A new-born brain imaging system and method based on photoacoustic technology

Abstract

The application claims a kind of neonatal brain imaging system and method based on photoacoustic technology, belong to the field of medical devices. Including control module, excitation source module, neonatal brain photoacoustic data acquisition module, data output module and quantitative calculation module. The control module includes two computers and laser control instrument;The excitation source module includes high-frequency laser and its water cooling system;Neonatal brain photoacoustic data acquisition module contains focusing lens and optical fiber, wearable flexible ultrasonic transducer, multichannel acquisition card;The data output module contains computer matched with real-time imaging MarsonicsDAQ software and the imaging algorithm embedded in the software;Quantitative calculation module contains multispectral linear demixing algorithm and imaging software. The application provides high-resolution, high-contrast real-time imaging of neonatal brain tissue structure and cerebral hemodynamic parameters, which can be used as a complementary method to existing brain imaging techniques for auxiliary diagnosis.

Description

Technical Field

[0001] This invention belongs to the field of medical devices, and specifically relates to a neonatal brain imaging detection system and method based on photoacoustic technology. Background Technology

[0002] With the rapid development of society and the economy, and the continuous advancement of modern medicine and diagnostic equipment, the early diagnosis and intervention of diseases have attracted increasing attention. Despite significant progress in the medical field, the diagnosis of neonatal encephalopathy remains a challenging task. This problem presents a series of difficulties in clinical practice, requiring continuous in-depth research and the utilization of advanced medical technologies and scientific research findings to find more accurate and effective diagnostic methods. Therefore, strengthening research on neonatal encephalopathy and improving diagnostic accuracy and treatment outcomes has become one of the most important issues urgently needing to be addressed in the current medical field.

[0003] Intracranial hemorrhage (ICH), also known as hemorrhagic cerebrovascular disease or hemorrhagic stroke, is a brain disease caused by the rupture of a blood vessel in the brain, resulting in blood spilling into the cranial cavity. ICH is a common early neonatal disease and one of the leading causes of death; its diagnosis and treatment are routine procedures in neonatal wards both domestically and internationally. Neonatal hypoxic-ischemic encephalopathy (HIE) refers to hypoxic-ischemic brain damage caused by perinatal asphyxia. Clinically, it presents with a series of central nervous system abnormalities, such as altered consciousness, changes in muscle tone, abnormal primitive reflexes, and in severe cases, seizures, brainstem signs, and increased anterior fontanelle tone. Both neonatal ICH and HIE are characterized by high morbidity, high mortality, and high rates of disability.

[0004] Studies have shown that the incidence of ICH in hospitalized newborns is approximately 13%, and as high as 40%-70% in premature infants. Furthermore, severe cerebral hemorrhage can cause permanent damage, leading to serious sequelae such as hydrocephalus, hemiplegia, or intellectual disability, and even death. According to related studies, the mortality rate of this disease is as high as 9.0%-18.5%. The incidence of HIE in hospitalized newborns is 2‰-8‰, but the mortality rate among affected newborns is as high as 15%-20%. In addition, 25%-30% of surviving children often suffer from various neurological disorders resulting in disability, including developmental delays, cerebral palsy, epilepsy, visual impairment, and learning disabilities.

[0005] Childhood epilepsy is a common, complex, and recurrent neurological syndrome in childhood. It is caused by paroxysmal, transient brain dysfunction leading to seizures. Clinical manifestations include recurrent muscle spasms, and transient abnormalities in consciousness, sensation, and emotion. It is mainly caused by incomplete development of the child's nervous system, resulting in excessive and abnormal electrical discharges in the cerebral cortex due to stimulation. Hydrocephalus refers to the excessive accumulation of cerebrospinal fluid in the ventricular system, causing increased intraventricular pressure. Its main symptoms include developmental delay, headache, vomiting, and drowsiness. Physical signs include increased head circumference, high fontanelle tension, difficulty looking upward, papilledema, and abducens nerve palsy.

[0006] Neonatal cerebral hemorrhage and hypoxic-ischemic encephalopathy are characterized by neurological damage, high mortality, and a high incidence of neurological sequelae. Severe neurological damage can lead to symptoms such as loss of consciousness, abnormal heart rate, and respiratory distress, as well as the gradual necrosis of neurons and nerve cells. Epilepsy and hydrocephalus are also common neurological syndromes in childhood, significantly impacting the growth, development, and normal function of the neonatal nervous system. Early diagnosis and treatment are crucial for neonatal encephalopathy, as timely treatment can minimize potential neurological damage. Therefore, developing a rapid and accurate brain diagnostic instrument is essential. The neonatal brain imaging system developed in this patent can, based on photoacoustic images and hemodynamic parameter assessments, clearly identify the location and severity of lesions in cerebral hemorrhage, hypoxic-ischemic encephalopathy, epileptic encephalopathy, and hydrocephalus, assisting medical personnel in developing appropriate intervention and treatment plans. This enables early detection and treatment, preventing further deterioration, inhibiting ongoing brain damage, reducing neonatal disability rates, and improving prognosis.

[0007] Modern brain imaging techniques include electroencephalography (EEG), transcranial Doppler ultrasound, computed tomography (CT), functional magnetic resonance imaging (fMRI), single-photon emission computed tomography (SPECT), positron emission tomography (PET), and near-infrared functional imaging. EEG can continuously monitor brain electrophysiological signals, but it cannot precisely locate the position and size of lesions, and quantitative assessment is difficult. Transcranial Doppler ultrasound can quantitatively assess the location of lesions, but it requires a high level of skill from the physician and has low contrast in brain tissue imaging. CT provides clear images of brain tissue, but it cannot provide quantitative assessment and involves ionizing radiation during scanning, the effects of which on newborns are unknown. FMRI offers multi-axial imaging, high resolution, and no radiation damage; however, the equipment has high environmental requirements, the examination is time-consuming and noisy, and the infant must be calm and immobilized, potentially requiring anesthesia or sedation. In addition, functional magnetic resonance imaging (fMRI) equipment is expensive, and the testing costs are high; single-photon emission computed tomography (SPECT) and positron emission tomography (PET) can semi-quantitatively or quantitatively measure local cerebral blood flow, but these two technologies not only require the injection of radioactive exogenous tracers, but also have low spatial resolution, high prices, and high equipment operation and maintenance costs; near-infrared functional imaging can diagnose brain tissue lesions, but its spatial resolution is limited, it cannot accurately locate the damaged area, and it is difficult to detect tiny lesions.

[0008] In traditional photoacoustic brain imaging systems, linear array ultrasound transducers typically only provide imaging at a certain angle, resulting in a limited imaging range that may not cover the entire sample area, and their resolution is relatively poor. Semi-circular array ultrasound transducers, limited by the probe's focusing radius, exhibit inconsistent imaging effects for patients with different head circumferences. Therefore, this invention employs flexible circuitry to create a wearable flexible ultrasound transducer that autonomously adjusts its shape and focusing radius according to each patient's head circumference, maximizing signal reception and effectively enhancing the resolution and contrast of the photoacoustic images.

[0009] Furthermore, traditional photoacoustic brain imaging systems often employ photoacoustic reconstruction algorithms with relatively low accuracy, such as delay-stack algorithms and filtered back-projection algorithms. This invention utilizes a finite element-based photoacoustic reconstruction algorithm, which iteratively solves the time-domain photon diffusion equation to obtain an accurate solution for the absorption coefficient of the medium / biological tissue. This method improves the accuracy of the reconstructed image and provides a reliable data foundation for the quantitative analysis of imaging results. Through this optimized algorithm, we can more accurately evaluate imaging results, thereby achieving more efficient diagnosis and research in the field of biomedical imaging. Summary of the Invention

[0010] This invention aims to solve the problems of the prior art mentioned above. It proposes a neonatal brain imaging system and method based on photoacoustic technology. The technical solution of this invention is as follows:

[0011] A neonatal brain imaging system based on photoacoustic technology, characterized in that it comprises: a control module (3), an excitation source module (4), a neonatal brain photoacoustic data acquisition module (5), and a data output module (8); the output end of the neonatal brain photoacoustic data acquisition module (5) is connected to the receiving end of the data output module (8); wherein,

[0012] The control module includes computer 1, computer 2 and a laser control instrument (10). Computer 1 is used to indirectly control the frequency, wavelength and energy of the laser by controlling the laser control instrument. Computer 2 is used to control the amplification factor of the neonatal brain photoacoustic data acquisition module (5), the frequency range of the acquired signal and the output of the image by controlling the MarsonicsDAQ software (18).

[0013] The excitation source module (4) includes a high-frequency laser (12) and a water cooling system (11). The high-frequency laser (12) is used to output pulsed laser, and the water cooling system (11) is used to control the ambient temperature of the laser pump source.

[0014] The neonatal brain photoacoustic data acquisition module (5) includes a laser transmission module (6) and a data acquisition module (7). The laser transmission module (6) includes a convex lens (13) and an optical fiber (14). The pulsed laser output by the laser is fed into the optical fiber (14) through a focusing lens. After the laser is transmitted through the optical fiber, it is uniformly irradiated onto the biological tissue under test to generate photoacoustic signals. The ultrasound signals are acquired by a flexible ultrasound transducer (15) worn on the neonatal brain. The ultrasound transducer is unidirectionally electrically connected to the acquisition card. The photoacoustic signals received by the ultrasound transducer are sent to a multi-channel data acquisition card (16) for data processing. Then the processed signals are transmitted to MarsonicsDAQ software (18) for image reconstruction.

[0015] The algorithm of the data output module (8) includes a photoacoustic reconstruction algorithm based on finite element iteration; the MarsonicsDAQ software (18) is loaded into the computer 2, and the data transmitted from the acquisition card is displayed in real time through its embedded photoacoustic reconstruction algorithm based on finite element iteration;

[0016] The multispectral linear unmixing algorithm of the quantitative calculation module (9) is a quantitative calculation method developed based on MATLAB software. It calculates the cerebral hemodynamic parameters by linearly unmixing the photoacoustic imaging data under multispectral conditions.

[0017] Furthermore, the high-frequency laser is used to output pulsed laser with a repetition frequency of 500Hz and a peak energy of 26.7mJ / cm2. Its water-cooling system can control the ambient temperature of the laser pump source at around 24℃. The high-frequency laser is also used to achieve rapid wavelength switching. With the pulse frequency at 500Hz, it can quickly switch between two wavelengths of 730nm and 875nm, that is, only the wavelength is changed while the other experimental conditions remain unchanged.

[0018] Furthermore, the optical fiber is 1.2m long, with a circular inlet of 0.9cm in diameter and a rectangular outlet of 40mm in length and 1mm in width. The laser beam, after being focused by a convex lens, enters the optical fiber uniformly and emits a rectangular laser beam of 40mm in length and 1mm in width with uniform energy at the outlet. The laser energy is approximately 2mJ / cm². 2 .

[0019] Furthermore, the ultrasonic transducer has 256 array elements, which can be freely adjusted to the corresponding curvature according to the different head contours of infants; by using ultrasonic coupling fluid, the ultrasonic transducer can be tightly coupled with the skin; the multi-channel data acquisition card has 256 channels, and the signal amplification factor is adjustable from 1dB to 100dB.

[0020] Furthermore, the real-time image display can determine whether there is bleeding, hypoxia / ischemia, abnormal brain activity, or cerebrospinal fluid accumulation in the brain tissue. The determination rule is as follows: the distribution of light absorption coefficient in the brain tissue imaging region is calculated by a photoacoustic reconstruction algorithm based on finite element iteration. High-brightness areas will appear at the sites of brain tissue bleeding and abnormal brain excitation, while dark areas will appear at the sites of hypoxia / ischemia and cerebrospinal fluid accumulation. It is also possible to determine whether there is structural misalignment of the brain by observing the brain tissue structure in the reconstructed image. The principle of the photoacoustic reconstruction algorithm based on finite element iteration is to use the finite element method (FEM) to iteratively solve the radiation transfer equation (RTE) and the photoacoustic wave equation (PWE). First, the distribution of light flux is obtained from the initial distribution of light absorption coefficient by solving the finite element method (FE) of RTE. Then, the sound pressure at each transducer position along the medium / tissue surface is calculated using the Helmholtz equation. Then, the matrix equation for absorption coefficient inversion is obtained using the canonical Newton method. Finally, the absorption coefficient distribution is updated by iteratively solving the equation to form a photoacoustic reconstructed image.

[0021] Furthermore, the luminous flux distribution is obtained from the initial distribution of the light absorption coefficient by solving the finite element method (FE) of the RTE; then... use The forward solution is solved using formula (1), and the backward solution is solved using formulas (2) and (3). Then, the forward and backward solutions are substituted into the time-domain photon diffusion equation for iterative calculation to solve the absorption coefficient of the medium / biological tissue. Finally, the absorption coefficient distribution is updated by iteratively solving the equation, specifically including the following steps:

[0022] Forward solution:

[0023]

[0024] Reverse solution:

[0025] (J T J+λI) Δχ=J T (p o -p c (2)

[0026] Δχ=Ψ o -Ψ c (3)

[0027] Light diffusion equation:

[0028] ▽·D▽Φ(r)-μ a Φ(r)=-S(r) (4)

[0029] In the formula, p(r,t) is the sound pressure at position r in the medium at time t, ▽ 2 It is the Laplace operator, v0 is the speed of sound in the medium, β is the coefficient of thermal expansion, and C p ψ(r) is the constant-pressure specific heat capacity, I(t) is the spatial distribution of the initial light absorption energy, J is the function of light intensity changing with time, and J is the Jacobian matrix composed of the partial derivatives of the measured sound pressure values ​​at the boundary with respect to the absorbed energy density. λ is the regularization parameter, Δχ is the update vector of absorbed energy density, and p o It is the actual sound pressure distribution, p c The sound pressure distribution ψ is obtained by forward solving for a given initial absorbed energy density. o The absorbed energy density distribution ψ is obtained by discretizing the wave equation using the finite element method. c It is the calculated absorption energy density distribution, where D is the diffusion coefficient, Φ(r) is the photon density, and μ is the density of light. a is the absorption coefficient, and S(r) is the photon flux at position r.

[0030] Furthermore, the multispectral linear unmixing algorithm specifically involves: performing photoacoustic imaging of the newborn's brain using lasers of two wavelengths, 730nm and 875nm, respectively; then substituting the imaging data into the formula for the relationship between endogenous contrast agents to calculate oxygenated hemoglobin, deoxygenated hemoglobin, total hemoglobin, oxygen saturation, and water content.

[0031] Furthermore, by substituting the imaging data into the formula relating endogenous contrast agents, important hemodynamic parameters such as oxyhemoglobin, deoxyhemoglobin, total hemoglobin, oxygen saturation, and water content are calculated, specifically including:

[0032]

[0033] sO2=f*sO 2,ti +(1-f)*f*sO 2,to (7)

[0034]

[0035] In the formula, Photoacoustic image at wavelength λ The intensity of the photoacoustic signal at the location; ε HbO (λ), ε HbR (λ) and These represent the absorption coefficients of oxyhemoglobin, deoxyhemoglobin, and water at a wavelength of λ, respectively. sO2 and [HbT] are respectively in The concentration distribution of oxygenated hemoglobin, deoxygenated hemoglobin, water, oxygen saturation, and total hemoglobin at the site. 2,ti and sO 2,to These are the mean oxygen saturation at the tissue inlet (artery) and outlet (venous), respectively, where f is the mean oxygen saturation (SO2). 2,ti The coefficient. Where BF is the average blood flow of all vessels within the tissue, and is specified as the average blood flow of the tissue; OC = MRO2 is the average oxygen consumption (oxygen metabolism) of the entire tissue; [HbT] blood It is the average total hemoglobin concentration calculated from the tissue, and V is the tissue volume.

[0036] A detection method based on any one of the systems described herein, comprising the following steps:

[0037] Step 1: Turn on the laser and the multi-channel acquisition card, adjust the trigger mode of the acquisition card to passive trigger for laser pulse, and then set the laser pulse wavelength to 730nm and the relevant parameters of the pulsed laser as well as the various parameters sampled by the acquisition card.

[0038] Step 2: Apply an appropriate amount of ultrasound coupling fluid to the detection location on the infant's brain, wear the flexible ultrasound transducer on the newborn's brain, and ensure that the detection array elements are in close contact with the newborn's brain skin.

[0039] Step 3: Using computer 1, gradually turn on the high-frequency laser pump source and pulsed laser emission switch, and allow the laser to preheat for about half an hour;

[0040] Step 4: The pulsed laser shines on the surface of the newborn's brain through a convex lens and optical fiber. The brain tissue absorbs the laser energy and converts it into heat energy, causing transient temperature changes. This further leads to thermal expansion, resulting in local pressure changes and generating ultrasound waves.

[0041] Step 5: Use a wearable ultrasound transducer to receive photoacoustic signals at multiple locations on the newborn's brain;

[0042] Step 6: The photoacoustic signal received by the ultrasonic transducer is wirelessly transmitted into the multi-channel data acquisition card for data processing.

[0043] Step 7: Keep all experimental conditions unchanged, and adjust the wavelength of the pulsed laser to 875nm;

[0044] Step 8: The collected photoacoustic data are combined with MATLAB software and finite element photoacoustic reconstruction algorithm to qualitatively determine whether there are lesions inside the neonatal brain tissue;

[0045] Step 9: If the brain tissue reconstruction imaging is abnormal, further combine the multispectral linear unmixing algorithm to quantify the degree of lesion in the brain region;

[0046] Step 10: Output the qualitative and quantitative reconstruction results from Steps 8 and 9.

[0047] The advantages and beneficial effects of this invention are as follows:

[0048] Existing brain imaging techniques often have limitations in diagnosing neuropathic encephalopathy such as neonatal cerebral hemorrhage, hypoxic-ischemic cerebral encephalopathy, epileptic encephalopathy, and hydrocephalus. Compared to electroencephalography (EEG), this invention can precisely locate lesions and provide data on the distribution of hemodynamic parameters of the lesion and its surrounding brain. Compared to transcranial Doppler ultrasound, this invention can perform high-contrast, high-resolution imaging. Compared to computed tomography (CT), single-photon emission computed tomography (SPECT), and positron emission tomography (PET), this invention allows for continuous bedside monitoring without ionizing radiation. Compared to magnetic resonance imaging (MRI), this invention provides rapid, real-time imaging with no contraindications. Compared to near-infrared imaging, this invention can provide clear, high-resolution imaging of lesions, enabling more precise lesion location.

[0049] The neonatal brain imaging system based on photoacoustic technology of this invention employs a finite element-based photoacoustic reconstruction method and a multispectral linear unmixing algorithm. By substituting the precise data solution from the finite element reconstruction algorithm into the multispectral linear unmixing algorithm, it helps to more accurately assess hemodynamic changes, thereby achieving a more accurate and reliable diagnosis. This system can simultaneously provide high-resolution, high-contrast real-time images of the internal structure of brain tissue, the distribution of light absorption coefficients in brain tissue, and cerebral hemodynamic parameters. It can determine the location and size of brain lesions based on the light absorption coefficient distribution map, and determine the degree of brain lesions based on the hemodynamic parameter images. This assists medical personnel in developing appropriate intervention and treatment plans, enabling early detection and treatment, preventing further deterioration of the condition, inhibiting ongoing brain injury processes, reducing neonatal disability rates, and improving prognosis.

[0050] The ingenuity of this invention lies in: (1) the use of a wearable flexible ultrasound transducer allows for appropriate bending according to the different shapes and sizes of infant brains, closely fitting the infant brain for photoacoustic imaging signal acquisition, making the acquisition operation more convenient and flexible, and the acquisition device more universal. At the same time, by using optical frequency domain scattering technology to accurately locate each array element on the flexible probe, and combined with a reconstruction algorithm specifically developed for the flexible probe, the resolution, contrast and other key image quality parameters of the reconstructed image can be significantly improved, thereby further optimizing the photoacoustic imaging results. In addition, wearable flexible ultrasound transducers can create relaxed testing conditions for infants and young children, avoiding excessive stimulation of the newborn's emotions during the testing process, which may lead to an increase in the severity of encephalopathy such as cerebral hemorrhage, cerebral hypoxia-ischemia, epileptic encephalopathy, and hydrocephalus; (2) MATLAB software combined with the photoacoustic reconstruction algorithm based on finite element can quickly determine in real time whether there is ischemia, hemorrhage, edema in the brain tissue and whether the internal structure of the brain tissue has shifted; (3) Combined with the multispectral linear unmixing algorithm to calculate the distribution of hemodynamic parameters of brain tissue, qualitatively and quantitatively determine the severity of the disease in newborns; (3) The reconstruction algorithm used in this invention is a dual-grid finite element photoacoustic reconstruction algorithm, which can perform preliminary calculations on a coarser grid and then perform local fine calculations on a finer grid, thereby reducing the overall calculation volume and improving the calculation efficiency. At the same time, it combines the global information of the coarse grid and the local details of the fine grid, which helps to improve the accuracy of the reconstructed image, especially when dealing with tissues with non-uniform acoustic properties. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of a preferred embodiment of the neonatal brain imaging system applicable to photoacoustic technology provided by the present invention;

[0052] Figure 2 This is a schematic diagram of the neonatal disease diagnosis process in an embodiment of the present invention;

[0053] Figure 3 This is a schematic diagram of the operation process of the neonatal brain photoacoustic imaging system in an embodiment of the present invention. Detailed Implementation

[0054] The technical solutions of the embodiments of the present invention will be clearly and thoroughly described below with reference to the accompanying drawings. The described embodiments are merely some embodiments of the present invention.

[0055] The technical solution of the present invention to solve the above-mentioned technical problems is:

[0056] like Figure 1As shown, the neonatal brain imaging system based on photoacoustic technology of the present invention includes a control module 3, an excitation source module 4, a neonatal brain photoacoustic data acquisition module 5, a data output module 8, and a quantitative calculation module 9; the output end of the receiving module 7 in the neonatal brain photoacoustic data acquisition module 5 is connected to the receiving end of the data output module 8;

[0057] The control module 3 includes computer 1, computer 2 and a laser control instrument 10. The entire system indirectly controls the frequency, wavelength and energy of the laser by controlling the laser control instrument 10 through computer 1, and controls the amplification factor and frequency range of the acquired signal through computer 2, and controls the output of the image through MarsonicsDAQ software 18.

[0058] The excitation source module 4 includes a high-frequency laser 12 and its water cooling system 11;

[0059] Based on the above embodiments, the high-frequency laser 12 can achieve rapid wavelength switching, with a maximum repetition frequency of 500 Hz and a peak energy of 26.7 mJ / cm². 2 .

[0060] Based on the above embodiments, the water cooling system 11 can control the ambient temperature of the laser pump source at around 24°C, ensuring the stability of the output laser.

[0061] The neonatal brain photoacoustic data acquisition module 5 includes a laser transmission module 6 and a data acquisition module 7. The laser transmission module 6 includes a convex lens 13 and an optical fiber 14. The data acquisition module 7 includes a wearable flexible ultrasonic transducer 15 and a multi-channel acquisition card 16. The pulsed laser output from the laser passes through the focusing lens 13 and enters the optical fiber 14. After being transmitted through the optical fiber 14, the laser uniformly irradiates the tested biological tissue to generate a photoacoustic signal. The optical fiber 14 is selected from silica optical fibers with a small absorption coefficient in a specific wavelength range of 730nm to 875nm to reduce energy loss during laser transmission. The laser irradiates the tested biological tissue to generate a photoacoustic signal after being transmitted through the optical fiber 14. This ultrasonic signal is acquired by the flexible ultrasonic transducer 15 worn on the neonatal brain. The ultrasonic transducer 15 is unidirectionally electrically connected to the acquisition card 16. The photoacoustic signal received by the ultrasonic transducer 15 is sent to the multi-channel data acquisition card 16 for data processing, and then the processed signal is transmitted to MarsonicsDAQ software for image reconstruction.

[0062] Based on the above embodiment, the optical fiber 14 is 1.2m long, with a circular inlet of 0.9cm in diameter and a rectangular outlet of 40mm in length and 1mm in width. After being focused by a convex lens, the laser light enters the optical fiber uniformly and is emitted at the outlet as a rectangular laser beam with uniform energy, measuring 40mm in length and 1mm in width. The laser energy is approximately 2mJ / cm².2 It is far below the laser energy safety standard of 10 mJ / cm 2 .

[0063] Based on the above embodiments, the wearable flexible ultrasonic transducer 15 has 256 array elements and excellent free bending performance, allowing it to be freely adjusted to the corresponding curvature according to different infant head contours. By using an ultrasonic coupling fluid, the ultrasonic transducer can be tightly coupled to the skin, thereby improving the sensitivity and accuracy of the sensor.

[0064] Based on the above embodiments, the multi-channel data acquisition card has 256 channels (16 channels in total) and receives data acquired by the ultrasonic transducer via wireless connection; its signal amplification factor is adjustable from 1dB to 100dB.

[0065] The MarsonicsDAQ imaging software 18 of the data output module 8 is software developed based on the multi-channel acquisition card 16 in the acquisition module. The algorithm includes an embedded photoacoustic reconstruction algorithm 17 based on finite element method. The MarsonicsDAQ software 18 is loaded into the computer 2, and the data transmitted from the acquisition card 16 is used to display the image in real time through its embedded algorithm.

[0066] Furthermore, based on the above embodiments, the rule for determining whether there is hemorrhage or hypoxia / ischemia is as follows: The distribution of light absorption coefficient in the brain tissue imaging region is calculated using a finite element-based photoacoustic reconstruction algorithm. Hemorrhage in the brain tissue will result in a bright area, while hypoxia / ischemia will result in a dark area. The principle of the finite element-based iterative photoacoustic reconstruction algorithm is to use the finite element method (FEM) to iteratively solve the radiation transfer equation (RTE) and the photoacoustic wave equation (PWE). First, from the initial (guessed) distribution of the light absorption coefficient, the distribution of light flux is obtained by solving the finite element (FE) method of the RTE. Then, the sound pressure at each transducer position along the medium / tissue surface is calculated using the Helmholtz equation. Next, the matrix equation for the absorption coefficient inversion is obtained using the canonical Newton method. Finally, the absorption coefficient distribution is updated by iteratively solving the equation, forming a photoacoustic reconstructed image.

[0067] The multispectral linear unmixing algorithm of the quantitative calculation module is a quantitative calculation method developed based on MATLAB software. It calculates cerebral hemodynamic parameters by linearly unmixing photoacoustic imaging data under multispectral conditions.

[0068] Furthermore, based on the above embodiments, real-time image display can determine whether there is bleeding, hypoxia / ischemia, abnormal excitation of brain regions, or cerebrospinal fluid within the brain tissue. The determination rule is as follows: the specific values ​​of oxygenated hemoglobin, deoxygenated hemoglobin, total hemoglobin, oxygen saturation, and water content parameters in the neonatal brain region are calculated using a multispectral linear unmixing algorithm 19. The degree of illness in the newborn is then determined by comparing the differences with the hemodynamic parameters of a normal newborn's brain.

[0069] Furthermore, the principle of the multispectral linear unmixed image reconstruction algorithm 16 is to use two wavelengths, 730nm and 875nm, to clearly image the brain region, and then substitute them into the formula for the relationship between endogenous contrast agents to calculate oxygenated hemoglobin, deoxygenated hemoglobin, total hemoglobin, blood flow velocity, oxygen saturation, oxygen metabolism rate, and water content. These indicators can all be used as direct criteria for early diagnosis of the degree of brain lesions.

[0070] like Figure 3 As shown, the neonatal brain imaging system and method based on photoacoustic technology of the present invention includes the following steps:

[0071] Step 1: Turn on the laser and the multi-channel acquisition card, adjust the trigger mode of the acquisition card to passive trigger for laser pulse, and then set the laser pulse wavelength to 730nm and the relevant parameters of the pulsed laser as well as the various parameters sampled by the acquisition card.

[0072] Step 2: Apply an appropriate amount of ultrasound coupling fluid to the detection location on the infant's brain, wear the flexible ultrasound transducer on the newborn's brain, and ensure that the detection array elements are in close contact with the newborn's brain skin.

[0073] Step 3: Gradually turn on the high-frequency laser pump source and pulsed laser emission switch via computer, and allow the laser to preheat for about half an hour;

[0074] Step 4: The pulsed laser shines on the surface of the newborn's brain through a convex lens and optical fiber. The brain tissue absorbs the laser energy and converts it into heat energy, causing transient temperature changes. This further leads to thermal expansion, resulting in local pressure changes and generating ultrasound waves.

[0075] Step 5: Use a wearable ultrasound transducer to receive photoacoustic signals at multiple locations around the newborn's brain;

[0076] Step 6: The photoacoustic signal received by the ultrasonic transducer is wirelessly transmitted into the multi-channel data acquisition card for data processing.

[0077] Step 7: Keep all experimental conditions unchanged, and adjust the wavelength of the pulsed laser to 875nm;

[0078] Step 8: The collected photoacoustic data are combined with MATLAB software and a finite element-based photoacoustic reconstruction algorithm to qualitatively determine whether there are lesions inside the neonatal brain tissue;

[0079] Step 9: If the brain tissue reconstruction imaging is abnormal, further combine the multispectral linear unmixing algorithm to quantify the degree of lesion in the brain region;

[0080] Step 10: Output the qualitative and quantitative reconstruction results from Steps 8 and 9.

[0081] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions.

[0082] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0083] The above embodiments should be understood as illustrative only and not as limiting the scope of protection of the present invention. After reading the description of the present invention, those skilled in the art can make various alterations or modifications to the present invention, and these equivalent changes and modifications also fall within the scope defined by the claims of the present invention.

Claims

1. A neonatal brain imaging system based on photoacoustic technology, characterized in that, The application relates to a new-born baby brain photoacoustic data acquisition device, which comprises a control module (3), an excitation source module (4), a new-born baby brain photoacoustic data acquisition module (5) and a data output module (8); the output end of the new-born baby brain photoacoustic data acquisition module (5) is connected with the receiving end of the data output module (8); wherein, The control module comprises a computer 1, a computer 2 and a laser control instrument (10); the computer 1 is used for indirectly controlling the frequency, wavelength and energy of laser through the laser control instrument (10); the computer 2 is used for controlling the amplification multiple of the new-born baby brain photoacoustic data acquisition module (5), the frequency range of the collected signals and the output of the image through the MarsonicsDAQ software (18); The excitation source module (4) comprises a high-frequency laser (12) and a water cooling system (11); the high-frequency laser (12) is used for outputting pulse laser; and the water cooling system (11) is used for controlling the ambient temperature of the laser pump source; The new-born baby brain photoacoustic data acquisition module (5) comprises a laser transmission module (6) and a data acquisition module (7); the laser transmission module (6) comprises a convex lens (13) and an optical fiber (14); the pulse laser output by the laser is converged into the optical fiber (14) through the focusing lens; the laser is uniformly irradiated to the measured biological tissue to generate photoacoustic signals after being transmitted through the optical fiber; the ultrasonic signals are collected through the flexible ultrasonic transducer (15) worn on the brain of the new-born baby; the ultrasonic transducer is unidirectionally electrically connected with the acquisition card; the photoacoustic signals received by the ultrasonic transducer are sent into the multi-channel data acquisition card (16) for data processing; and then the processed signals are transmitted into the MarsonicsDAQ software (18) for image reconstruction; The algorithm of the data output module (8) comprises a photoacoustic reconstruction algorithm based on finite element iteration; the MarsonicsDAQ software (18) is loaded in the computer 2; and the data transmitted by the acquisition card are displayed in images in real time through the photoacoustic reconstruction algorithm based on finite element iteration embedded in the MarsonicsDAQ software (18); The multispectral linear demixing algorithm of the quantitative calculation module (9) is a quantitative calculation method developed based on the MATLAB software; the brain hemodynamic parameters are calculated by linear demixing of the photoacoustic imaging data under multispectrum. ​ The real-time image display can determine whether the brain tissue is hemorrhagic, hypoxic-ischemic, abnormal brain region activity and whether there is effusion, the determination rule is that the distribution of the light absorption coefficient in the brain tissue imaging area is calculated through the photoacoustic reconstruction algorithm based on the finite element iteration, the hemorrhagic brain tissue, the abnormal excited brain region and the brain effusion will appear high light area and dark area, and whether the internal structure of the brain is dislocated can be determined by observing the structure of the reconstructed image; the principle of the photoacoustic reconstruction algorithm based on the finite element iteration is to solve the radiative transfer equation RTE and the photoacoustic wave equation PWE by using the finite element method FEM, first, the distribution of the light flux is obtained by solving the finite element FE of the RTE from the initial distribution of the light absorption coefficient; then the sound pressure at each transducer position along the medium / tissue surface is calculated using the Helmholtz equation; then the regular Newton method is used to obtain the matrix equation of the absorption coefficient inversion; finally, the absorption coefficient distribution is updated by iteratively solving the equation to form the photoacoustic reconstruction image; The distribution of the light flux is obtained by solving the finite element FE of the RTE from the initial distribution of the light absorption coefficient; then the forward solution is solved using formula (1), the reverse solution is solved using formula (2) and (3), and then the forward solution and the backward solution are substituted into the time-domain photon diffusion equation for iterative operation to solve the absorption coefficient of the medium / biological tissue; finally, the absorption coefficient distribution is updated by iteratively solving the equation, which specifically includes the following steps: Forward solution: Reverse solution: (J T J+λI) Δχ=J T (p o -p c ) (2) Δχ = Ψ o -Ψ c (3) Light diffusion equation: where p(r, t) is the acoustic pressure at position r and time t in the medium, is the Laplacian operator, v0is the sound wave propagation velocity in the medium, β is the thermal expansion coefficient, C p is the constant pressure specific heat, ψ(r) is the initial spatial distribution of the optical absorption energy, I(t) is the function of the light intensity variation with time, J is the Jacobian matrix composed of the partial derivatives of the measured acoustic pressure values on the boundary with respect to the absorption energy density λ is the regularization parameter, Δχ is the update vector of the absorption energy density, p o is the real acoustic pressure distribution, p c is the acoustic pressure distribution obtained by forward solving with the given initial absorption energy density, ψ o is the absorption energy density distribution obtained by finite element discretization of the wave equation, ψ c is the calculated absorption energy density distribution, D is the diffusion coefficient, Φ(r) is the photon density, μ a is the absorption coefficient, S(r) is the photon flux at position r.

2. The photoacoustic based neonatal brain imaging system of claim 1, wherein, The high-frequency laser is used to output pulsed laser with a repetition frequency of 500Hz and an energy peak value of 26.7mJ / cm2, and the water cooling system matched with the high-frequency laser can control the environmental temperature of the laser pump source near 24℃, and the high-frequency laser is also used to realize the rapid switching of the wavelength, and in the case that the pulse frequency is 500Hz, the wavelength can be rapidly switched between 730nm and 875nm, that is, only the wavelength is changed and the rest of the experimental conditions remain unchanged.

3. The photoacoustic based neonatal brain imaging system of claim 1, wherein, The optical fiber is 1.2 m long, the light inlet is a circle with a diameter of 0.9 cm, the light outlet is a rectangle with a length of 40 mm and a width of 1 mm, the laser is converged into the optical fiber after being focused by a convex lens, and a uniform-energy rectangular laser with a length of 40 mm and a width of 1 mm is emitted at the light outlet of the optical fiber, and the laser energy is 2 mJ / cm 2 .

4. The photoacoustic based neonatal brain imaging system of claim 1, wherein, The ultrasonic transducer has 256 array elements and can be adjusted to a corresponding arc according to the head profile of different infants; the ultrasonic transducer and the skin can be tightly coupled by using ultrasonic coupling liquid; the multi-channel data acquisition card has 256 channels, and the amplification multiple of the signal is adjustable between 1dB and 100dB.

5. The photoacoustic based neonatal brain imaging system of claim 1, wherein, The multi-spectral linear unmixing algorithm specifically includes: performing photoacoustic imaging on the newborn brain by using 730nm and 875nm wavelength lasers respectively, and then substituting the imaging data into the formula of the relationship between the endogenous contrast agents to calculate the oxygenated hemoglobin, deoxyhemoglobin, total hemoglobin, oxygen saturation and water content.

6. The photoacoustic-based neonatal brain imaging system of claim 5, wherein, The imaging data is substituted into the formula (5)-(8) of the relationship between the endogenous contrast agents to calculate important hemodynamic parameter indexes such as oxygenated hemoglobin, deoxyhemoglobin, total hemoglobin, oxygen saturation and water content, which specifically includes: sO2 = f * sO 2,ti + (1 - f) * f * sO 2,to (7) wherein, is the photoacoustic signal intensity at position on the photoacoustic image at wavelength λ; ε is the absorption coefficient of water at wavelength λ; sO HbO (λ), ε HbR (λ), and represent the absorption coefficients of oxyhemoglobin, deoxyhemoglobin, and water at wavelength λ, respectively; sO2and [HbT] are the concentrations of oxyhemoglobin and total hemoglobin at position , respectively; sO 2,ti and sO 2,to are the average oxygen saturations of the tissue inlet (artery) and outlet (vein), respectively, and f is a coefficient of sO 2,ti ; where BF is the average blood flow of all blood vessels in the tissue and is designated as the average blood flow of the tissue, OC = MRO2is the average oxygen consumption (oxygen metabolism) of the entire tissue, [HbT] blood is the average total hemoglobin concentration calculated through the tissue, and V is the tissue volume.

7. A detection method based on the system of any one of claims 1-6, characterized in that, The method comprises the following steps: Step 1, turn on the laser and multi-channel data acquisition card, adjust the trigger mode of the data acquisition card to be passively triggered by the laser pulse, and then set the wavelength of the laser pulse to 730 nm and the related parameters of the pulsed laser and the sampling parameters of the data acquisition card; Step 2, apply appropriate ultrasonic coupling liquid on the infant brain detection position, wear the flexible ultrasonic transducer on the measured newborn brain, and ensure that the detection elements are in close contact with the newborn brain skin; Step 3, gradually turn on the high-frequency laser pump source and pulsed laser emission switch through the computer 1, and preheat the laser for about half an hour; Step 4, the pulsed laser is irradiated to the surface of the newborn brain through the convex lens and the optical fiber, and after the brain tissue absorbs the laser energy, it is further converted into heat energy, causing transient temperature change, further producing thermal expansion leading to local pressure change, generating ultrasonic waves; Step 5, use the wearable ultrasonic transducer to receive photoacoustic signals at multiple positions on the newborn brain; Step 6, the photoacoustic signals received by the ultrasonic transducer are transmitted wirelessly into the multi-channel data acquisition card for data processing; Step 7, maintain all experimental conditions unchanged, adjust the wavelength of the pulsed laser to 875 nm; Step 8, the collected photoacoustic data are combined with MATLAB software and finite element photoacoustic reconstruction algorithm to qualitatively judge whether the newborn brain tissue is diseased; Step 9, if the brain tissue reconstruction imaging is abnormal, further combine the multi-spectral linear unmixing algorithm to quantitatively determine the degree of brain lesion; Step 10, output the qualitative and quantitative reconstruction results in steps 8 and 9.

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