection and delivery of local anesthetics for individual patients, the initial injection volume and average injection time of the selected local anesthetics are used as the drug inlet boundary conditions. In the preoperative cerebrospinal fluid pulsation flow analysis model of the spinal canal of patients, the peak cerebrospinal fluid flow rate at the axial position measured by 4D PC-MRI is used as the cerebrospinal fluid inlet boundary condition and the cerebrospinal fluid flow field under normal physiological conditions is used as the initial condition. S74. Perform calculations on the intrathecal injection and delivery of local anesthetics for individual patients to obtain the concentration values ​​of local anesthetics at the blockade plane.

10. The working method of the local anesthetic dosage control system based on CFD and PC-MRI coupling according to claim 2, characterized in that, Step S8 specifically includes the following steps: S81. In the dosage assessment unit, the concentration value of the local anesthetic at the target blocking plane in the calculation result of step S7 is assessed. When the target blocking plane reaches the effective drug concentration, step S82 is performed. If the judgment criteria are not met, the dosage is increased or decreased and then the process returns to step S6 to re-enter the dosage. S82. Determine the total simulated injection volume and record the total onset time of the drug. S83. Collect clinical usage feedback, further optimize and adjust the local anesthetic dosage model, and then construct a patient-based local anesthetic dosage plan.

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