[go: up one dir, main page]

CN119048631B - Visual imaging method, device, equipment and storage medium of tumor microenvironment - Google Patents

Visual imaging method, device, equipment and storage medium of tumor microenvironment Download PDF

Info

Publication number
CN119048631B
CN119048631B CN202411289136.9A CN202411289136A CN119048631B CN 119048631 B CN119048631 B CN 119048631B CN 202411289136 A CN202411289136 A CN 202411289136A CN 119048631 B CN119048631 B CN 119048631B
Authority
CN
China
Prior art keywords
sequence
dsc
contrast agent
cerebral blood
oxygen
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202411289136.9A
Other languages
Chinese (zh)
Other versions
CN119048631A (en
Inventor
刘萍
江桂华
简杰梅
华克磊
欧阳群慧
王伟
詹文峰
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Guangdong No 2 Peoples Hospital
Original Assignee
Guangdong No 2 Peoples Hospital
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Guangdong No 2 Peoples Hospital filed Critical Guangdong No 2 Peoples Hospital
Priority to CN202411289136.9A priority Critical patent/CN119048631B/en
Publication of CN119048631A publication Critical patent/CN119048631A/en
Application granted granted Critical
Publication of CN119048631B publication Critical patent/CN119048631B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/003—Reconstruction from projections, e.g. tomography
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10088—Magnetic resonance imaging [MRI]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30096—Tumor; Lesion

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Quality & Reliability (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Magnetic Resonance Imaging Apparatus (AREA)

Abstract

The embodiment of the invention provides a visual imaging method, device, equipment and storage medium of a tumor microenvironment, wherein the method obtains oxygen metabolism and neovascular parameter information of a glioma patient by acquiring MRI scanning data of the glioma patient, the MRI scanning data comprises a T2 * map sequence, a T2map sequence, a DWI sequence, a gradient echo DSC sequence and a spin echo DSC sequence which are acquired after contrast agent injection, and carries out visual imaging on the tumor microenvironment of the glioma patient according to the imaging parameters by adopting a vascular structure construction method and multi-parameter quantitative blood oxygen level dependent imaging based on the T2 * map sequence, the T2map sequence, the DWI sequence, the gradient echo DSC sequence and the spin echo DSC sequence which are acquired after contrast agent injection. And reestablishing a set of imaging system of noninvasive tumor microenvironment which can be clinically applied, and realizing the personalized metabolic heterogeneity visualization of glioma.

Description

Visual imaging method, device, equipment and storage medium of tumor microenvironment
Technical Field
The embodiment of the invention relates to the technical field of medical magnetic resonance imaging, in particular to a visual imaging method, device and equipment of tumor microenvironment and a storage medium.
Background
In recent years, tumor Microenvironment (TME) and its heterogeneity are considered key mediators of glioma progression and therapeutic response, while metabolic reprogramming is considered a major factor and feature affecting TME. High hypoxia and metabolic reprogramming are significant features of high grade gliomas, mainly manifested by the Warburg effect, i.e. aerobic glycolysis, but at the same time tumor cells can also undergo oxidative phosphorylation, with significant heterogeneity in glioma glycometabolism. The metabolic heterogeneity can cause different tolerance degrees of cells to radiotherapy and chemotherapy and the like. The tumor metabolism is further researched, a key 'metabolism check point' is searched, various medicaments for targeting glioma metabolism are developed, a tumor treatment strategy based on metabolism reprogramming can provide guidance for improving the diagnosis and treatment effectiveness of glioma from the aspect of drug resistance mechanism, and a new direction is opened for glioma treatment.
Currently, various metabolic imaging techniques including Positron Emission Tomography (PET), dynamic hyperpolarized 13C magnetic resonance spectroscopy (HP-13C-MRSI), and Deuterium Metabolism (DMI) are developed with respect to Tumor Microenvironment (TME) metabolic imaging. PET detects increased glucose uptake prevalent in malignant tissue by detecting the intensity of 18F-FDG radiation to quantify glucose uptake. However, PET is difficult to monitor dynamically for the entire glucose metabolic pathway, is limited by low background contrast in brains with high background glucose uptake, and is not conducive to longitudinal follow-up when examined for the presence of ionizing radiation. Although HP-13C-MRSI can detect downstream glucose metabolites, tumor glycolysis and tricarboxylic acid cycle kinetic flux, the detection mode requires additional hardware support due to the instability of HP-13C (only 1-2 min can be maintained) and the complexity of DNP technology, and clinical implementation worldwide still faces challenges and clinical transformation still has challenges. While Deuterium Metabolism (DMI) is capable of non-invasive in vivo imaging of multiple sugar metabolic pathways within a tumor, the clinical use of deuterated contrast agents has not been widespread.
Disclosure of Invention
The embodiment of the invention provides a visual imaging method, a device, equipment and a storage medium of a tumor microenvironment, which are used for overcoming various defects in the existing tumor microenvironment metabolic imaging technology, reestablishing a set of imaging system of a noninvasive tumor microenvironment which can be clinically applied, realizing the visualization and quantitative analysis of the individual metabolic heterogeneity of glioma based on multi-parameter imaging of MRI.
In a first aspect, an embodiment of the present invention provides a method for visualizing a tumor microenvironment, including:
MRI scanning data of a glioma patient are obtained, wherein the MRI scanning data comprise a T2 * map sequence, a T2map sequence, a DWI sequence, and a gradient echo DSC sequence and a spin echo DSC sequence which are acquired after contrast agent is injected;
obtaining oxygen metabolism and neovascular parameter information of the glioma patient through an vascular structure construction method and multi-parameter quantitative blood oxygen level dependent imaging based on the T2 * map sequence, the T2map sequence, the DWI sequence, and a gradient echo DSC sequence and a spin echo DSC sequence which are acquired after the contrast agent is injected;
determining imaging parameters of a tumor microenvironment of the glioma patient according to the oxygen metabolism and the neovascular parameter information of the glioma patient;
and carrying out visual imaging on the tumor microenvironment of the glioma patient according to the imaging parameters.
In a second aspect, an embodiment of the present invention further provides a visual imaging apparatus for tumor microenvironment, including:
The data acquisition module is used for acquiring MRI scanning data of a glioma patient, wherein the MRI scanning data comprise a T2 * map sequence, a T2map sequence, a DWI sequence, and a gradient echo DSC sequence and a spin echo DSC sequence which are acquired after contrast agent is injected;
The data processing module is used for obtaining the oxygen metabolism and the neovascular parameter information of the glioma patient through a vascular structure construction method and multi-parameter quantitative blood oxygen level dependent imaging based on the T2 * map sequence, the T2map sequence, the DWI sequence, the gradient echo DSC sequence and the spin echo DSC sequence which are acquired after the contrast agent is injected;
the imaging parameter determining module is used for determining imaging parameters of the tumor microenvironment of the glioma patient according to the oxygen metabolism and the neovascular parameter information of the glioma patient;
and the visualization module is used for carrying out visual imaging on the tumor microenvironment of the glioma patient according to the imaging parameters.
In a third aspect, an embodiment of the present invention further provides a computer apparatus, including:
One or more processors;
A memory for storing one or more programs,
The one or more programs, when executed by the one or more processors, cause the one or more processors to implement the visual imaging method of any of the first aspects.
In a fourth aspect, embodiments of the present invention further provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method of visual imaging as defined in any of the first aspects.
In the embodiment of the application, MRI scanning data of a glioma patient are acquired, wherein the MRI scanning data comprise a T2 * map sequence, a T2map sequence, a DWI sequence, a gradient echo DSC sequence and a spin echo DSC sequence which are acquired after a contrast agent is injected, the oxygen metabolism and the neovascular parameter information of the glioma patient are acquired through a vascular structure construction method and multi-parameter quantitative blood oxygen level dependent imaging based on the T2 * map sequence, the T2map sequence, the DWI sequence, the gradient echo DSC sequence and the spin echo DSC sequence which are acquired after the contrast agent is injected, the imaging parameters of the tumor microenvironment of the glioma patient are determined according to the oxygen metabolism and the neovascular parameter information of the glioma patient, and the tumor microenvironment of the glioma patient is subjected to visual imaging according to the imaging parameters. According to the embodiment of the application, a set of imaging system of noninvasive tumor microenvironment which can be clinically applied is established, oxygen metabolism and neovascular quantitative information of glioma patients can be obtained based on MRI (magnetic resonance imaging) multiparameter imaging, a biological tumor pathophysiology mechanism can be reflected according to the parameters, visualization of glioma tumor microenvironment oxygen metabolism reprogramming and quantification of metabolic heterogeneity can be realized, and further visualization and quantitative analysis of glioma individuation metabolic heterogeneity can be realized.
Drawings
Fig. 1 is a flowchart of a visual imaging method according to a first embodiment of the present invention;
fig. 2 is a schematic structural diagram of a visual imaging apparatus according to a second embodiment of the present invention;
Fig. 3 is a schematic structural diagram of a computer device according to a third embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Example 1
Fig. 1 is a flowchart of a visual imaging method provided in an embodiment of the present invention, where the embodiment is applicable to a case of performing noninvasive visual imaging on a tumor microenvironment of a brain tumor patient, and is also applicable to a case of applying noninvasive imaging on a brain glioma oxygen metabolism-reprogramming microenvironment in clinical work, and the method may be performed by a visual imaging device, which may be implemented by software and/or hardware, and may be configured in a computer device, for example, a server, a workstation, a personal computer, a medical system, a scanner, a medical detection device, and so on, and specifically includes the following steps:
S110, acquiring MRI scanning data of a glioma patient, wherein the MRI scanning data comprise a T2 * map sequence, a T2map sequence, a DWI sequence, and a gradient echo DSC sequence and a spin echo DSC sequence which are acquired after contrast agent is injected.
In the embodiment of the application, MRI scan data of a glioma patient can be obtained by performing MRI scan on the brain of the glioma patient, the MRI scan data refers to data obtained by using a magnetic resonance imaging (Magnetic Resonance Imaging, MRI) technology, the MRI scan data can be in the form of image data, for example, an MRI scanner can be configured to scan an object (such as a glioma patient) to obtain image data, and the MRI scanner can detect at least two echo signals by applying MRI pulse sequences on the object, which is not particularly limited in the embodiment of the application.
The MRI scan data to be acquired in the embodiment of the application comprises a T2 * map sequence, a T2map sequence, a DWI sequence, and a gradient echo DSC sequence and a spin echo DSC sequence which are acquired after the contrast agent is injected into the glioma patient.
It is understood that relaxation parameters of magnetic resonance scan subjects in the art typically include T1 (longitudinal relaxation time), T2 (transverse relaxation time), T2 * (inverse of transverse relaxation time), etc., T1 may be the time constant for longitudinal magnetization regrowth (e.g., along the main magnetic field), T2 relaxation may be the process of decay or dephasing of the transverse component of magnetization, and T2 may be the time constant for transverse magnetization decay or dephasing. In Magnetic Resonance Imaging (MRI), relaxation parameters are measures of the rate at which hydrogen nuclei in tissue resume their original state, typically assessed by measuring the longitudinal relaxation time T1 and the transverse relaxation time T2 of the tissue. Gradient echo and spin echo are two different MRI sequences that can both be used to measure relaxation parameters, but the principle and characteristics of operation are different.
In the embodiment of the application, a T2 * map sequence can be understood as a sequence which is acquired in magnetic resonance scanning and can be used for measuring a T2 * value (inverse of transverse relaxation time), a T2map sequence can be understood as a sequence which is acquired in magnetic resonance scanning and can be used for measuring a T2 value (transverse relaxation time), a DWI sequence is diffusion weighted imaging and is also a special sequence for magnetic resonance imaging and is commonly used for detecting diffusion motion of water molecules in a human body, a nuclear magnetic resonance DWI sequence is a special sequence which is rapidly excited in a magnetic field to generate an oscillation signal, namely, the motion condition of the water molecules can be detected, part of malignant tumor cells grow densely, free water is less, diffusion is limited in malignant tumors, and a high signal is formed, namely, the DWI sequence can be used for diagnosing tumors.
Gradient Echo DSC sequence refers to a gradient Echo sequence (GRADIENT RECALLED Echo, GRE) acquired after enhancement of MRI signal intensity and contrast using dynamic sensitivity contrast (Dynamic Susceptibility Contrast, DSC) techniques, which is a special technique for magnetic resonance imaging that uses paramagnetic contrast agents (e.g., gadolinium agents) to enhance MRI signal intensity and contrast. DSC perfusion imaging begins with intravenous injection of a bolus of gadolinium chelate followed by a series of rapid acquisition gradient or spin echo images over the organ of interest. The imaging energy of MRI is radio frequency pulse (RF), and a gradient echo sequence can be understood as a pulse sequence that generates echo signals and generates images by switching the direction of gradient fields after radio frequency excitation in magnetic resonance scanning. The radio frequency excitation angle is typically less than 90 deg. to obtain a larger transverse magnetization vector in a shorter longitudinal recovery time.
Spin Echo DSC sequence refers to Spin Echo sequence (Spin Echo, SE) acquired after enhancing the signal intensity and contrast of MRI by dynamic sensitivity contrast (Dynamic Susceptibility Contrast, DSC) technology, spin Echo sequence (Spin Echo Sequence) is a pulse sequence commonly used in Magnetic Resonance Imaging (MRI) and is used for exciting and acquiring signals of human tissues by using a combined pulse form of 90 ° and 180 °, because the imaging energy of MRI is mainly radio frequency pulse (RF), RF is a short wave electromagnetic wave, emitted into a magnetic field through a radio frequency coil surrounding a human body, and when the order of applying pulses in MRI is 90 ° pulse first and 180 ° pulse later, it is called Spin Echo sequence.
S120, obtaining oxygen metabolism and neovascular parameter information of a glioma patient through a vascular structure construction method and multi-parameter quantitative blood oxygen level dependent imaging based on a T2 * map sequence, a T2map sequence, a DWI sequence, a gradient echo DSC sequence and a spin echo DSC sequence which are acquired after contrast agent is injected.
In a specific implementation manner of the embodiment of the present application, S120 may include the following steps:
and S1201, determining the surface diffusion coefficient according to a linear registration result between the DWI sequence and a spin echo DSC sequence acquired after the contrast medium is injected.
Specifically, diffusion gradient-free weighted data b0 can be extracted from the DWI sequence, the image presented by the DWI sequence and the image presented by the spin echo DSC sequence acquired after injection of the contrast agent are linearly registered with reference to a b0 graph (i.e. an imaging result when the b value is 0), and a surface diffusion coefficient (Apparent Diffusion Coefficient, ADC) is calculated based on the formula adc= -ln [ (S/S0)/b ] according to the registered DWI data, wherein S0 is diffusion gradient-free weighted data, S is diffusion gradient weighted data, and b is the b value of the diffusion gradient.
S1202, performing data processing on a gradient echo DSC sequence and a spin echo DSC sequence acquired after the contrast medium is injected, and obtaining the cerebral blood volume and the cerebral blood flow rate.
In some specific examples, S1202 may include the following specific data processing steps:
s12021, determining a target image obtained by converting a gradient echo DSC sequence and a spin echo DSC sequence acquired after the contrast is injected.
Specifically, an image represented by a gradient echo DSC sequence acquired after the injection of the contrast agent may be used as a target image, or an image represented by a spin echo DSC sequence acquired after the injection of the contrast agent may be used as a target image.
S12022, performing motion correction on the target image, removing skull and correcting the acquisition time of each layer, and obtaining the processed target image.
Wherein the motion correction, skull removal and per-layer acquisition time correction can be performed on the target image using an open source tool kit FSL.
S12023, determining a relaxation rate change Δr 2 (t) generated by the contrast agent corresponding to each pixel in the processed target image.
Wherein the formula can be utilizedEach pixel DSC signal in the processed target image is converted to an R2 change Δr 2 (t) by the contrast agent. Note that TE in the above formula is an echo time of a sequence (spin echo DSC sequence or gradient echo DSC sequence) corresponding to the target image, S (t) is a DSC signal varying with time, and S 0 is a DSC signal before the contrast agent reaches the brain.
S12024, performing contrast agent leakage correction on the delta R 2 (t) corresponding to each pixel to obtain corrected delta R 2 (t). This reduces the effects of contrast leakage caused by disruption of the blood brain barrier.
And S12025, fitting the leakage corrected delta R 2 (t) to obtain a fitting result.
Wherein the gamma-variate function can be used to fit ΔR 2 (t) after leak correction to reduce the effect of recirculation of contrast agent.
S12026, converting DeltaR 2 (t) corresponding to each pixel into a contrast agent concentration C (t), and deconvoluting the contrast agent concentration C (t) corresponding to each pixel to obtain a tissue reaction function R (t).
Wherein, a singular value decomposition algorithm (block-circulant singular value decomposition) of block circulation can be used to deconvolve the contrast agent concentration C (t) of each pixel through an arterial input function AIF to obtain a tissue reaction function R (t).
S12027, calculating cerebral blood volume (cerebral blood volume, CBV) and cerebral blood flow rate (cerebral blood flow, CBF) from the tissue reaction function R (t) and the contrast agent concentration C (t).
Wherein, before the step of performing the fitting to the Δr 2 (t) after the leak correction, the step of obtaining the fitting result may further include the step of controlling the image quality as follows:
acquiring an arterial input function (arterial input functions, AIF) and a venous output function (venous output functions, VOF) using an automatic detection algorithm, the arterial input function and the venous output function being used to ensure data accuracy in calculating cerebral blood volume and cerebral blood flow rate;
And correcting the partial volume effect of the arterial input function according to the venous output function.
Among other things, the Arterial Input Function (AIF) may represent the change in contrast agent concentration in the cerebral blood supply artery over time.
And S1203, determining quantitative data of R2 and R2 * according to linear registration results of the T2 * map sequence and the T2map sequence and a spin echo DSC sequence acquired after contrast medium injection.
Specifically, quantitative data of T2 and T2 * can be extracted from the T2 * map sequence and the T2map sequence, linear registration is performed on the quantitative data of T2 and T2 * and an image represented by a spin echo DSC sequence acquired after injection of a contrast agent, the registered quantitative data of T2 and T2 * are converted into quantitative data of R2 and R2 *, and the quantitative data can be converted according to the following formula, wherein r2=1/T2 and R2 *＝1/T2*.
And S1204, obtaining oxygen metabolism parameter information of the glioma patient through multiparameter quantitative blood oxygen level dependent imaging according to the quantitative data of R2 and R2 *, the cerebral blood volume and the cerebral blood flow rate.
Wherein the oxygen metabolism parameter information comprises brain oxygen uptake fraction, brain oxygen metabolism rate and tissue oxygen tension. Brain oxygen uptake fraction (OEF), which reflects the proportion of oxygen that tissue takes from blood through capillary networks, is a specific biomarker for assessing tissue function. In areas of low perfusion with reduced cerebral blood flow, an increase in OEF can often be considered as a compensatory mechanism to maintain tissue function. Magnetic Resonance Imaging (MRI) is a relatively safe and contrast-rich imaging modality. If changes in OEF can be detected, there will be more important clinical application value and greater flexibility of investigation.
The multiparameter quantitative blood oxygen level dependent imaging (quantitative blood oxygenation level-dependent, qBOLD) technology, namely qBOLD technology, is one of the branch technologies for measuring OEF by MRI, and mainly utilizes the Blood Oxygen Level Dependent (BOLD) effect to indirectly reflect the change of intracranial blood oxygen metabolism. Due to the disturbance of deoxyhemoglobin (dHb) on MRI signals, qBOLD signals have certain difference under different echo times, and by means of an MR signal attenuation model, the OEF quantification of the whole brain voxel level can be realized by qBOLD, which is an imaging technology capable of achieving local tissue OEF quantification at the earliest time. The technology does not need to acquire specific geometric information of blood vessels, only needs statistical characteristics of blood vessel distribution, and is one of important reasons for the technology to be capable of achieving voxel level quantification.
In a specific implementation of this embodiment, the brain oxygen uptake fraction (OEF) may be obtained from the quantitative data of R2 and R2 *, and the cerebral blood volume, the brain oxygen metabolism rate (CMRO 2) may be obtained from the brain oxygen uptake fraction and the cerebral blood flow rate, and the tissue oxygen tension (PO 2) may be obtained from the brain oxygen metabolism rate and the brain oxygen uptake fraction.
In one example, the brain oxygen uptake fraction (OEF) can be derived from equation (1), the brain oxygen metabolism rate (CMRO 2) from equation (2), and the tissue oxygen tension (PO 2) from equation (3):
In the formula (1), gamma= 2.67502 ×10 8 rad/s/T) is the magnetic rotation ratio, Δχ=0.264×10 -6 is the difference in magnetization between fully oxygenated and fully deoxygenated hemoglobin, hct=0.42×0.85 is the microvascular erythrocyte pressure integral number, 0.85 is the correction coefficient of the small blood vessels, and B 0 =3T is the main magnetic field strength of MRI.
CMRO2＝OEF·CBF·Ca (2)
In formula (2), C a = 8.68mmol/mL, is arterial blood oxygen content.
In the formula (3), P 50 =27 mmHg is the half-saturated oxygen tension of hemoglobin, h=2.7 is the hil coefficient of the combination between oxygen and hemoglobin, and l=4.4 mmol/Hg/min is the oxygen conductivity of the tissue. Where PO 2 reflects the balance between oxygen input and consumption by the tissue.
S1205, obtaining the neovascular parameter information of the glioma patient through a vascular structure construction method according to the surface diffusion coefficient, the cerebral blood volume, the gradient echo DSC sequence and the spin echo DSC sequence which are acquired after the contrast agent is injected.
The neovascular parameter information may include, among other things, an indicator of microvascular type, microvascular density, and vascular size. The above vascular structure construction method can be understood as vascular structure imaging (VAI) MRI, a technique for researching and evaluating vascular structure and function using magnetic resonance imaging MRI technique, and a technique for non-invasively measuring parameters to describe brain microvascular structure heterogeneity. MRI is a non-invasive medical imaging technique that uses a strong external magnetic field and specific radio frequency pulses to act on hydrogen nuclei in the human body to generate magnetic resonance phenomena, and reconstructs images by collecting and processing resonance signals, thereby displaying the tissue structure inside the human body. Vascular imaging (VAI) MRI focuses on detailed imaging of the vascular system, including veins, arteries, and other vascular structures such as coronary arteries, intracranial vessels, cervical vessels, and the like. Such techniques are capable of providing detailed information about the morphology, structure and function of blood vessels, and are of great importance for diagnosing vascular-related diseases, assessing disease progression and monitoring the efficacy of treatment. In this embodiment, angiographic imaging (VAI) MRI may be used for intracranial vascular imaging, and may be used to determine the presence or absence of a malformation in an intracranial vessel, the presence or absence of an intracranial aneurysm, and the associated condition of the tumor body.
In some specific examples, S1205 may include the following specific data processing steps:
and constructing a vascular hysteresis loop chart based on the fitting result obtained in the specific implementation step of the step S1202.
An indicator (micro-VESSEL TYPE indicator, MTI) with a micro-blood vessel type is determined, wherein the area formed by a hysteresis loop in a blood vessel hysteresis loop diagram (vascular hysteresis loop, VHL), and the sign of the indicator of the micro-blood vessel type is determined by the direction of the hysteresis loop in the blood vessel hysteresis loop diagram, namely the sign of the MTI is determined by the direction of the VHL (when the VHL rotates clockwise, the sign of the MTI is positive, and when the VHL rotates anticlockwise, the sign of the MTI is negative). When the absolute value of MTI is small (e.g., -5s -5/2<MTI<5s-5/2), it represents mainly capillaries in the tissue, when MTI is small negative (e.g., -60s -5/2), it represents mainly venous vessels in the tissue, and when MTI is large positive (e.g., >60s -5/2), it represents mainly arterial vessels in the tissue.
Microvessel density (micro-VESSEL DENSITY, MVD) and vessel size (vessel size index, VSI) were calculated from the surface diffusion coefficient (ADC) and Cerebral Blood Volume (CBV). Specifically, the microvascular density (MVD) and the Vascular Size (VSI) can be calculated from equation (4) and equation (5):
Q max＝max[ΔR2,GE(t)]/max[(ΔR2,SE(t))3/2],ΔR2,GE (t) and DeltaR 2,SE (t) in the formula are fitting results obtained in the data processing process based on a gradient echo DSC sequence and a spin echo DSC sequence acquired after the contrast agent is injected, wherein b= 1.6781 is a constant; Is the average vessel lumen radius.
S130, determining imaging parameters of tumor microenvironment of the glioma patient according to oxygen metabolism and neovascular parameter information of the glioma patient.
The imaging parameters in the embodiment of the application refer to parameters required by visual imaging of tumor microenvironment, and comprise the types of parameters visually displayed, the numerical range of each parameter, color information, units, the parameter duty ratio and the like.
The oxygen metabolism and neovascular parameter information of the glioma patient may include six specific parameter information of brain oxygen uptake fraction (OEF), brain oxygen metabolism rate (CMRO 2), tissue oxygen tension (PO 2), indicator of Microvascular Type (MTI), microvascular density (MVD) and Vascular Size (VSI), and the six specific parameter information may be determined as the visually displayed parameter types. The numerical range of each type of parameter may be determined based on three specific parameter information of brain oxygen uptake fraction (OEF), brain oxygen metabolism rate (CMRO 2), tissue oxygen tension (PO 2) among the oxygen metabolism parameter information, and further classified according to the numerical range, and respective color information may be determined based on the result of the classification. The color information such as warm color and cool color can be assigned based on the MTI value of the indicator (MTI) of the microvascular type in the neovascular parameter information (for example, positive MTI value is assigned to warm color and negative MTI value is assigned to cool color), and the microvascular Radius (RU) and the microvascular density (NU) can be further determined based on the blood Vessel Size (VSI) and the microvascular density (MVD), wherein the microvascular Radius (RU) refers to the radius of the microvascular, the parameter reflects the fineness of the microvascular, the microvascular density (NU) refers to the number of the microvascular in unit volume, the parameter reflects the distribution density of the microvascular in unit volume, and the height of the microvascular density is closely related to the physiological function of organs or tissues.
In the embodiment of the application, the specific parameter information in the oxygen metabolism and the neovascular parameter information can be subjected to MRI biomarker information fusion and classified according to Tumor Microenvironment (TME), and the dimension of classification can be considered as classification of mitochondrial oxidation state, classification integrity of tumor neovascular system, and fusion of the classification information in an MRI imaging dataset and classification of TME in the dataset.
And S140, performing visual imaging on the tumor microenvironment of the glioma patient according to the imaging parameters.
The tumor microenvironment (tumor microenvironment, abbreviated as TME) is mainly composed of tumor cells, immune and inflammatory cells around the tumor cells, tumor-related fibroblasts, and nearby interstitial tissues, microvessels, and various cytokines and chemokines, and is a complex comprehensive system which can be divided into immune microenvironments mainly composed of immune cells and non-immune microenvironments mainly composed of fibroblast cells. The cellular composition and functional status of TMEs may vary greatly depending on the organ in which the tumor occurs, the intrinsic characteristics of the cancer cells, the stage of the tumor, and the characteristics of the patient.
It can be understood that the heterogeneity of oxygen metabolism in tumors, the change of new blood vessels and the change of energy metabolism can influence the Tumor Microenvironment (TME) landscape of the patients, so that imaging parameters determined by introducing oxygen metabolism and new blood vessel parameter information can be used for carrying out visual imaging on the tumor microenvironment of the patients with glioma, the visualization and quantitative analysis of the individual metabolic heterogeneity of glioma can be realized, and the visualization and quantitative analysis of the oxygen metabolism phenotype of glioma including aerobic glycolysis, namely the Warburg effect, can be further realized.
The method comprises the steps of obtaining MRI scanning data of a glioma patient, wherein the MRI scanning data comprise a T2 * map sequence, a T2map sequence, a DWI sequence, a gradient echo DSC sequence and a spin echo DSC sequence which are acquired after a contrast agent is injected, obtaining oxygen metabolism and neovascular parameter information of the glioma patient through a vascular structure construction method and multi-parameter quantitative blood oxygen level dependent imaging based on the T2 * map sequence, the T2map sequence, the DWI sequence, the gradient echo DSC sequence and the spin echo DSC sequence which are acquired after the contrast agent is injected, determining imaging parameters of a tumor microenvironment of the glioma patient according to the oxygen metabolism and the neovascular parameter information of the glioma patient, and carrying out visual imaging on the tumor microenvironment of the glioma patient according to the imaging parameters. According to the embodiment of the application, a set of noninvasive tumor microenvironment imaging system which can be clinically applied is established, oxygen metabolism and neovascular quantitative information of glioma patients can be obtained based on MRI (magnetic resonance imaging) multiparameter imaging, a biological tumor pathophysiology mechanism can be reflected according to the parameters, visualization of glioma tumor microenvironment oxygen metabolism reprogramming and quantification of metabolic heterogeneity can be realized, and further visualization and quantitative analysis of glioma individuation metabolic heterogeneity can be realized.
It should be noted that, for simplicity of description, the method embodiments are shown as a series of acts, but it should be understood by those skilled in the art that the embodiments are not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred embodiments, and that the acts are not necessarily required by the embodiments of the invention.
Example two
Fig. 2 is a block diagram of a visual imaging apparatus according to a second embodiment of the present invention, which may specifically include the following modules:
The data acquisition module 210 is configured to acquire MRI scan data of a glioma patient, where the MRI scan data includes a T2 * map sequence, a T2map sequence, a DWI sequence, and a gradient echo DSC sequence and a spin echo DSC sequence acquired after injection of a contrast agent;
The data processing module 220 is configured to obtain oxygen metabolism and neovascular parameter information of the glioma patient through a vascular structure construction method and multi-parameter quantitative blood oxygen level dependent imaging based on the T2 * map sequence, the T2map sequence, the DWI sequence, and the gradient echo DSC sequence and the spin echo DSC sequence acquired after the injection of the contrast agent;
An imaging parameter determining module 230, configured to determine imaging parameters of a tumor microenvironment of the glioma patient according to oxygen metabolism and neovascular parameter information of the glioma patient;
The visualization module 240 is configured to perform visual imaging on the tumor microenvironment of the glioma patient according to the imaging parameters.
In one embodiment of the present application, the data processing module 220 may include:
The surface diffusion coefficient calculation sub-module is used for determining a surface diffusion coefficient according to a linear registration result between the DWI sequence and the spin echo DSC sequence acquired after the contrast agent is injected;
the data processing submodule is used for carrying out data processing on the gradient echo DSC sequence and the spin echo DSC sequence acquired after the contrast agent is injected to obtain cerebral blood volume and cerebral blood flow velocity;
A quantitative data processing sub-module, configured to determine quantitative data of R2 and R2 * according to the T2 * map sequence and the linear registration result of the T2map sequence and a spin echo DSC sequence (GE-DSC), respectively;
The oxygen metabolism parameter information calculation submodule is used for obtaining oxygen metabolism parameter information of the glioma patient through multiparameter quantitative blood oxygen level dependent imaging according to the R2 and R2 * quantitative data, the cerebral blood volume and the cerebral blood flow rate;
And the neovascular parameter information calculation sub-module is used for obtaining neovascular parameter information of the glioma patient through a vascular structure construction method according to the surface diffusion coefficient, the cerebral blood volume, the gradient echo DSC sequence and the spin echo DSC sequence which are acquired after the contrast agent is injected.
In one embodiment of the invention, the data processing submodule includes:
The target image acquisition unit is used for determining a target image obtained by converting a gradient echo DSC sequence and a spin echo DSC sequence acquired after the contrast agent is injected;
the target image preprocessing unit is used for performing motion correction on the target image, removing skull and correcting the acquisition time of each layer to obtain a processed target image;
a change amount calculation unit configured to determine a relaxation rate change Δr 2 (t) by a contrast agent corresponding to each pixel in the processed target image;
A contrast agent leakage correction unit, configured to perform contrast agent leakage correction on Δr 2 (t) corresponding to each pixel, to obtain corrected Δr 2 (t);
the fitting unit is used for fitting the DeltaR 2 (t) after the leakage correction to obtain a fitting result;
The response unit is used for converting delta R 2 (t) corresponding to each pixel into a contrast agent concentration C (t), and deconvolving the contrast agent concentration C (t) corresponding to each pixel to obtain a tissue reaction function R (t);
and a cerebral blood volume and cerebral blood flow rate calculation unit for calculating a cerebral blood volume and cerebral blood flow rate from the tissue reaction function R (t) and the contrast agent concentration C (t).
In one embodiment of the invention, the data processing sub-module further comprises:
The image quality control unit is used for acquiring an artery input function and a vein output function by using an automatic detection algorithm, wherein the artery input function and the vein output function are used for ensuring the data accuracy of calculating the cerebral blood volume and the cerebral blood flow rate, and partial volume effect correction is carried out on the artery input function according to the vein output function.
In one embodiment of the invention, the oxygen metabolism parameter information comprises brain oxygen uptake fraction, brain oxygen metabolism rate and tissue oxygen tension, and the oxygen metabolism parameter information calculation submodule comprises:
a brain oxygen uptake score calculation unit for obtaining the brain oxygen uptake score from the R2 and R2 * quantitative data and the cerebral blood volume;
a brain oxygen metabolism rate calculation unit for obtaining the brain oxygen metabolism rate according to the brain oxygen uptake fraction and the brain blood flow rate;
And a tissue oxygen tension calculation unit for obtaining the tissue oxygen tension according to the brain oxygen metabolism rate and the brain oxygen uptake fraction.
In one embodiment of the invention, the neovascular parameter information comprises an indicator of a microvascular type, a microvascular density, a vessel size, and the neovascular parameter information calculation submodule comprises:
the image construction unit is used for constructing a blood vessel hysteresis echo diagram based on the fitting result;
an indicator obtaining unit, configured to determine an area formed by hysteresis loops in the vascular hysteresis loop diagram as an indicator of the microvascular type, where a sign of the indicator of the microvascular type is determined by a direction of the hysteresis loops in the vascular hysteresis loop diagram;
and the blood vessel information acquisition unit is used for calculating the micro-blood vessel density and the blood vessel size according to the surface diffusion coefficient and the cerebral blood volume.
The visual imaging device provided by the embodiment of the invention can execute the visual imaging method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example III
Fig. 3 is a schematic structural diagram of a computer device according to a third embodiment of the present invention. FIG. 3 illustrates a block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention. The computer device 12 shown in fig. 3 is merely an example and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.
As shown in FIG. 3, computer device 12 is in the form of a general purpose computing device. Components of computer device 12 may include, but are not limited to, one or more processors or processing units 16, a system memory 28, and a bus 18 that connects the various system components, including system memory 28 and processing units 16.
Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, micro channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Computer device 12 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by computer device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. The computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from or write to non-removable, nonvolatile magnetic media (not shown in FIG. 3, commonly referred to as a "hard disk drive"). Although not shown in fig. 3, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods of the embodiments described herein.
The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the computer device 12, and/or any devices (e.g., network card, modem, etc.) that enable the computer device 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Moreover, computer device 12 may also communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through network adapter 20. As shown, network adapter 20 communicates with other modules of computer device 12 via bus 18. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with computer device 12, including, but not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, for example, to implement the visual imaging method provided by the embodiment of the present invention.
Example IV
The fourth embodiment of the present invention further provides a computer readable storage medium, on which a computer program is stored, where the computer program when executed by a processor implements each process of the above visual imaging method, and the same technical effects can be achieved, so that repetition is avoided, and no further description is given here.
The computer readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.

Claims (8)

1.一种肿瘤微环境的可视化成像方法，其特征在于，包括：1. A method for visualizing a tumor microenvironment, comprising: 获取胶质瘤患者的MRI扫描数据，所述MRI扫描数据包括T2*map序列、T2map序列、DWI序列，以及注入对比剂后采集的梯度回波DSC序列和自旋回波DSC序列；Acquiring MRI scan data of a glioma patient, wherein the MRI scan data includes a T2 * map sequence, a T2map sequence, a DWI sequence, and a gradient echo DSC sequence and a spin echo DSC sequence acquired after contrast agent injection; 基于所述T2*map序列、所述T2map序列、所述DWI序列，以及所述注入对比剂后采集的梯度回波DSC序列和自旋回波DSC序列，通过血管结构构筑方法和多参数定量血氧水平依赖成像得到所述胶质瘤患者的氧代谢和新生血管参数信息；Based on the T2 * map sequence, the T2map sequence, the DWI sequence, and the gradient echo DSC sequence and the spin echo DSC sequence acquired after the injection of the contrast agent, the oxygen metabolism and neovascularization parameter information of the glioma patient is obtained through a vascular structure construction method and multi-parameter quantitative blood oxygen level-dependent imaging; 根据所述胶质瘤患者的氧代谢和新生血管参数信息确定所述胶质瘤患者的肿瘤微环境的成像参数；Determining imaging parameters of the tumor microenvironment of the glioma patient according to the oxygen metabolism and neovascularization parameter information of the glioma patient; 依据所述成像参数对所述胶质瘤患者的肿瘤微环境进行可视化成像；Performing visual imaging of the tumor microenvironment of the glioma patient according to the imaging parameters; 所述基于所述T2*map序列、所述T2map序列、所述DWI序列，以及所述注入对比剂后采集的梯度回波DSC序列和自旋回波DSC序列，通过血管结构构筑方法和多参数定量血氧水平依赖成像得到所述胶质瘤患者的氧代谢和新生血管参数信息，包括：The oxygen metabolism and neovascularization parameter information of the glioma patient is obtained by using a vascular structure construction method and multi-parameter quantitative blood oxygen level-dependent imaging based on the T2 * map sequence, the T2map sequence, the DWI sequence, and the gradient echo DSC sequence and the spin echo DSC sequence acquired after the contrast agent is injected, including: 根据所述DWI序列与所述注入对比剂后采集的自旋回波DSC序列之间的线性配准结果，确定表面扩散系数；determining a surface diffusion coefficient according to a linear registration result between the DWI sequence and the spin echo DSC sequence acquired after the injection of the contrast agent; 对所述注入对比剂后采集的梯度回波DSC序列和自旋回波DSC序列进行数据处理，得到脑血容积和脑血流速；Processing the gradient echo DSC sequence and the spin echo DSC sequence acquired after the contrast agent is injected to obtain cerebral blood volume and cerebral blood flow velocity; 根据所述T2*map序列和所述T2map序列分别与所述注入对比剂后采集的自旋回波DSC序列的线性配准结果，确定R2和R2*定量数据；Determine R2 and R2 * quantitative data according to the linear registration results of the T2 * map sequence and the T2map sequence with the spin echo DSC sequence acquired after the injection of the contrast agent; 根据所述R2和R2*定量数据、所述脑血容积、所述脑血流速，通过多参数定量血氧水平依赖成像得到所述胶质瘤患者的氧代谢参数信息；According to the R2 and R2 * quantitative data, the cerebral blood volume, and the cerebral blood flow rate, the oxygen metabolism parameter information of the glioma patient is obtained by multi-parameter quantitative blood oxygen level dependent imaging; 根据所述表面扩散系数和所述脑血容积，以及所述注入对比剂后采集的梯度回波DSC序列和自旋回波DSC序列，通过血管结构构筑方法得到所述胶质瘤患者的新生血管参数信息；According to the surface diffusion coefficient and the cerebral blood volume, as well as the gradient echo DSC sequence and the spin echo DSC sequence acquired after the contrast agent is injected, the new blood vessel parameter information of the glioma patient is obtained by a blood vessel structure construction method; 所述对所述注入对比剂后采集的梯度回波DSC序列和自旋回波DSC序列进行数据处理，得到脑血容积和脑血流速，包括：The step of performing data processing on the gradient echo DSC sequence and the spin echo DSC sequence acquired after the contrast agent is injected to obtain the cerebral blood volume and the cerebral blood flow velocity comprises: 确定由所述注入对比剂后采集的梯度回波DSC序列和自旋回波DSC序列转换得到的目标图像；Determining a target image converted from a gradient echo DSC sequence and a spin echo DSC sequence acquired after the contrast agent is injected; 对所述目标图像进行运动矫正、去除颅骨和每层采集时间校正，得到处理后的目标图像；Performing motion correction, skull removal, and each layer acquisition time correction on the target image to obtain a processed target image; 确定所述处理后的目标图像中的每个像素所对应的由对比剂而产生的弛豫率变化ΔR2(t)；Determine a relaxation rate change ΔR 2 (t) caused by the contrast agent corresponding to each pixel in the processed target image; 对每个所述像素所对应的ΔR2(t)进行对比剂泄漏矫正，得到校正后的ΔR2(t)；Performing contrast agent leakage correction on the ΔR 2 (t) corresponding to each pixel to obtain a corrected ΔR 2 (t); 对泄漏矫正后的ΔR2(t)进行拟合，得到拟合结果；Fitting the leakage-corrected ΔR 2 (t) to obtain the fitting result; 将每个所述像素所对应的ΔR2(t)转换为对比剂浓度C(t)，并对每个所述像素所对应的对比剂浓度C(t)进行反卷积，得到组织反应函数R(t)；Converting ΔR 2 (t) corresponding to each pixel into a contrast agent concentration C(t), and performing deconvolution on the contrast agent concentration C(t) corresponding to each pixel to obtain a tissue response function R(t); 根据所述组织反应函数R(t)和所述对比剂浓度C(t)计算脑血容积和脑血流速。The cerebral blood volume and cerebral blood flow velocity are calculated according to the tissue response function R(t) and the contrast agent concentration C(t). 2.根据权利要求1所述的方法，其特征在于，在所述对泄漏矫正后的ΔR2(t)进行拟合，得到拟合结果之前，还包括：2. The method according to claim 1, characterized in that before fitting the leakage-corrected ΔR 2 (t) to obtain the fitting result, it further comprises: 使用自动检测算法获取动脉输入函数和静脉输出函数，所述动脉输入函数和所述静脉输出函数用于确保计算所述脑血容积和所述脑血流速的数据准确性；Using an automatic detection algorithm to obtain an arterial input function and a venous output function, wherein the arterial input function and the venous output function are used to ensure the accuracy of data for calculating the cerebral blood volume and the cerebral blood flow rate; 根据所述静脉输出函数对所述动脉输入函数进行部分容积效应矫正。The arterial input function is corrected for partial volume effect according to the venous output function. 3.根据权利要求1所述的方法，其特征在于，所述氧代谢参数信息包括脑氧摄取分数、脑氧代谢率、组织氧张力；所述根据所述R2和R2*定量数据、所述脑血容积、所述脑血流速，通过多参数定量血氧水平依赖成像得到所述胶质瘤患者的氧代谢参数信息，包括：3. The method according to claim 1, characterized in that the oxygen metabolism parameter information includes brain oxygen uptake fraction, brain oxygen metabolic rate, and tissue oxygen tension; the oxygen metabolism parameter information of the glioma patient is obtained by multi-parameter quantitative blood oxygen level dependent imaging based on the R2 and R2 * quantitative data, the cerebral blood volume, and the cerebral blood flow rate, comprising: 根据所述R2和R2*定量数据、以及所述脑血容积，得到所述脑氧摄取分数；Obtaining the cerebral oxygen uptake fraction according to the R2 and R2 * quantitative data and the cerebral blood volume; 根据所述脑氧摄取分数和所述脑血流速得到所述脑氧代谢率；Obtaining the cerebral oxygen metabolic rate according to the cerebral oxygen uptake fraction and the cerebral blood flow rate; 根据所述脑氧代谢率和所述脑氧摄取分数得到所述组织氧张力。The tissue oxygen tension is obtained according to the brain oxygen metabolic rate and the brain oxygen uptake fraction. 4.根据权利要求1所述的方法，其特征在于，所述新生血管参数信息包括微血管类型的指示物、微血管密度、血管尺寸；所述根据所述表面扩散系数和所述脑血容积，以及所述注入对比剂后采集的梯度回波DSC序列和自旋回波DSC序列，通过血管结构构筑方法得到所述胶质瘤患者的新生血管参数信息，包括：4. The method according to claim 1, characterized in that the neovascularization parameter information includes an indicator of microvascular type, microvascular density, and blood vessel size; the neovascularization parameter information of the glioma patient is obtained by a vascular structure construction method based on the surface diffusion coefficient and the cerebral blood volume, and the gradient echo DSC sequence and spin echo DSC sequence collected after the injection of contrast agent, comprising: 基于所述拟合结果构建血管迟滞回线图；constructing a vascular hysteresis loop diagram based on the fitting results; 确定所述血管迟滞回线图中迟滞回线所构成的面积为所述微血管类型的指示物，其中，所述微血管类型的指示物的符号由所述血管迟滞回线图中迟滞回线的方向决定；Determining an area formed by a hysteresis loop in the vascular hysteresis loop diagram as an indicator of the microvessel type, wherein a sign of the indicator of the microvessel type is determined by a direction of the hysteresis loop in the vascular hysteresis loop diagram; 根据所述表面扩散系数和所述脑血容积计算得到所述微血管密度和所述血管尺寸。The microvessel density and the blood vessel size are calculated based on the surface diffusion coefficient and the cerebral blood volume. 5.根据权利要求1所述的方法，其特征在于，所述成像参数包括数值范围、颜色信息、单位信息；所述根据所述胶质瘤患者的氧代谢和新生血管参数信息确定所述胶质瘤患者的肿瘤微环境的成像参数，包括：5. The method according to claim 1, characterized in that the imaging parameters include a numerical range, color information, and unit information; and determining the imaging parameters of the tumor microenvironment of the glioma patient according to the oxygen metabolism and neovascularization parameter information of the glioma patient comprises: 基于所述胶质瘤患者的氧代谢参数信息中的微血管类型的指示物的数值确定所述颜色信息；Determining the color information based on the value of the indicator of the microvessel type in the oxygen metabolism parameter information of the glioma patient; 基于所述胶质瘤患者的氧代谢参数信息中的血管尺寸确定微血管半径，以及基于所述胶质瘤患者的氧代谢参数信息中的微血管密度确定微血管密度，由所述微血管半径及所述微血管密度确定所述单位信息；Determine the microvessel radius based on the blood vessel size in the oxygen metabolism parameter information of the glioma patient, and determine the microvessel density based on the microvessel density in the oxygen metabolism parameter information of the glioma patient, and determine the unit information by the microvessel radius and the microvessel density; 基于所述胶质瘤患者的氧代谢参数信息中的脑氧摄取分数、脑氧代谢率、组织氧张力确定所述数值范围。The numerical range is determined based on the brain oxygen uptake fraction, brain oxygen metabolic rate, and tissue oxygen tension in the oxygen metabolism parameter information of the glioma patient. 6.一种肿瘤微环境的可视化成像装置，其特征在于，包括：6. A visualization imaging device for tumor microenvironment, comprising: 数据获取模块，用于获取胶质瘤患者的MRI扫描数据，所述MRI扫描数据包括T2*map序列、T2map序列、DWI序列，以及注入对比剂后采集的梯度回波DSC序列和自旋回波DSC序列；A data acquisition module, used to acquire MRI scan data of glioma patients, wherein the MRI scan data includes a T2 * map sequence, a T2map sequence, a DWI sequence, and a gradient echo DSC sequence and a spin echo DSC sequence acquired after contrast agent injection; 数据处理模块，用于基于所述T2*map序列、所述T2map序列、所述DWI序列，以及所述注入对比剂后采集的梯度回波DSC序列和自旋回波DSC序列，通过血管结构构筑方法和多参数定量血氧水平依赖成像得到所述胶质瘤患者的氧代谢和新生血管参数信息；A data processing module, for obtaining oxygen metabolism and neovascularization parameter information of the glioma patient through a vascular structure construction method and multi-parameter quantitative blood oxygen level-dependent imaging based on the T2 * map sequence, the T2map sequence, the DWI sequence, and the gradient echo DSC sequence and spin echo DSC sequence acquired after the injection of the contrast agent; 成像参数确定模块，用于根据所述胶质瘤患者的氧代谢和新生血管参数信息确定所述胶质瘤患者的肿瘤微环境的成像参数；An imaging parameter determination module, used to determine the imaging parameters of the tumor microenvironment of the glioma patient according to the oxygen metabolism and neovascularization parameter information of the glioma patient; 可视化模块，用于依据所述成像参数对所述胶质瘤患者的肿瘤微环境进行可视化成像；A visualization module, used for visualizing the tumor microenvironment of the glioma patient according to the imaging parameters; 所述数据处理模块包括：表面扩散系数计算子模块，用于根据所述DWI序列与所述注入对比剂后采集的自旋回波DSC序列之间的线性配准结果，确定表面扩散系数；数据处理子模块，用于对所述注入对比剂后采集的梯度回波DSC序列和自旋回波DSC序列进行数据处理，得到脑血容积和脑血流速；定量数据处理子模块，用于根据所述T2*map序列和所述T2map序列分别与自旋回波DSC序列(GE-DSC)的线性配准结果，确定R2和R2*定量数据；氧代谢参数信息计算子模块，用于根据所述R2和R2*定量数据、所述脑血容积、所述脑血流速，通过多参数定量血氧水平依赖成像得到所述胶质瘤患者的氧代谢参数信息；新生血管参数信息计算子模块，用于根据所述表面扩散系数和所述脑血容积，以及所述注入对比剂后采集的梯度回波DSC序列和自旋回波DSC序列，通过血管结构构筑方法得到所述胶质瘤患者的新生血管参数信息；The data processing module includes: a surface diffusion coefficient calculation submodule, which is used to determine the surface diffusion coefficient according to the linear registration result between the DWI sequence and the spin echo DSC sequence acquired after the injection of contrast agent; a data processing submodule, which is used to perform data processing on the gradient echo DSC sequence and the spin echo DSC sequence acquired after the injection of contrast agent to obtain cerebral blood volume and cerebral blood flow rate; a quantitative data processing submodule, which is used to perform data processing on the gradient echo DSC sequence and the spin echo DSC sequence acquired after the injection of contrast agent to obtain cerebral blood volume and cerebral blood flow rate according to the linear registration result between the T2*map sequence and the T2map sequence and the spin echo DSC sequence (GE-DSC) respectively. The registration result determines the quantitative data of R2 and R2*; an oxygen metabolism parameter information calculation submodule is used to obtain the oxygen metabolism parameter information of the glioma patient through multi-parameter quantitative blood oxygen level dependent imaging according to the quantitative data of R2 and R2*, the cerebral blood volume, and the cerebral blood flow rate; a neovascularization parameter information calculation submodule is used to obtain the neovascularization parameter information of the glioma patient through a vascular structure construction method according to the surface diffusion coefficient and the cerebral blood volume, as well as the gradient echo DSC sequence and spin echo DSC sequence collected after the injection of the contrast agent; 数据处理子模块包括：目标图像获取单元，用于确定由所述注入对比剂后采集的梯度回波DSC序列和自旋回波DSC序列转换得到的目标图像；目标图像预处理单元，用于对所述目标图像进行运动矫正、去除颅骨和每层采集时间校正，得到处理后的目标图像；变化量计算单元，用于确定所述处理后的目标图像中的每个像素所对应的由对比剂而产生的弛豫率变化ΔR2(t)；对比剂泄漏矫正单元，用于对每个所述像素所对应的ΔR2(t)进行对比剂泄漏矫正，得到校正后的ΔR2(t)；拟合单元，用于对泄漏矫正后的ΔR2(t)进行拟合，得到拟合结果；响应单元，用于将每个所述像素所对应的ΔR2(t)转换为对比剂浓度C(t)，并对每个所述像素所对应的对比剂浓度C(t)进行反卷积，得到组织反应函数R(t)；脑血容积和脑血流速计算单元，用于根据所述组织反应函数R(t)和所述对比剂浓度C(t)计算脑血容积和脑血流速。The data processing submodule includes: a target image acquisition unit, used to determine the target image converted by the gradient echo DSC sequence and the spin echo DSC sequence acquired after the injection of the contrast agent; a target image preprocessing unit, used to perform motion correction, skull removal and each layer acquisition time correction on the target image to obtain a processed target image; a change calculation unit, used to determine the relaxation rate change ΔR2(t) caused by the contrast agent corresponding to each pixel in the processed target image; a contrast agent leakage correction unit, used to calculate the relaxation rate change ΔR2(t) corresponding to each pixel. R2(t) is corrected for contrast agent leakage to obtain a corrected ΔR2(t); a fitting unit is used to fit the leakage-corrected ΔR2(t) to obtain a fitting result; a response unit is used to convert the ΔR2(t) corresponding to each pixel into a contrast agent concentration C(t), and deconvolute the contrast agent concentration C(t) corresponding to each pixel to obtain a tissue response function R(t); a cerebral blood volume and cerebral blood flow velocity calculation unit is used to calculate the cerebral blood volume and cerebral blood flow velocity according to the tissue response function R(t) and the contrast agent concentration C(t). 7.一种计算机设备，其特征在于，所述计算机设备包括：7. A computer device, characterized in that the computer device comprises: 一个或多个处理器；one or more processors; 存储器，用于存储一个或多个程序，a memory for storing one or more programs, 当所述一个或多个程序被所述一个或多个处理器执行，使得所述一个或多个处理器实现如权利要求1-5中任一所述的可视化成像方法。When the one or more programs are executed by the one or more processors, the one or more processors implement the visualization imaging method according to any one of claims 1 to 5. 8.一种计算机可读存储介质，其特征在于，所述计算机可读存储介质上存储计算机程序，所述计算机程序被处理器执行时实现如权利要求1-5中任一项所述的可视化成像方法。8. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the visualization imaging method according to any one of claims 1 to 5 is implemented.
CN202411289136.9A 2024-09-14 2024-09-14 Visual imaging method, device, equipment and storage medium of tumor microenvironment Active CN119048631B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202411289136.9A CN119048631B (en) 2024-09-14 2024-09-14 Visual imaging method, device, equipment and storage medium of tumor microenvironment

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202411289136.9A CN119048631B (en) 2024-09-14 2024-09-14 Visual imaging method, device, equipment and storage medium of tumor microenvironment

Publications (2)

Publication Number Publication Date
CN119048631A CN119048631A (en) 2024-11-29
CN119048631B true CN119048631B (en) 2025-02-11

Family

ID=93583397

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202411289136.9A Active CN119048631B (en) 2024-09-14 2024-09-14 Visual imaging method, device, equipment and storage medium of tumor microenvironment

Country Status (1)

Country Link
CN (1) CN119048631B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN119724552B (en) * 2024-12-12 2025-09-26 中国人民解放军总医院第一医学中心 Prediction method for effect of treating early-stage neoplastic lesions of superficial stomach

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021052898A1 (en) * 2019-09-20 2021-03-25 Koninklijke Philips N.V. Motion corrected tracer-kinetic mapping using mri
CN113469943A (en) * 2021-06-03 2021-10-01 广西医科大学附属肿瘤医院 Method, system and application for accurate registration of tumor nuclear magnetic resonance and histology

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021052898A1 (en) * 2019-09-20 2021-03-25 Koninklijke Philips N.V. Motion corrected tracer-kinetic mapping using mri
CN113469943A (en) * 2021-06-03 2021-10-01 广西医科大学附属肿瘤医院 Method, system and application for accurate registration of tumor nuclear magnetic resonance and histology

Also Published As

Publication number Publication date
CN119048631A (en) 2024-11-29

Similar Documents

Publication Publication Date Title
Fan et al. Comparison of cerebral blood flow measurement with [15O]-water positron emission tomography and arterial spin labeling magnetic resonance imaging: a systematic review
Zhang et al. New magnetic resonance imaging methods in nephrology
EP1171028B1 (en) System for determining haemodynamic indices by use of tomographic data
JP6679467B2 (en) Magnetic resonance imaging apparatus and method for calculating oxygen uptake rate
Johns et al. Pulmonary MR angiography and perfusion imaging—a review of methods and applications
Steeden et al. Rapid flow assessment of congenital heart disease with high-spatiotemporal-resolution gated spiral phase-contrast MR imaging
Zaitsu et al. Mapping of cerebral oxygen extraction fraction changes with susceptibility-weighted phase imaging
CN119048631B (en) Visual imaging method, device, equipment and storage medium of tumor microenvironment
EP2271257B1 (en) Imaging technique
Ma et al. Quantification of brain oxygen extraction fraction using QSM and a hyperoxic challenge
AU2020349121A1 (en) System, method, and computer program product for predicting, anticipating, and/or assessing tissue characteristics
Katada et al. A comparative study between arterial spin labeling and CT perfusion methods on hepatic portal venous flow
US20130150705A1 (en) Systems and methods for imaging a blood vessel using temperature sensitive magnetic resonance imaging
Seemann et al. Imaging gravity-induced lung water redistribution with automated inline processing at 0.55 T cardiovascular magnetic resonance
Xiang et al. Evaluation of regional variability and measurement reproducibility of intravoxel incoherent motion diffusion weighted imaging using a cardiac stationary phase based ECG trigger method
Blanken et al. Coronary flow assessment using accelerated 4D flow MRI with respiratory motion correction
Dogra et al. Acetazolamide-augmented BOLD MRI to assess whole-brain cerebrovascular reactivity in chronic steno-occlusive disease using principal component analysis
Niendorf et al. MRI of kidney size matters
Fischer et al. Assessment of pulmonary perfusion in a single shot using SEEPAGE
Fan et al. Demonstration of pulmonary perfusion heterogeneity induced by gravity and lung inflation using arterial spin labeling
Fan et al. Assessment of pulmonary parenchyma perfusion with FAIR in comparison with DCE-MRI—Initial results
Fan et al. Application value of magnetic resonance perfusion imaging in the early diagnosis of rat hepatic fibrosis
Zhang et al. Quantitative Magnetic Resonance Imaging Methods for the Assessment and Prediction of Treatment Response to Transarterial Chemoembolization in Hepatocellular Carcinoma
Wang et al. Functional and Molecular Imaging Techniques
Radjenovic et al. Clinical Cardiovascular Imaging

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant