A method and apparatus for cerebral perfusion imaging

Abstract

The present disclosure relates to a method and device for brain perfusion imaging. The method comprises: controlling each antenna unit in an antenna array to emit electromagnetic waves in sequence; continuously collecting spatial scattered electromagnetic field data at each antenna unit in the antenna array, and taking the collected spatial scattered electromagnetic field data as a frame of data after each antenna unit emits an electromagnetic wave; starting from an initial time, extracting a corresponding perfusion component from each frame of data; calculating a change in the perfusion component and a change in an electrical parameter of the brain relative to the initial time according to the corresponding perfusion component extracted from each frame of data; and performing imaging according to the calculated change in the electrical parameter of the brain. The method can realize rapid positioning screening and real-time monitoring of the blood vessels in the brain of a patient, win treatment time for the patient, improve treatment effect, and does not require the use of contrast agents, and does not cause side effects to the patient's body.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of microwave imaging, in particular to a cerebral perfusion imaging method and device. BACKGROUND

[0002] Microwave imaging refers to an imaging method using microwaves as information carriers. Microwave imaging has the advantages of non-invasiveness, non-ionizing radiation, and large detection depth. The measurement equipment is convenient and has low requirements on the measurement environment, and is an ideal imaging method suitable for early screening and bedside dynamic monitoring of stroke.

[0003] The microwave imaging method currently widely studied is static or quasi-static imaging. It reconstructs the mean value or change distribution of the electrical parameters of brain tissue over a long period of time by measuring the carrier frequency component of the data. However, static or quasi-static imaging cannot reflect the transient changes in electrical parameters caused by cerebral blood perfusion in real time. Static imaging directly uses the measured data to reconstruct the absolute value of the electrical parameters of the human brain, and infers the brain tissue condition through the spatial distribution thereof. Quasi-static imaging uses the long-term change of the measured data to reconstruct the change of the electrical parameters of the human brain, and infers the abnormal change of the brain tissue through the spatial distribution of the change. The static imaging method has a long calculation time, and the quasi-static imaging has a long data recording time. Both of them have low time resolution of brain tissue electrical parameters, and it is difficult to perform real-time imaging of brain tissue and blood.

[0004] The current method of microwave imaging of brain blood vessels cannot reflect the transient changes in electrical parameters caused by cerebral blood perfusion in real time, cannot timely respond to the rapid screening of sudden and rapidly progressing cerebral ischemic or cerebral hemorrhagic diseases in the early stage of the disease, cannot respond to the rapid screening of sudden and rapidly progressing cerebral ischemic or cerebral hemorrhagic diseases in the early stage of the disease, the emergency scene of brain blood vessel obstruction or cerebral hemorrhage, and cannot quickly and timely obtain the condition of the brain blood vessels of the patient, resulting in delayed treatment opportunity. SUMMARY

[0005] Therefore, the present disclosure aims to provide a cerebral perfusion imaging method and device to solve the problem that the current method of microwave imaging of brain blood vessels cannot reflect the transient changes in electrical parameters caused by cerebral blood perfusion in real time, cannot timely respond to the rapid screening of sudden and rapidly progressing cerebral ischemic or cerebral hemorrhagic diseases in the early stage of the disease, and cannot quickly and timely obtain the condition of the brain blood vessels of the patient in the emergency scene of brain blood vessel obstruction or cerebral hemorrhage, resulting in delayed treatment opportunity.

[0006] To achieve the above object, the technical scheme of the present disclosure is as follows:

[0007] According to a first aspect of the embodiment of the present disclosure, a cerebral perfusion imaging method is provided, comprising:

[0008] S1: Controls each antenna element in the antenna array to transmit electromagnetic waves sequentially.

[0009] S2: Continuously collect spatial scattered electromagnetic field data at each antenna element in the antenna array. After each antenna element emits an electromagnetic wave once, the collected spatial scattered electromagnetic field data is taken as a frame of data. The frequency of collecting a frame of data is greater than twice the heart rate.

[0010] S3: Starting from the initial moment, extract the corresponding perfusion component from each frame of continuously acquired data;

[0011] S4: Based on the corresponding perfusion component extracted from each frame of data, calculate the change in the perfusion component relative to the initial time, and calculate the change in the brain electrical parameters based on the change in the perfusion component.

[0012] S5: Based on the changes in the brain's electrical parameters obtained through calculation, imaging is performed.

[0013] According to a first aspect of the present disclosure, in a first possible implementation of the first aspect, after each antenna element has emitted an electromagnetic wave once, the collected spatially scattered electromagnetic field data is used as a frame of data, including:

[0014] S21: Collect the spatial scattered electromagnetic field data at the other antenna elements when each antenna element in the antenna array emits electromagnetic waves in sequence;

[0015] S22: After each antenna element in the antenna array has emitted an electromagnetic wave once in sequence, all the spatial scattered electromagnetic field data collected in the antenna array are taken as a frame of data.

[0016] According to a first aspect of the present disclosure, in a second possible implementation of the first aspect, extracting the corresponding perfusion component from each continuously acquired frame of data includes:

[0017] S31: Filter the data frame acquired each time to extract the low-frequency component data;

[0018] S32: Extract data that is consistent with the heart rate from the low-frequency component data, and use it as the perfusion component corresponding to the frame of data.

[0019] According to a first aspect of the present disclosure, in a third possible implementation of the first aspect, calculating the change in the perfusion component relative to the initial time includes:

[0020] S41: Take the injection component corresponding to the first frame of data at the initial moment as the reference point injection component;

[0021] S42: subtracting the perfusion component corresponding to each time moment after the initial time moment from the reference point perfusion component to obtain a differential data amount; the differential data amount is the change amount of the perfusion component at the time moment relative to the initial time moment;

[0022] S43: calculating a differential data amount sensitivity matrix according to the differential data amount;

[0023] S44: calculating the brain electrical parameter change amount according to the differential data amount sensitivity matrix.

[0024] According to a first aspect of an embodiment of the present disclosure, in a fourth possible implementation manner of the first aspect, the brain electrical parameter change amount is a dielectric constant change amount of a brain blood vessel.

[0025] According to a second aspect of an embodiment of the present disclosure, a device for brain perfusion imaging is provided, which is used to implement the brain perfusion imaging method provided in the first aspect of the present disclosure, and includes:

[0026] A transmitting module is configured to control each antenna unit in an antenna array to sequentially transmit electromagnetic waves in turn;

[0027] A collecting module is configured to continuously collect spatial scattered electromagnetic field data at each antenna unit in the antenna array, and after each antenna unit transmits an electromagnetic wave, the collected spatial scattered electromagnetic field data is taken as one frame of data; the frequency of collecting one frame of data is greater than 2 times the heart rate;

[0028] A data processing module is configured to extract a corresponding perfusion component from each frame of data collected continuously, starting from an initial time moment;

[0029] A calculating module is configured to calculate a change amount of a perfusion component relative to the initial time moment according to the corresponding perfusion component extracted from each frame of data, and calculate a brain electrical parameter change amount according to the change amount of the perfusion component;

[0030] An imaging module is configured to perform imaging according to the brain electrical parameter change amount obtained by calculation.

[0031] According to the second aspect of the present disclosure, in a first possible implementation manner of the second aspect, the collecting module includes:

[0032] A data collecting sub-module is configured to sequentially collect spatial scattered electromagnetic field data at the remaining antenna units when each antenna unit in the antenna array transmits an electromagnetic wave;

[0033] The first output sub-module is configured to output the collected spatial scattering electromagnetic field data of all the antenna units in the antenna array as a frame of data after each antenna unit in the antenna array transmits an electromagnetic wave once.

[0034] According to a second aspect of the embodiments of the present disclosure, in a second possible implementation manner of the second aspect, the data processing module comprises:

[0035] The filtering sub-module is configured to filter the frame of data collected each time to extract low-frequency component data therefrom;

[0036] The second output sub-module is configured to extract data consistent with the heart rate from the low-frequency component data as a perfusion component corresponding to the frame of data.

[0037] According to a second aspect of the embodiments of the present disclosure, in a third possible implementation manner of the second aspect, the calculation module comprises:

[0038] The parameter reconstruction sub-module is configured to take the perfusion component corresponding to the frame of data at the initial time as a reference point perfusion component, and take the difference between the perfusion component corresponding to each time after the initial time and the reference point perfusion component to obtain a differential data amount; the differential data amount is the change amount of the perfusion component at the time relative to the initial time; calculate a differential data amount sensitivity matrix according to the differential data amount; and calculate the brain electrical parameter change amount according to the differential data amount sensitivity matrix.

[0039] The third output sub-module is configured to output the calculated brain electrical parameter change amount.

[0040] According to a second aspect of the embodiments of the present disclosure, in a fourth possible implementation manner of the second aspect, further comprising a control module configured to:

[0041] Control each antenna unit in the antenna array to transmit and receive spatial electromagnetic field data in turn; the frequency at which each antenna unit transmits an electromagnetic wave once is greater than 2 times the heart rate;

[0042] Control the acquisition module to continuously acquire the frame of data; the frequency at which the frame of data is acquired is consistent with the frequency at which each antenna unit transmits an electromagnetic wave once.

[0043] Compared with the prior art, the technical solutions provided by the embodiments of the present disclosure can have the following beneficial effects:

[0044] In the embodiments of this disclosure, firstly, brain microwave electromagnetic field data is collected to extract the perfusion component of the human brain's blood vessels. Then, the changes in brain electrical parameters are calculated using the perfusion component, and the changes in brain electrical parameters are dynamically imaged in terms of temporal and spatial distribution, achieving the purpose of reflecting the state of cerebral vascular occlusion in real time and accurately. In critical scenarios such as sudden cerebral vascular occlusion in patients with stroke or ischemic stroke, this method can quickly screen and locate the patient's brain blood vessels, buying time for treatment. In scenarios of continuous monitoring of cerebral blood revascularization after stroke treatment, it can monitor the treatment recovery status in real time, providing timely feedback to improve treatment effectiveness. Furthermore, this method does not require the use of contrast agents and will not cause side effects on the patient's body. Attached Figure Description

[0045] The accompanying drawings, which form part of this disclosure, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure. In the drawings:

[0046] Figure 1 This is a flowchart illustrating a brain perfusion imaging method according to an embodiment of the present disclosure;

[0047] Figure 2 This is a three-dimensional static model of the human brain based on three-dimensional coordinate axes, as shown in an embodiment of this disclosure.

[0048] Figure 3 This is a diagram showing the distribution of the relative permittivity of cerebral blood vessels when cerebral blood perfusion is at its weakest, according to an embodiment of this disclosure.

[0049] Figure 4a This is an image showing the change in dielectric constant caused by cerebral blood perfusion under normal conditions, according to an embodiment of this disclosure.

[0050] Figure 4b An imaging diagram showing the change in dielectric constant caused by blood perfusion to the brain when a blood vessel in the brain is blocked, according to an embodiment of this disclosure;

[0051] Figure 5a This is a dielectric constant distribution diagram of cerebral blood vessels under normal cerebral blood perfusion conditions, as shown in an embodiment of this disclosure.

[0052] Figure 5b This is a dielectric constant distribution diagram of cerebral blood vessels when cerebral blood vessels are blocked, according to an embodiment of this disclosure;

[0053] Figure 6 This is a block diagram of a brain perfusion imaging apparatus according to an embodiment of the present disclosure. Detailed Implementation

[0054] With reference to the drawings, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below. Obviously, the described embodiments are only some of the embodiments of the present disclosure, rather than all the embodiments of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts should fall within the scope of the present disclosure.

[0055] It should be understood that every technical feature mentioned in the specification refers to a specific feature related to the embodiments, which is included in at least one embodiment of the present disclosure. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner.

[0056] In various embodiments of the present disclosure, it should be understood that the size of the serial number of each process does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.

[0057] The exemplary embodiments will be described in detail herein with reference to the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present disclosure. Instead, they are merely examples of apparatuses and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0058] It should be noted that the embodiments in the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0059] The electrical parameters (dielectric constant and conductivity) of brain tissue are different from those of blood. Hemorrhagic or ischemic injury of the brain can cause changes in the spatial distribution of the electrical parameters of the brain, and further affect the spatial electromagnetic field distribution and electromagnetic wave propagation. By using microwave detection imaging technology, the electrical parameter distribution of brain blood vessels can be reconstructed from the electromagnetic data measured by the sensor, and the diagnosis of abnormal lesions of brain tissue can be realized.

[0060] The spatial distribution of cerebral blood perfusion is dynamically imaged using electromagnetic waves in the microwave frequency band, which can be used to assist in rapid identification of ischemic stroke, continuous monitoring of blood reconstitution after stroke treatment, and other situations in emergency scenarios where CT or nuclear magnetic resonance cannot meet the demand. Since the low-frequency component of the brain microwave data contains cerebral blood perfusion information, the frequency is the same as the heart rate, and therefore, imaging of this component can reconstruct the temporal and spatial distribution of the brain electrical parameters, where the temporal variation reflects the heart rate, and the spatial distribution is consistent with the brain blood vessel distribution. The change in the electrical parameters of the brain blood vessel region can reflect the occlusion of the brain blood vessel region in a timely manner, and therefore, by monitoring the change in the electrical parameters of the brain blood vessel region, the brain blood vessel region with pathological changes can be quickly located.

[0061] Taking a carrier frequency of 1 GHz as an example, the wavelength of electromagnetic waves in the brain tissue is about 3.5-5 cm, and according to electromagnetic detection theory, the resolution of far-field electromagnetic detection is half a wavelength; considering that the brain microwave detection device works in the near-field region, the imaging has near-field super-resolution characteristics, and the imaging resolution is expected to reach 2-3 cm. This resolution can visualize the blood perfusion abnormalities caused by brain blood vessel stenosis or occlusion, which is beneficial to timely response before brain tissue necrosis.

[0062] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0063] Figure 1 is a flowchart of a cerebral perfusion imaging method provided by an embodiment of the present disclosure, in step S1, each antenna element in the antenna array is controlled to emit electromagnetic waves in sequence;

[0064] In step S2, the spatial scattered electromagnetic field data at each antenna element in the antenna array is continuously collected, and after the electromagnetic wave is emitted by each antenna element, the collected spatial scattered electromagnetic field data is taken as a frame of data; the frequency of collecting a frame of data is greater than 2 times the heart rate;

[0065] In step S3, starting from an initial time, the corresponding perfusion component is extracted from each frame of data collected continuously;

[0066] In step S4, the change in the perfusion component relative to the initial time is calculated according to the corresponding perfusion component extracted from each frame of data, and the change in the brain electrical parameters is calculated according to the change in the perfusion component;

[0067] In step S5, the brain electrical parameter change is imaged according to the brain electrical parameter change obtained by calculation.

[0068] The antenna array in the present disclosure can be a hemispherical or cylindrical antenna array arranged around the human head. The antenna array in the present disclosure can include a plurality of antenna units, which can be uniformly distributed or arranged according to certain requirements. The antenna units can optionally include multiple polarization directions, multiple electrical sizes, and multiple array arrangement modes. For example, a horizontally polarized dipole antenna can be used and uniformly distributed around the human head in a hemispherical shape.

[0069] In the present disclosure, the antenna units in the antenna array transmit and collect microwave electromagnetic field data. The microwave electromagnetic field data collected by the antenna units are transmitted to the data processing module, which processes the collected microwave electromagnetic field data, such as filtering, amplifying, mixing, modulating, etc.

[0070] In step S1, the antenna units in the antenna array are controlled to emit electromagnetic waves in sequence. The control module controls the emission and reception parameters of the electromagnetic waves. The signal source generates electromagnetic wave signals of a certain frequency, which are then emitted by the antenna array. The control module sets the emission frequency of the electromagnetic waves and controls the antenna units in the antenna array to emit the electromagnetic waves generated by the signal source. The control module controls the emission sequence of the antenna units in the antenna array, and only one antenna unit emits electromagnetic waves at a time. In a complete electromagnetic wave emission process, each antenna unit in the antenna array emits electromagnetic waves once. In the brain perfusion imaging process of the present disclosure, the frequency of the electromagnetic waves generated by the signal source is consistent with the frequency of the electromagnetic waves emitted by the antenna units and the frequency of collecting a frame of data, which is greater than 2 times the heart rate.

[0071] According to the Nyquist sampling theorem, when the sampling frequency is less than 2 times the highest frequency of the spectrum, the spectrum of the data is aliasing. When the sampling frequency is greater than 2 times the highest frequency of the spectrum, the spectrum of the data is not aliasing. Therefore, in the present disclosure, a frequency greater than 2 times the heart rate is used to sample the data.

[0072] In step S2, the spatial scattered electromagnetic field data of the antenna units in the antenna array are continuously collected. When an electromagnetic wave is emitted by a certain antenna unit in the antenna array, the remaining antenna units in the antenna array receive the spatial scattered electromagnetic field data within the range of the antenna array and transmit them to the collection module. The collection module records the spatial scattered electromagnetic field data received by the multiple antenna units. After all the antenna units in the antenna array have emitted electromagnetic waves once, the antenna array completes a complete electromagnetic wave emission process. At this time, the collection module obtains a complete set of antenna array spatial scattered electromagnetic field data. The collection module collects all the spatial scattered electromagnetic field data received by the antenna units during this process as a frame of data, and completes a collection.

[0073] Optionally, the acquisition module in the present disclosure has multiple data acquisition forms to choose from, such as single-transmit multi-receive, multi-transmit multi-receive, and multi-transmit single-receive. The acquisition module can be built based on a switch array and a vector network analyzer.

[0074] In step S3, an initial time t0 is set as the initial time of the brain perfusion imaging. Before the initial time t0, the acquisition module has already acquired at least one frame of data. The control module controls the antenna array to continuously transmit electromagnetic waves at a certain frequency. Correspondingly, the acquisition module continuously acquires the scattered electromagnetic field data sent by the antenna elements in the antenna array at different times, i.e., a complete frame of data at different times. For example, at the initial time t0, a frame of data at the time t0 is acquired. At each time after the initial time t0, a frame of data acquired at the corresponding time is recorded. For example, at the time t1 after the initial time t0, a frame of data at the time t1 is acquired. At the time t2 after the time t1, a frame of data at the time t2 is acquired. In the present disclosure, the acquisition module continuously acquires multiple frames of data, and sets a frame of data acquired at a certain time as the reference point data. For example, the time t0 is set as the reference point, and the frame of data acquired at the time t0 is set as the reference point data.

[0075] The data processing module processes the acquired multiple frames of data, and extracts the corresponding perfusion component from each frame of data. In the present disclosure, the perfusion component exists in the low-frequency component of the brain microwave data, and the frequency of the perfusion component is the same as the heart beat frequency. Therefore, in the present disclosure, a corresponding filter can be designed to filter each frame of data acquired, so as to extract the data consistent with the heart beat frequency from the low-frequency component, and obtain the perfusion component corresponding to the frame of data. The frequency band of the perfusion component is different from that of the frame of data, and the perfusion component corresponds to the frame of data one-to-one. For example, the perfusion component extracted from the reference point data acquired at the time t0 is the reference point perfusion component. In the embodiment of the present disclosure, a low-pass filter can be designed, with the highest cutoff frequency being 120 Hz, to filter out the 0-120 Hz component from the received microwave signal as the perfusion component.

[0076] In step S4, the difference between the perfusion component extracted from each frame of data collected and the perfusion component extracted from the reference point data is obtained, that is, the difference data quantity, that is, the change quantity of the perfusion component relative to the reference point. Wherein, the scattered electromagnetic field data in the antenna array range is collected for multiple times, and the perfusion components corresponding to multiple time points are extracted. The perfusion components at all time points except the reference point are subtracted from the perfusion component at the reference point time, and multiple difference data quantities are obtained. For example, the perfusion component corresponding to t1 is subtracted from the reference point perfusion component at t0, and the difference data quantity of t1 relative to t0 is obtained.

[0077] Then, according to the change quantity of the perfusion component, the change quantity of the brain electrical parameter is calculated. In the embodiment of the present disclosure, the obtained difference data quantity is used to reconstruct the change quantity of the brain dielectric constant.

[0078] In the embodiment of the present disclosure, the average dielectric constant model of 25 human brains is selected as the calculation background, and the following formula is used

[0079]

[0080] E can be obtained i and In the above formula, r0 represents the position of any receiving antenna in the antenna array, j is an imaginary number (j*j=-1), ω is an angular frequency, ∈0 is the dielectric constant of free space, is the vector electric field at each point in the entire region D when the transmitting antenna is used as a source, ∈ * is the complex dielectric constant at each point in the space, E i is the electric field three-dimensional vector at each point in the entire region when the transmitting antenna is used as a source, is the electric field three-dimensional vector at each point in the entire region when the electric dipole source is placed at the receiving antenna unit (referred to as the accompanying field).

[0081] According to the electromagnetic field E obtained above, the sensitivity matrix J is obtained, and each row element of the sensitivity matrix J is the derivative of the electromagnetic field E measured by the receiving antenna at r0 with respect to the dielectric constant.

[0082] The data processing module obtains the corresponding perfusion components d0, d1 and d2 at t0, t1 and t2 respectively, and according to the accompanying equation method, the imaging target function with t0 as the reference point is obtained:

[0083]

[0084] Wherein, d is the perfusion component at the current time (for example: d1 or d2), m is the change quantity of the brain dielectric constant to be reconstructed in the present disclosure, λ i (i=x, y, z) is a regularization parameter, For the difference operator along each coordinate axis, ||·|| represents the L2 norm. On this basis, the objective function L(m) is minimized using an optimization algorithm, which in this example is the Gauss-Newton method, to obtain the following linear equations:

[0085] Am = b

[0086] wherein,

[0087]

[0088] b = J H (d-d0)

[0089] In the above formula, H is the conjugate transpose, and T is the transpose. According to the above linear equations, the change in the dielectric constant of the perfusion component at the reference point at the current time can be obtained.

[0090] Optionally, in the process of calculating the change in the brain electrical parameter by the change in the perfusion component, the background dielectric constant required for the calculation contains various distributions, for example, the background dielectric constant can be selected to be a uniform space, a head model containing only the skull, or an average human brain model based on big data. The imaging results obtained based on different backgrounds only have slight differences in accuracy.

[0091] Optionally, in the process of calculating the change in the brain electrical parameter by the change in the perfusion component, the sensitivity matrix has multiple calculation methods, such as the finite difference method and the adjoint equation method. In theory, different calculation methods can obtain the same or similar results.

[0092] Optionally, in the process of calculating the change in the brain electrical parameter by the change in the perfusion component, the difference imaging objective function contains multiple regularization forms, such as 1-norm regularization, 2-norm regularization, and total variation regularization.

[0093] Optionally, in the process of calculating the change in the brain electrical parameter by the change in the perfusion component, the algorithm for optimizing the difference imaging objective function contains various forms, such as the Gauss-Newton method, the ADMM algorithm, the FISTA algorithm, the quasi-Newton method, and the conjugate gradient method.

[0094] Step S5: Imaging is performed according to the change in the brain electrical parameter calculated in step S4. In this embodiment, the change in the dielectric constant of the brain blood vessels is calculated according to the change in the brain perfusion component in a short time, and the spatial distribution of the change in the dielectric constant of the brain blood vessels is imaged to present the spatiotemporal distribution of the dielectric constant of the brain blood vessels, wherein the temporal distribution reflects the heart cycle, and the spatial distribution is consistent with the distribution of the brain blood vessels.

[0095] In this embodiment, the imaging process by the change in the dielectric constant is as follows.

[0096] A three-dimensional static model of a human brain based on three-dimensional coordinate axes is established as shown in Figure 2 , wherein the light-colored part represents the skull and the internal brain tissue, and the dark-colored part represents the main blood vessels (not including capillaries) of the head. In a normal case, blood perfuses into the brain blood vessels with the heartbeat, causing a periodic change in the dielectric constant of the brain blood vessels. The distribution of the relative dielectric constant of the brain blood vessels when the blood perfusion is weakest is taken as the observation basis for imaging in this embodiment. In this embodiment, the three-dimensional static model of the human brain as shown in Figure 2 is sliced from top to bottom along the Z axis, and then the imaging of the relevant data of the sliced cross section is performed to obtain Figure 3 , Figure 4a , Figure 4b , Figure 5a , Figure 5b .

[0097] As shown in Figure 3 , it is the distribution of the relative dielectric constant of the brain blood vessels when the blood perfusion is weakest. The dielectric constant values of the blood vessels distributed in different regions of the brain are used for imaging. In a normal case, blood perfuses into the brain blood vessels with the heartbeat of the heart, causing changes in the electrical parameters of the blood vessels at different positions in the brain. The change amounts of the electrical parameters of the blood vessels at different positions are different, as shown in Figure 4a . When a patient has a brain blood vessel occlusion, such as a sudden stroke or ischemic stroke, at this time, blood cannot normally perfuse into the brain blood vessels with the heartbeat of the heart. Once the blood cannot normally perfuse into the blood vessels in a certain region of the brain, the change amount of the electrical parameters of the blood vessels in the region decreases, causing the imaging image of the region to become dark, or even disappear. In this embodiment, as shown in Figure 4b , it is the change amount of the dielectric constant caused by the brain blood perfusion when the brain blood vessels are occluded. By comparing Figure 4a with Figure 4b , it can be clearly seen that after the brain blood vessel occlusion, the change amount of the dielectric constant of the blood vessels in some regions of the brain decreases (the imaging becomes light), or even disappears (the imaging has no display).

[0098] Similarly, in this embodiment, the dielectric constant during brain perfusion is also imaged and compared. As shown in Figure 5a , it is the dielectric constant distribution of the brain blood vessels in the case of normal brain blood perfusion. As shown in Figure 5b , it is the dielectric constant distribution of the brain blood vessels when the brain blood vessels are occluded, corresponding to a sudden stroke, ischemic stroke, etc. By comparison, it can be clearly seen that the dielectric constant of the brain blood vessels changes obviously when the brain blood vessels are occluded.

[0099] Figure 6is a block diagram of a brain perfusion imaging device 100 according to the present embodiment, referring to Figure 6 The device comprises a transmitting module, an acquisition module, a data processing module, a calculation module and an imaging module,

[0100] The transmitting module 101 is configured to control each antenna unit in the antenna array to sequentially emit electromagnetic waves in turn;

[0101] The acquisition module 102 is configured to continuously acquire spatial scattered electromagnetic field data at each antenna unit in the antenna array, and after each antenna unit emits electromagnetic waves, the acquired spatial scattered electromagnetic field data is taken as a frame of data; The frequency of acquiring a frame of data is greater than 2 times the heart rate;

[0102] The data processing module 103 is configured to extract the corresponding perfusion component from each frame of data continuously acquired from the initial time;

[0103] The calculation module 104 is configured to calculate the change amount of the perfusion component relative to the initial time according to the corresponding perfusion component extracted from each frame of data, and calculate the change amount of the brain electrical parameter according to the change amount of the perfusion component;

[0104] The imaging module 105 is configured to perform imaging according to the brain electrical parameter change amount calculated.

[0105] Optionally, the acquisition module 102 can comprise:

[0106] The data acquisition submodule is configured to sequentially acquire spatial scattered electromagnetic field data at the remaining antenna units when each antenna unit in the antenna array emits electromagnetic waves;

[0107] The first output submodule is configured to output all the spatial scattered electromagnetic field data acquired in the antenna array as a frame of data after each antenna unit in the antenna array emits electromagnetic waves in turn.

[0108] Optionally, the data processing module 103 can comprise:

[0109] The filtering submodule is configured to filter each frame of data acquired to extract low-frequency component data therefrom;

[0110] The second output submodule is configured to extract data consistent with the heart rate from the low-frequency component data as the perfusion component corresponding to the frame of data.

[0111] In the embodiments of the present disclosure, the data processing module performs relevant processing on the received spatial scattering electromagnetic wave data, including operations such as filtering, amplification, mixing, modulation, and the like, to obtain the required perfusion component.

[0112] Optionally, the calculation module 104 can include:

[0113] The parameter reconstruction submodule is configured to take the perfusion component corresponding to the one frame of data at the initial moment as a reference point perfusion component; take the perfusion component corresponding to each moment after the initial moment as a reference point perfusion component; take the difference between the reference point perfusion component and the perfusion component corresponding to each moment after the initial moment to obtain a differential data quantity; the differential data quantity is the change quantity of the perfusion component at the initial moment; calculate a differential data quantity sensitivity matrix according to the differential data quantity; and calculate the change quantity of the brain electrical parameter according to the differential data quantity sensitivity matrix.

[0114] The third output submodule is configured to output the calculated change quantity of the brain electrical parameter.

[0115] Optionally, the brain perfusion imaging device 100 further includes a control module configured to control each antenna unit in the antenna array to sequentially emit and receive spatial electromagnetic field data; the frequency at which each antenna unit sequentially emits one electromagnetic wave is greater than 2 times the heart rate.

[0116] The control module controls the acquisition module to continuously acquire the one frame of data; the frequency at which the one frame of data is acquired is consistent with the frequency at which each antenna unit sequentially emits one electromagnetic wave.

[0117] The control module in the embodiments is not only limited to acting on the emission, reception, and acquisition processes of electromagnetic waves, but can also control and manage the microwave measurement system, including but not limited to setting measurement parameters, controlling the working state of a signal source and a receiver, and the like.

[0118] As to the device in the above embodiments, the specific manner in which each module performs operations has been described in detail in the embodiments of the method, and will not be described in detail here.

[0119] Unlike the related art, which reconstructs the static spatial distribution of brain tissue electrical parameters by using the carrier frequency component of the brain microwave signal, the present disclosure reconstructs the change in brain permittivity and conductivity by using the modulation low-frequency component of the signal, and reconstructs the perfusion distribution of the brain blood flow in real time, to provide the four-dimensional spatiotemporal information of the brain blood flow perfusion that is currently unavailable in the clinic and does not require a contrast agent.

[0120] In the embodiments of the present disclosure, first, the perfusion component of the human brain blood vessels is extracted from the collected brain microwave electromagnetic field data, then the brain electrical parameter change amount is calculated through the perfusion component, and the brain electrical parameter change amount is dynamically imaged in time distribution and spatial distribution, so as to reflect the brain blood vessel occlusion state in real time and accurately. In the critical scene of sudden brain blood vessel occlusion such as stroke, ischemic stroke and the like of the patient, the brain blood vessels of the patient can be quickly screened and positioned, so as to win the treatment time for the patient, in the continuous monitoring of the brain blood reconstruction after the treatment of stroke, the treatment recovery can be monitored in real time, and the treatment effect can be improved in time feedback, and the method does not need to use contrast agent, and does not cause side effects to the patient's body.

[0121] The above only describes the preferred embodiments of the present disclosure and does not limit the present disclosure. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

[0122] For the method embodiments, in order to simply describe, they are all expressed as a series of action combinations, but those skilled in the art should know that the present disclosure is not limited to the action sequence described, because according to the present disclosure, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and components involved are not necessarily necessary for the present disclosure.

[0123] The brain perfusion imaging method and device provided by the present disclosure are described in detail above, and the principles and implementation modes of the present disclosure are described by applying specific examples. The above embodiment description is only used to help understand the method of the present disclosure and its core idea; at the same time, for those skilled in the art, according to the idea of the present disclosure, the specific implementation mode and application range will be changed; in summary, the content of the specification should not be understood as a limitation of the present disclosure.

Claims

1. A brain perfusion imaging method, characterized in that, include: S1: Controls each antenna element in the antenna array to transmit electromagnetic waves sequentially. S2: Continuously collect spatial scattered electromagnetic field data at each antenna element in the antenna array. After each antenna element emits an electromagnetic wave once, the collected spatial scattered electromagnetic field data is taken as a frame of data. The frequency of collecting a frame of data is greater than twice the heart rate. S3: Starting from the initial moment, extract the corresponding perfusion component from each frame of data continuously acquired; S4: Based on the corresponding perfusion component extracted from each frame of data, calculate the change in the perfusion component relative to the initial time, and calculate the change in the brain electrical parameters based on the change in the perfusion component. S5: Based on the calculated changes in brain electrical parameters, perform imaging; Extracting the corresponding perfusion component from each frame of continuously acquired data includes: S31: Filter each frame of data collected to extract the low-frequency component data; S32: Extract data that is consistent with the heart rate from the low-frequency component data, and use it as the perfusion component corresponding to the frame of data.

2. The brain perfusion imaging method according to claim 1, characterized in that, After each antenna element transmits an electromagnetic wave, the collected spatial scattered electromagnetic field data is taken as a frame of data, including: S21: Collect the spatial scattered electromagnetic field data at the other antenna elements when each antenna element in the antenna array emits electromagnetic waves in sequence; S22: After each antenna element in the antenna array has emitted an electromagnetic wave once in sequence, all the spatial scattered electromagnetic field data collected in the antenna array are taken as a frame of data.

3. The brain perfusion imaging method according to claim 1, characterized in that, Calculating the change in perfusion components relative to the initial time includes: S41: Take the injection component corresponding to the first frame of data at the initial time as the reference point injection component; S42: Subtract the perfusion component corresponding to each time point after the initial time point from the perfusion component at the reference point to obtain the differential data quantity; the differential data quantity is the change in the perfusion component at that time point relative to the initial time point. S43: Calculate the differential data volume sensitivity matrix based on the differential data volume; S44: Calculate the change in the brain electrical parameters based on the differential data sensitivity matrix.

4. The brain perfusion imaging method according to claim 1, characterized in that, The change in the electrical parameters of the brain refers to the change in the dielectric constant of the blood vessels in the brain.

5. An apparatus for brain perfusion imaging, used to perform the brain perfusion imaging method as described in any one of claims 1 to 4, characterized in that, include: The transmitting module is configured to control the antenna elements in the antenna array to transmit electromagnetic waves sequentially. The acquisition module is configured to continuously acquire spatially scattered electromagnetic field data at each antenna element in the antenna array. After each antenna element has emitted an electromagnetic wave once, the acquired spatially scattered electromagnetic field data is used as a frame of data. The frequency of acquiring a frame of data is greater than twice the heart rate. The data processing module is configured to extract the corresponding perfusion component from each frame of continuously acquired data, starting from the initial moment. The calculation module is configured to calculate the change in the perfusion component relative to the initial time based on the corresponding perfusion component extracted from each frame of data, and to calculate the change in the brain electrical parameters based on the change in the perfusion component. An imaging module is configured to perform imaging based on the calculated changes in brain electrical parameters; The data processing module includes: The filtering submodule is configured to filter each frame of data acquired in each acquisition and extract the low-frequency component data. The second output submodule is configured to extract data consistent with the heart rate from the low-frequency component data and output it as the perfusion component corresponding to the frame of data.

6. The apparatus for brain perfusion imaging according to claim 5, characterized in that, The acquisition module includes: The data acquisition submodule is configured to sequentially acquire the spatial scattered electromagnetic field data at the other antenna elements when each antenna element in the antenna array emits electromagnetic waves; The first output submodule is configured to output all the spatial scattered electromagnetic field data collected in the antenna array as a data frame after each antenna element in the antenna array has emitted an electromagnetic wave in sequence.

7. The apparatus for brain perfusion imaging according to claim 5, characterized in that, The computing module includes: The parameter reconstruction submodule is configured to use the perfusion component corresponding to the first frame of data at the initial time as the reference point perfusion component; subtract the reference point perfusion component from the perfusion component corresponding to each time after the initial time to obtain the differential data quantity; the differential data quantity is the change in the perfusion component at that time relative to the initial time; calculate the differential data quantity sensitivity matrix based on the differential data quantity; and calculate the change in the electroencephalogram of brain parameters based on the differential data quantity sensitivity matrix. The third output submodule is configured to output the calculated changes in brain electrical parameters.

8. The apparatus for brain perfusion imaging according to claim 5, characterized in that, It also includes a control module, which is configured to: The antenna array is controlled to sequentially transmit and receive spatial electromagnetic field data; the frequency of each antenna element transmitting an electromagnetic wave in sequence is greater than twice the heart rate. The acquisition module is controlled to continuously acquire one frame of data; the frequency of acquiring one frame of data is consistent with the frequency at which each antenna element transmits an electromagnetic wave in sequence.

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