CN113674248B - Magnetic resonance amide proton transfer imaging magnetic susceptibility detection method and related equipment - Google Patents
Magnetic resonance amide proton transfer imaging magnetic susceptibility detection method and related equipment Download PDFInfo
- Publication number
- CN113674248B CN113674248B CN202110969450.1A CN202110969450A CN113674248B CN 113674248 B CN113674248 B CN 113674248B CN 202110969450 A CN202110969450 A CN 202110969450A CN 113674248 B CN113674248 B CN 113674248B
- Authority
- CN
- China
- Prior art keywords
- amide proton
- magnetic resonance
- proton transfer
- transfer imaging
- image
- 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
Links
- 238000012546 transfer Methods 0.000 title claims abstract description 264
- 125000003368 amide group Chemical group 0.000 title claims abstract description 183
- 238000003384 imaging method Methods 0.000 title claims abstract description 175
- 238000001514 detection method Methods 0.000 title claims abstract description 31
- 238000000034 method Methods 0.000 claims abstract description 22
- 238000013507 mapping Methods 0.000 claims description 16
- 238000001228 spectrum Methods 0.000 claims description 15
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 12
- 238000004891 communication Methods 0.000 claims description 10
- 230000005415 magnetization Effects 0.000 claims description 7
- 238000012360 testing method Methods 0.000 claims description 6
- 238000001914 filtration Methods 0.000 claims description 4
- 238000010606 normalization Methods 0.000 claims description 4
- 208000014829 head and neck neoplasm Diseases 0.000 abstract description 6
- 206010028980 Neoplasm Diseases 0.000 description 8
- 102000004169 proteins and genes Human genes 0.000 description 8
- 108090000623 proteins and genes Proteins 0.000 description 8
- 229920001184 polypeptide Polymers 0.000 description 6
- 102000004196 processed proteins & peptides Human genes 0.000 description 6
- 108090000765 processed proteins & peptides Proteins 0.000 description 6
- 210000001519 tissue Anatomy 0.000 description 5
- 230000008859 change Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 239000000126 substance Substances 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000035755 proliferation Effects 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 210000004881 tumor cell Anatomy 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 210000004027 cell Anatomy 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 230000002452 interceptive effect Effects 0.000 description 2
- 230000003902 lesion Effects 0.000 description 2
- 238000011002 quantification Methods 0.000 description 2
- 238000009738 saturating Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 210000004204 blood vessel Anatomy 0.000 description 1
- 210000000988 bone and bone Anatomy 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000002059 diagnostic imaging Methods 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000004083 survival effect Effects 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
- A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20092—Interactive image processing based on input by user
- G06T2207/20104—Interactive definition of region of interest [ROI]
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Theoretical Computer Science (AREA)
- Medical Informatics (AREA)
- General Health & Medical Sciences (AREA)
- Radiology & Medical Imaging (AREA)
- General Physics & Mathematics (AREA)
- Pathology (AREA)
- High Energy & Nuclear Physics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Biophysics (AREA)
- Quality & Reliability (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Magnetic Resonance Imaging Apparatus (AREA)
Abstract
The application discloses a magnetic resonance amide proton transfer imaging magnetic susceptibility detection method and related equipment, wherein the method comprises the steps of obtaining an image data set of magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of a magnetic resonance amide proton transfer imaging sequence; determining a region of interest corresponding to the image dataset for magnetic resonance amide proton transfer imaging; and determining transfer rate data corresponding to the region of interest based on the image dataset of the magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of the magnetic resonance amide proton transfer imaging sequence. According to the method, the transfer rate data corresponding to the region of interest is obtained and determined by analyzing the image data set of the magnetic resonance amide proton transfer imaging of the head and neck tumor and the zeroth-order symmetric model of the magnetic resonance amide proton transfer imaging sequence, and the richness of the transfer rate data is improved, so that the application value of the magnetic resonance amide proton transfer imaging is improved.
Description
Technical Field
The application relates to the technical field of medical imaging, in particular to a magnetic resonance amide proton transfer imaging magnetic transfer rate detection method and related equipment.
Background
Chemical exchange saturation transfer is a novel magnetic resonance molecular imaging technology, has the advantages of detecting free protein and polypeptide in tissues and cells and the like, and rapidly leads to wide research and study in the field of biological hospitals. The APT technology is based on a Chemical Exchange Saturation Transfer (CEST) effect, detects a surrounding free water signal after exchanging with an amide proton through selectively pre-saturating signals of the amide proton in a free protein and a polypeptide, and indirectly reflects the change of the concentration of the free protein and the polypeptide through collecting the change of the signals before and after the free water saturation, so that magnetic resonance amide proton transfer imaging becomes an important index for identifying tumor tissues. Therefore, it is desirable to comprehensively acquire the transfer rate data of the magnetic resonance amide proton transfer imaging so as to improve the evaluation value of the magnetic resonance amide proton transfer imaging.
Disclosure of Invention
The technical problem to be solved by the present application is to provide a method and related apparatus for detecting the magnetic transfer rate of magnetic resonance amide proton transfer imaging (mri) for visual quantification, in view of the deficiencies in the prior art.
In order to solve the above technical problem, a first aspect of embodiments of the present application provides a magnetic resonance amide proton transfer imaging magnetic susceptibility detection method, including:
acquiring an image data set of magnetic resonance amide proton transfer imaging and a zeroth order symmetric model of a magnetic resonance amide proton transfer imaging sequence;
determining a region of interest corresponding to the image dataset for magnetic resonance amide proton transfer imaging;
determining transfer rate data corresponding to the region of interest based on the image dataset of the magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of a magnetic resonance amide proton transfer imaging sequence, wherein the transfer rate data comprises one or more of amide proton transfer imaging magnetic transfer rate values of all pixel points in the region of interest, statistical data of the amide proton transfer imaging magnetic transfer rate values, a Z spectrogram of amide proton transfer imaging magnetic field uniformity, a histogram of the amide proton transfer imaging magnetic transfer rate values, a mapping image of the amide proton transfer imaging, a mapping image of a main magnetic field, and a mapping image of the amide proton transfer imaging superimposed with an original image.
The magnetic resonance amide proton transfer imaging magnetic susceptibility detection method includes the following steps:
normalizing each image data in the image data set of the magnetic resonance amide proton transfer imaging to obtain each image data after normalization;
selecting basic image data from the normalized image data, and determining an interested area corresponding to the basic image data;
and taking the region of interest as the region of interest corresponding to the image data set of the magnetic resonance amide proton transfer imaging.
The magnetic resonance amide proton transfer imaging magnetic susceptibility detection method comprises the steps that basic image data are normalized image data which are positioned at the forefront in imaging sequence in the normalized image data; the determining of the region of interest corresponding to the basic image data specifically includes:
multiplying the pixel value of each pixel point in the basic image data by 255 to map the pixel value of each pixel point to 0-255 so as to obtain mapped basic image data;
and determining the interested region corresponding to the basic image data based on the mapped basic image data.
The method for detecting the magnetic transfer rate of magnetic resonance amide proton transfer imaging includes the following steps of:
determining a transfer rate image of the region of interest based on the image dataset of magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of a magnetic resonance amide proton transfer imaging sequence, wherein the magnetization transfer rate image of amide protons is extracted from the Z spectrum at a frequency of 3.3-3.7ppm with the frequency of water as a center frequency and the frequency of water being set to 0ppm in the Z spectrum;
denoising the transfer rate image, and determining transfer rate data corresponding to the region of interest based on the denoised transfer rate image.
The magnetic resonance amide proton transfer imaging magnetic susceptibility detection method specifically comprises the following steps of:
respectively calculating the pixel absolute value of the pixel value of each pixel point in the transfer rate image;
and filtering the pixel points with the pixel absolute values smaller than the preset threshold value to obtain the denoised transfer rate image.
The magnetic resonance amide proton transfer imaging magnetic susceptibility detection method is characterized in that the statistical data comprise one or more of the average value, the median, the maximum value, the minimum value, the standard deviation, the kurtosis coefficient, the skewness coefficient and the 90% digit of the numerical values.
In a second aspect, the present invention provides a magnetic resonance amide proton transfer imaging susceptibility testing system, including:
the acquisition module is used for acquiring an image data set of magnetic resonance amide proton transfer imaging and a zeroth order symmetric model of a magnetic resonance amide proton transfer imaging sequence;
a first determination module for determining a region of interest corresponding to the image dataset for magnetic resonance amide proton transfer imaging;
a second determining module, configured to determine transfer rate data corresponding to the region of interest based on the image dataset of magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of a magnetic resonance amide proton transfer imaging sequence.
The magnetic resonance amide proton transfer imaging magnetic susceptibility detection system is characterized in that the magnetic resonance amide proton transfer imaging magnetic susceptibility detection system is established based on Python language.
A third aspect of embodiments of the present application provides a computer-readable storage medium storing one or more programs, which are executable by one or more processors to implement the steps in the magnetic resonance amide proton transfer imaging susceptibility detecting method as described in any of the above.
A fourth aspect of the embodiments of the present application provides a terminal device, including: a processor, a memory, and a communication bus; the memory has stored thereon a computer readable program executable by the processor;
the communication bus realizes connection communication between the processor and the memory;
the processor, when executing the computer readable program, implements the steps of the magnetic resonance amide proton transfer imaging magnetic susceptibility detection method as described in any one of the above.
Has the advantages that: compared with the prior art, the application provides a magnetic resonance amide proton transfer imaging magnetic susceptibility detection method and related equipment, wherein the method comprises the steps of acquiring an image data set of magnetic resonance amide proton transfer imaging and a zeroth-order symmetric model of a magnetic resonance amide proton transfer imaging sequence; determining a region of interest corresponding to the image dataset for magnetic resonance amide proton transfer imaging; and determining transfer rate data corresponding to the region of interest based on the image dataset of the magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of the magnetic resonance amide proton transfer imaging sequence. According to the method, the transfer rate data corresponding to the region of interest is obtained and determined by analyzing the image data set of the magnetic resonance amide proton transfer imaging of the head and neck tumor and the zeroth-order symmetric model of the magnetic resonance amide proton transfer imaging sequence, and the richness of the transfer rate data is improved, so that the application value of the magnetic resonance amide proton transfer imaging is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without any inventive work.
Fig. 1 is a flowchart of a magnetic resonance amide proton transfer imaging magnetic susceptibility detection method provided in the present application.
FIG. 2 shows the Z spectrum.
Fig. 3 is a mapped image of the main magnetic field.
Fig. 4 is a mapping image of amide proton transfer imaging superimposed with the original image.
Fig. 5 is a mapping image of amide proton transfer imaging.
FIG. 6 is a histogram of amide proton transfer imaging magnetic susceptibility values.
Fig. 7 is a schematic structural diagram of a magnetic resonance amide proton transfer imaging magnetic susceptibility detection apparatus provided in the present application.
Fig. 8 is a schematic structural diagram of a terminal device provided in the present application.
Detailed Description
In order to make the purpose, technical scheme and effect of the present application clearer and clearer, the present application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.
It will be understood by those within the art that, unless otherwise defined, all terms (including 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 belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
It should be understood that, the sequence numbers and sizes of the steps in this embodiment do not mean the execution sequence, and the execution sequence of each process is determined by its function and inherent logic, and should not constitute any limitation on the implementation process of this embodiment.
The inventor finds that chemical exchange saturation transfer imaging (CEST) is a novel magnetic resonance molecular imaging technology, has the advantages of noninvasive detection of free proteins and polypeptides in tissues and cells and the like, and rapidly leads to wide research and research in the field of biomedicine. The method comprises the steps of detecting a peripheral free water signal after exchanging with an amide proton by selectively pre-saturating signals of amide protons in free protein and polypeptide based on a chemical exchange saturation transfer effect, and indirectly reflecting the change of the concentration of the free protein and the polypeptide by collecting the change of the signals before and after the free water is saturated, so that magnetic resonance amide proton transfer imaging becomes an important index for identifying tumor tissues. Therefore, it is desirable to comprehensively acquire the transfer rate data of the magnetic resonance amide proton transfer imaging so as to improve the evaluation value of the magnetic resonance amide proton transfer imaging.
In order to solve the above problem, in the embodiment of the present application, an image data set for magnetic resonance amide proton transfer imaging and a zeroth order symmetric model of a magnetic resonance amide proton transfer imaging sequence are acquired; determining a region of interest corresponding to the image dataset for magnetic resonance amide proton transfer imaging; and determining transfer rate data corresponding to the region of interest based on the image dataset of the magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of the magnetic resonance amide proton transfer imaging sequence. According to the method, the transfer rate data corresponding to the region of interest is obtained and determined by analyzing the image data set of the magnetic resonance amide proton transfer imaging of the head and neck tumor and the zeroth-order symmetric model of the magnetic resonance amide proton transfer imaging sequence, and the richness of the transfer rate data is improved, so that the application value of the magnetic resonance amide proton transfer imaging is improved.
The following further describes the content of the application by describing the embodiments with reference to the attached drawings.
The embodiment provides a magnetic resonance amide proton transfer imaging magnetic susceptibility detection method, which can be used as a functional module, and the steps of the magnetic resonance amide proton transfer imaging magnetic susceptibility detection method provided by the embodiment are implemented by the functional module. In a specific implementation manner, the function module can be implemented by a python programming language, and the open source library such as simpletick, Opencv, Scipy is called when the function is implemented by the python programming language.
As shown in fig. 1, the method for detecting magnetic resonance amide proton transfer imaging magnetic susceptibility provided in this embodiment specifically includes:
s10, acquiring an image data set of magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of the magnetic resonance amide proton transfer imaging sequence.
In particular, the image dataset for magnetic resonance amide proton transfer imaging comprises an amide proton transfer imaging sequence, e.g. the amide proton transfer imaging sequence comprises a scan by a magnetic resonance scanner with a saturation offset from-7 ppm to 7ppm, wherein the saturation offset is shifted by a shift step size of 0.2 ppm. The zeroth order symmetric model of the magnetic resonance amide proton transfer imaging sequence is a shimming model which needs to be added to the magnetic resonance amide proton transfer imaging sequence, the homogeneity of a main magnetic field can be improved through the zeroth order symmetric model, water is corrected to be 0ppm, and signals on the left side and the right side of the water are symmetrically distinguished. In one implementation of this embodiment, the image dataset for magnetic resonance amide proton transfer imaging is an image dataset for magnetic resonance amide proton transfer imaging of a head and neck tumor, and of course, in practical applications, the image dataset for magnetic resonance amide proton transfer imaging may be an image dataset for magnetic resonance amide proton transfer imaging of other parts.
And S20, determining the region of interest corresponding to the image data set of the magnetic resonance amide proton transfer imaging.
Specifically, the region of interest is determined for one piece of magnetic resonance amide proton basis image data in an image dataset based on magnetic resonance amide proton transfer imaging, and the region of interest is included in all image data of the magnetic resonance amide protons. After the sensor region is selected, a Z spectrum of the region of interest can be fitted, whether the lowest point appears at 0ppm or not and whether signals at two sides are symmetrically distributed or not is observed by analyzing the Z spectrum, and the nonuniformity of the main magnetic field is better solved only if the lowest point is at 0ppm, which is the requirement of quality control and also the premise of ensuring the accuracy of the APT value. In addition, a wider offset frequency scanning range is used, and the loss of APT signals after Z spectrum offset is avoided or reduced. The region of interest is a tumor or lesion image region in the magnetic resonance amide proton image data, an image region avoiding blood vessels, air and bones, and does not contain normal tissues.
In an implementation manner of this embodiment, the determining a region of interest corresponding to the image data set for magnetic resonance amide proton transfer imaging specifically includes:
normalizing each image data in the image data set of the magnetic resonance amide proton transfer imaging to obtain each image data after normalization;
selecting basic image data from the normalized image data, and determining an interested area corresponding to the basic image data;
and taking the region of interest as the region of interest corresponding to the image data set of the magnetic resonance amide proton transfer imaging.
Specifically, the normalization refers to mapping a pixel value range of a pixel point in the image data to be within a range of 0 to 1. The basic image data is one of the image data sets of magnetic resonance amide proton transfer imaging, wherein the basic image data can be selected randomly or according to the use requirement. In one implementation of this embodiment, the base image data may be image data corresponding to an initial saturation in an image data set for magnetic resonance amide proton transfer imaging, that is, the base image data may be image data located at the top in an image acquisition order in the image data set for magnetic resonance amide proton transfer imaging. After the base image data is acquired, the base image data may be displayed to the user so that the user may select a region of interest on the base image data, where the region of interest may be a tumor or a lesion, which may be of any shape, such as a circle, a square, or other irregular shape, etc.
In an implementation manner of this embodiment, the determining the region of interest corresponding to the basic image data specifically includes:
multiplying the pixel value of each pixel point in the basic image data by 255 to map the pixel value of each pixel point to 0-255 so as to obtain mapped basic image data;
and determining the interested region corresponding to the basic image data based on the mapped basic image data.
Specifically, multiplying the pixel value of each pixel point in the basic image data by 255 refers to multiplying the pixel value of the normalized basic image by 255 so as to map the pixel value of the pixel point in the basic image data to an interval of 0 to 255, then displaying the basic image data by calling a mouse event of an opencv window, and selecting the region of interest in a human-computer interactive mode. After the region of interest is processed in a man-machine interactive mode, the selected region of interest is extracted to form a region of interest map.
S30, determining transfer rate data corresponding to the region of interest based on the image data set of the magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of the magnetic resonance amide proton transfer imaging sequence.
Specifically, the transfer rate data includes one or more of amide proton transfer imaging magnetic transfer rate values of all pixel points in the region of interest, statistical data of the amide proton transfer imaging magnetic transfer rate values, a Z-spectrum of the uniformity of an amide proton transfer imaging magnetic field, a histogram of the amide proton transfer imaging magnetic transfer rate values, a mapping image of amide proton transfer imaging, a mapping image of a main magnetic field, and a mapping image in which the amide proton transfer imaging and an original image are superimposed. For example, as a Z spectrum shown in fig. 2, it is observed whether the lowest point appears at 0ppm and signals on both sides are symmetrically distributed through the Z spectrum to show the uniformity of the main magnetic field; a mapped image of the main magnetic field as shown in fig. 3, by which the homogeneity of the main magnetic field of interest is illustrated; the map image obtained by superimposing the amide proton transfer imaging of the head and neck tumor and the original image as shown in fig. 4 is used for visually observing whether tumor protein exists in the region of interest, and analyzing the proliferation degree of the tumor according to the color depth, wherein the redder or more blue the color is, the higher the absolute value of the APT is, which indicates that the proliferation of the tumor cells is vigorous; the mapping image of amide proton transfer imaging shown in fig. 5 is used for visually observing whether the tumor protein exists in the region of interest and the proliferation degree of the tumor cells; the histogram of amide proton transfer imaging magnetic susceptibility values shown in fig. 6 is used for visual quantification of APT values of the region of interest, especially for comparison before and after tumor treatment, and can visually observe the survival rate of tumor cells.
The statistical data comprises one or more of the average, median, maximum, minimum, standard deviation, kurtosis coefficient, skewness coefficient, and 90% digit of the value. In one implementation of this embodiment, the transfer rate data includes the 90% digit, and since the amide proton magnetic transfer rate values are positive and negative, and most of the values are in a non-normal distribution, and the 90% digit of the region of interest can provide better biological information relative to the average value through 60 cases of amide proton transfer imaging magnetic transfer rate analysis.
In one implementation manner of the embodiment, the determining the transfer rate data corresponding to the region of interest based on the image data set of the magnetic resonance amide proton transfer imaging and the zeroth-order symmetry model of the magnetic resonance amide proton transfer imaging sequence specifically includes:
determining a transfer rate image of the region of interest based on the image dataset of magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of a magnetic resonance amide proton transfer imaging sequence;
denoising the transfer rate image, and determining transfer rate data corresponding to the region of interest based on the denoised transfer rate image.
Specifically, the transfer rate image of the region of interest is an image of the magnetization transfer rate of amide protons acquired from a Z spectrum at a frequency of 3.3 to 3.7ppm (centered at 3.5ppm, spread ± 0.2ppm) with the frequency of water as the center frequency, the frequency of water being set to 0ppm in the Z spectrum. In addition, each pixel point in the transfer rate image is the transfer rate corresponding to each pixel point in the region of interest. That is, after the region of interest is acquired, a Z spectrum of the region of interest is determined based on each image data in the image dataset of the magnetic resonance amide proton transfer imaging, and then an image of the magnetization transfer rate of amide protons is acquired from the Z spectrum at a frequency of 3.3-3.7ppm to obtain a transfer rate image corresponding to the region of interest.
In one implementation of the present implementation, the percentage of asymmetric magnetization transfer is calculated as follows: MTRasym (%) (S- Δ ω -S + Δ ω) ÷ S0 where S- Δ ω represents the signal strength at negative frequency shift and S + Δ ω represents the signal strength at positive frequency shift at the same symmetric position; s0 represents the signal strength without radio frequency saturation. Whereas in the APTw weighted image, the asymmetric magnetization transfer percentage MTRasym (%) is the weight of the conversion APT, APTright, and the amide proton is at +3.5ppm, so that MTRasym calculated at 3.5ppm is the weight of the APT. Therefore, the calculation formula of the transfer rate may be: APTw ═ MTRasym (%) (S- Δ ω -S + Δ ω) ÷ S0, and Δ ω ═ 3.5 ppm. That is, S- Δ ω represents the signal strength at-3.5 ppm frequency offset; s + Δ ω represents the signal strength at +3.5ppm frequency offset. Accordingly, the formula for the APTw% calculation can be rewritten as: APTw% (S-3.5ppm-S +3.5ppm) ÷ S0.
In an implementation manner of this embodiment, the denoising the transfer rate image specifically includes:
respectively calculating the pixel absolute value of the pixel value of each pixel point in the transfer rate image;
and filtering the pixel points with the pixel absolute values smaller than the preset threshold value to obtain the denoised transfer rate image.
Specifically, the preset threshold is preset and is used for filtering pixel points in the transfer rate image, wherein each pixel point in the transfer rate image corresponds to each pixel point in the region of interest, and the pixel value of each pixel point is used for reflecting the transfer rate of the corresponding pixel point. The pixel points with the pixel absolute value smaller than the preset threshold value are filtered, so that pixels with unreasonable amide proton transfer imaging values and poor fitting goodness, heterogeneity and very large or partial (incomplete) saturation in the transfer rate image can be discharged. In one implementation of this embodiment, the preset threshold may be determined based on the average number of the transfer rate images, for example, the preset threshold is half of the average number, or the absolute value of the difference between the preset threshold and the average number is preset. In addition, after the denoised transfer rate image is acquired, the average value, the median, the maximum value, the minimum value, the standard deviation, the kurtosis coefficient, the skewness coefficient and the 90% digit can be calculated based on the denoised transfer rate image, and meanwhile, the transfer rate image can be superposed on an original image, wherein the original image is basic image data for determining the region of interest. In addition, after the transfer rate data is acquired, the transfer rate data can be displayed to a user through a display window so that the transfer rate data is visualized. Of course, when determining the transfer rate image of the region of interest based on the image data set of the magnetic resonance amide proton transfer imaging and the zeroth order symmetry model of the magnetic resonance amide proton transfer imaging sequence, the transfer rate image can be determined by using an existing method, which is not specifically described herein.
The embodiment provides a magnetic resonance amide proton transfer imaging magnetic susceptibility detection method and related equipment, wherein the method comprises the steps of acquiring an image data set for magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of a magnetic resonance amide proton transfer imaging sequence; determining a region of interest corresponding to the image dataset for magnetic resonance amide proton transfer imaging; and determining transfer rate data corresponding to the region of interest based on the image dataset of the magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of the magnetic resonance amide proton transfer imaging sequence. According to the method, the transfer rate data corresponding to the region of interest is obtained and determined by analyzing the image data set of the magnetic resonance amide proton transfer imaging of the head and neck tumor and the zeroth-order symmetric model of the magnetic resonance amide proton transfer imaging sequence, and the richness of the transfer rate data is improved, so that the application value of the magnetic resonance amide proton transfer imaging is improved.
Based on the magnetic resonance amide proton transfer imaging magnetic susceptibility detection method, this embodiment provides a magnetic resonance amide proton transfer imaging magnetic susceptibility detection system, as shown in fig. 7, where the detection system includes:
an obtaining module 100, configured to obtain an image dataset for magnetic resonance amide proton transfer imaging and a zeroth order symmetric model of a magnetic resonance amide proton transfer imaging sequence;
a first determining module 200 for determining a region of interest corresponding to the image data set for magnetic resonance amide proton transfer imaging;
a second determination module 300, configured to determine transfer rate data corresponding to the region of interest based on the image dataset of magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of a magnetic resonance amide proton transfer imaging sequence.
The magnetic resonance amide proton transfer imaging magnetic susceptibility detection system is established based on Python language.
Based on the magnetic resonance amide proton transfer imaging magnetic susceptibility detection method, the present embodiment provides a computer-readable storage medium storing one or more programs, which are executable by one or more processors to implement the steps in the magnetic resonance amide proton transfer imaging magnetic susceptibility detection method according to the above embodiment.
Based on the magnetic resonance amide proton transfer imaging susceptibility detection method, the present application also provides a terminal device, as shown in fig. 8, which includes at least one processor (processor) 20; a display screen 21; and a memory (memory)22, and may further include a communication Interface (Communications Interface)23 and a bus 24. The processor 20, the display 21, the memory 22 and the communication interface 23 can communicate with each other through the bus 24. The display screen 21 is configured to display a user guidance interface preset in the initial setting mode. The communication interface 23 may transmit information. The processor 20 may call logic instructions in the memory 22 to perform the methods in the embodiments described above.
Furthermore, the logic instructions in the memory 22 may be implemented in software functional units and stored in a computer readable storage medium when sold or used as a stand-alone product.
The memory 22, which is a computer-readable storage medium, may be configured to store a software program, a computer-executable program, such as program instructions or modules corresponding to the methods in the embodiments of the present disclosure. The processor 20 executes the functional application and data processing, i.e. implements the method in the above-described embodiments, by executing the software program, instructions or modules stored in the memory 22.
The memory 22 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal device, and the like. Further, the memory 22 may include a high speed random access memory and may also include a non-volatile memory. For example, a variety of media that can store program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk, may also be transient storage media.
In addition, the specific processes loaded and executed by the storage medium and the instruction processors in the mobile terminal are described in detail in the method, and are not stated herein.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (9)
1. A magnetic resonance amide proton transfer imaging magnetic susceptibility detection method, comprising:
acquiring an image data set of magnetic resonance amide proton transfer imaging and a zeroth order symmetric model of a magnetic resonance amide proton transfer imaging sequence;
determining a region of interest corresponding to the image dataset for magnetic resonance amide proton transfer imaging;
determining transfer rate data corresponding to the region of interest based on the image dataset of the magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of a magnetic resonance amide proton transfer imaging sequence, wherein the transfer rate data comprises amide proton transfer imaging magnetic transfer rate values of all pixel points in the region of interest, statistical data of the amide proton transfer imaging magnetic transfer rate values, a Z spectrogram of amide proton transfer imaging magnetic field uniformity, a histogram of the amide proton transfer imaging magnetic transfer rate values, a mapping image of amide proton transfer imaging, a mapping image of a main magnetic field and a mapping image of superposition of the amide proton transfer imaging and an original image; wherein the statistical data comprises the average value, median, maximum value, minimum value, standard deviation, kurtosis coefficient, skewness coefficient and the 90% digit of the numerical value.
2. The method for detecting the magnetization transfer rate in mri according to claim 1, wherein the determining the region of interest corresponding to the image dataset of mri specifically comprises:
normalizing each image data in the image data set of the magnetic resonance amide proton transfer imaging to obtain each image data after normalization;
selecting basic image data from the normalized image data, and determining an interested area corresponding to the basic image data;
and taking the region of interest as the region of interest corresponding to the image data set of the magnetic resonance amide proton transfer imaging.
3. The magnetic resonance amide proton transfer imaging magnetic susceptibility detection method according to claim 2, wherein the base image data is normalized image data positioned at the forefront in the imaging order among the normalized image data; the determining of the region of interest corresponding to the basic image data specifically includes:
multiplying the pixel value of each pixel point in the basic image data by 255 to map the pixel value of each pixel point to 0-255 so as to obtain mapped basic image data;
and determining the interested region corresponding to the basic image data based on the mapped basic image data.
4. The magnetic resonance amide proton transfer imaging susceptibility testing method as claimed in claim 1, wherein the determining the transfer rate data corresponding to the region of interest based on the image dataset of the magnetic resonance amide proton transfer imaging and the zeroth order symmetry model of the magnetic resonance amide proton transfer imaging sequence specifically comprises:
determining a transfer rate image of the region of interest based on the image dataset of the magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of a magnetic resonance amide proton transfer imaging sequence, wherein the transfer rate image is a magnetization transfer rate image of amide protons acquired from a Z frequency spectrum at a frequency of 3.3-3.7ppm, with the frequency of water as a center frequency, the frequency of water being set to 0ppm in the Z frequency spectrum;
denoising the transfer rate image, and determining transfer rate data corresponding to the region of interest based on the denoised transfer rate image.
5. The magnetic resonance amide proton transfer imaging magnetic susceptibility detection method as claimed in claim 4, wherein the denoising of the transfer rate image specifically comprises:
respectively calculating the pixel absolute value of the pixel value of each pixel point in the transfer rate image;
and filtering the pixel points with the pixel absolute values smaller than the preset threshold value to obtain the denoised transfer rate image.
6. A magnetic resonance amide proton transfer imaging magnetic susceptibility testing system, said testing system comprising:
the acquisition module is used for acquiring an image data set of magnetic resonance amide proton transfer imaging and a zeroth order symmetric model of a magnetic resonance amide proton transfer imaging sequence;
a first determination module for determining a region of interest corresponding to the image dataset for magnetic resonance amide proton transfer imaging;
a second determining module, configured to determine transfer rate data corresponding to the region of interest based on the image data set of the magnetic resonance amide proton transfer imaging and a zeroth order symmetry model of a magnetic resonance amide proton transfer imaging sequence; the transfer rate data comprises amide proton transfer imaging magnetic transfer rate values of all pixel points in the region of interest, statistical data of the amide proton transfer imaging magnetic transfer rate values, a Z spectrogram of the uniformity of an amide proton transfer imaging magnetic field, a histogram of the amide proton transfer imaging magnetic transfer rate values, a mapping image of amide proton transfer imaging, a mapping image of a main magnetic field and a mapping image of superposition of the amide proton transfer imaging and an original image; wherein the statistical data comprises the average value, median, maximum value, minimum value, standard deviation, kurtosis coefficient, skewness coefficient and the 90% digit of the numerical value.
7. The magnetic resonance amide proton transfer imaging magnetic susceptibility testing system according to claim 6, wherein the testing system is built based on Python language.
8. A computer readable storage medium, storing one or more programs which are executable by one or more processors to perform the steps of the method for magnetic resonance amide proton transfer imaging susceptibility detection according to any of claims 1-5.
9. A terminal device, comprising: the device comprises a processor, a memory and a communication bus, wherein the memory is stored with a computer readable program which can be executed by the processor;
the communication bus realizes connection communication between the processor and the memory;
the processor, when executing the computer readable program, implements the steps in the magnetic resonance amide proton transfer imaging susceptibility detection method of any one of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110969450.1A CN113674248B (en) | 2021-08-23 | 2021-08-23 | Magnetic resonance amide proton transfer imaging magnetic susceptibility detection method and related equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110969450.1A CN113674248B (en) | 2021-08-23 | 2021-08-23 | Magnetic resonance amide proton transfer imaging magnetic susceptibility detection method and related equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113674248A CN113674248A (en) | 2021-11-19 |
| CN113674248B true CN113674248B (en) | 2022-08-12 |
Family
ID=78545333
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110969450.1A Active CN113674248B (en) | 2021-08-23 | 2021-08-23 | Magnetic resonance amide proton transfer imaging magnetic susceptibility detection method and related equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113674248B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102510282A (en) * | 2011-10-25 | 2012-06-20 | 中国科学院空间科学与应用研究中心 | Time-resolved single-photon counting two-dimensional imaging system and method |
| CN104155623A (en) * | 2013-04-17 | 2014-11-19 | 西门子公司 | Methods and systems for automatically determining magnetic field inversion time of a tissue species |
| CN104204839A (en) * | 2012-04-03 | 2014-12-10 | 皇家飞利浦有限公司 | MR imaging using APT contrast enhancement and multi-echo time sampling |
| CN104714201A (en) * | 2015-02-09 | 2015-06-17 | 浙江大学 | Method for effectively correcting main magnetic field of magnetic resonance imaging system |
| CN105551026A (en) * | 2015-12-08 | 2016-05-04 | 浙江工业大学 | Brain feature extraction method based on diffusion tensor imaging |
| CN105825496A (en) * | 2015-01-22 | 2016-08-03 | 西门子公司 | Method for improving image quality of magnetic resonance image dataset, computing device, and computer program |
Family Cites Families (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2015146514A (en) * | 2013-03-29 | 2017-05-04 | Конинклейке Филипс Н.В. | VISUALIZATION USING THE PROPERTY TRANSFER OF AMID (ART) AND TOMOGRAPHY BASED ON ELECTRIC PROPERTIES (ERT) IN ONE MAGNETIC RESONANCE DATA COLLECTION |
| CN103218788B (en) * | 2013-04-24 | 2015-12-02 | 南方医科大学 | A kind of measuring method of liver magnetic resonance R2* parameter |
| CN104856677B (en) * | 2015-06-14 | 2017-10-10 | 西安交通大学医学院第一附属医院 | The MR imaging method of magnetization transfer joint level selection inversion recovery prepulsing |
| CN106772165B (en) * | 2016-12-30 | 2019-04-05 | 深圳先进技术研究院 | The determination method and device of amide proton transfer effect |
| US10726552B2 (en) * | 2017-03-20 | 2020-07-28 | The General Hospital Corporation | Quantification of magnetic resonance data by adaptive fitting of downsampled images |
| US10775462B2 (en) * | 2017-07-05 | 2020-09-15 | The General Hospital Corporation | System and method for direct saturation-corrected chemical exchange saturation transfer (DISC-CEST) |
| EP3511729A1 (en) * | 2018-01-11 | 2019-07-17 | Koninklijke Philips N.V. | Magnetization transfer based metric for chemical exchange saturation transfer magnetic resonance imaging |
| CN110118950B (en) * | 2019-06-19 | 2021-01-01 | 华东师范大学 | Phase correction method for bipolar readout gradient in abdominal quantitative magnetic susceptibility imaging |
| CN111583204B (en) * | 2020-04-27 | 2022-10-14 | 天津大学 | Organ positioning method of two-dimensional sequence magnetic resonance image based on network model |
| CN112598619A (en) * | 2020-11-23 | 2021-04-02 | 西安科锐盛创新科技有限公司 | Method for establishing intracranial vascular simulation three-dimensional narrowing model based on transfer learning |
-
2021
- 2021-08-23 CN CN202110969450.1A patent/CN113674248B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102510282A (en) * | 2011-10-25 | 2012-06-20 | 中国科学院空间科学与应用研究中心 | Time-resolved single-photon counting two-dimensional imaging system and method |
| CN104204839A (en) * | 2012-04-03 | 2014-12-10 | 皇家飞利浦有限公司 | MR imaging using APT contrast enhancement and multi-echo time sampling |
| CN104155623A (en) * | 2013-04-17 | 2014-11-19 | 西门子公司 | Methods and systems for automatically determining magnetic field inversion time of a tissue species |
| CN105825496A (en) * | 2015-01-22 | 2016-08-03 | 西门子公司 | Method for improving image quality of magnetic resonance image dataset, computing device, and computer program |
| CN104714201A (en) * | 2015-02-09 | 2015-06-17 | 浙江大学 | Method for effectively correcting main magnetic field of magnetic resonance imaging system |
| CN105551026A (en) * | 2015-12-08 | 2016-05-04 | 浙江工业大学 | Brain feature extraction method based on diffusion tensor imaging |
Non-Patent Citations (2)
| Title |
|---|
| Amide Proton Transfer Imaging of the Human Brain;Jinyuan Zhou;《Methods Mol Biol》;20111231;第227-237页 * |
| APT-Weighted MRI: Techniques, Current Neuro Applications, and Challenging Issues;Jinyuan Zhou 等;《J Magn Reson Imagin》;20190831;第50卷(第2期);第347-364页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113674248A (en) | 2021-11-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8600135B2 (en) | System and method for automatically generating sample points from a series of medical images and identifying a significant region | |
| EP2357612B1 (en) | Method for quantifying and imaging features of a tumor | |
| CN108171738B (en) | Multi-modal medical image registration method based on brain function template | |
| TWI719587B (en) | Pre-processing method and storage device for quantitative analysis of fundus image | |
| MXPA06002304A (en) | Counting biological agents on biological growth plates. | |
| US11848098B2 (en) | Identifying anomalous brain data | |
| US11257301B2 (en) | Image analysis apparatus, image analysis method, and image analysis program | |
| CN112200802A (en) | Training method of image detection model, related device, equipment and storage medium | |
| US9916658B2 (en) | Disease analysis apparatus, control method, and program | |
| CN110910335B (en) | Image processing method, image processing device and computer readable storage medium | |
| CN108765447B (en) | Image segmentation method, image segmentation device and electronic equipment | |
| CN109949288A (en) | Tumor type determines system, method and storage medium | |
| US7689265B2 (en) | System and method for the joint evaluation of multi phase MR marrow images | |
| CN114419181A (en) | CTA image reconstruction method and device, display method and device | |
| EP3933759A1 (en) | Image processing method, apparatus and system, and electronic device and storage medium | |
| CN110415228B (en) | Nerve fiber tracking method, magnetic resonance system, and storage medium | |
| CN112750099A (en) | Follicle measurement method, ultrasound apparatus, and computer-readable storage medium | |
| CN113674248B (en) | Magnetic resonance amide proton transfer imaging magnetic susceptibility detection method and related equipment | |
| JP7337693B2 (en) | Cortical malformation identification | |
| WO2013037702A1 (en) | Method and a system for medical imaging | |
| CN113538352B (en) | Method and device for acquiring brain stroke organization window evaluation value and storage medium | |
| CN109767468B (en) | Visceral volume detection method and device | |
| US20130322713A1 (en) | Color map design method for assessment of the deviation from established normal population statistics and its application to quantitative medical images | |
| JP7265805B2 (en) | Image analysis method, image analysis device, image analysis system, control program, recording medium | |
| CN109350062B (en) | Medical information acquisition method, medical information acquisition device and non-volatile computer storage medium |
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 |