A method for measuring lung physiological function based on 129 Xe magnetic resonance

Abstract

This invention discloses a method based on 129 Xe MRI is a method for measuring lung physiological function, utilizing highly selective-dynamic exchange sampling sequences to acquire hyperpolarized lung tissue. 129 Magnetic resonance spectral data of Xe signal oscillations only need to cover 2-3 cardiac cycles, significantly shortening data acquisition time; further, from hyperpolarization... 129 Hyperpolarization was obtained from the magnetic resonance spectral data of the Xe signal oscillation. 129 The oscillation amplitude and frequency of the Xe signal, based on the gas-blood exchange model proposed in this invention, are used to establish formulas for lung physiological function parameters, and then based on hyperpolarization. 129 The oscillation amplitude and frequency of the Xe signal are used to calculate lung physiological function parameters; the method of this invention performs repeated sampling at large exchange time points and hyperpolarization. 129 The magnetic resonance spectral data with Xe signal oscillation has a higher signal-to-noise ratio; the method in this paper utilizes signal oscillation, so there is no need to avoid signal oscillation.

Description

Technical Field

[0001] This invention relates to the field of gas magnetic resonance technology, specifically to a method based on... 129 Xe magnetic resonance imaging is a method for measuring lung physiological function, suitable for rapid quantitative assessment of lung physiological function. Background Technology

[0002] Currently, traditional clinical lung assessment techniques have some limitations in measuring lung physiological function. Traditional pulmonary function tests can only provide coarse, global lung function information and cannot obtain detailed information at the alveolar and pulmonary vascular scale. While CT can provide structural information about the lungs, it is limited by the involvement of ionizing radiation and the lack of functional data. In addition, nuclear medicine techniques are not suitable as routine lung examination methods due to the use of radioactive materials. In contrast, MRI does not involve ionizing radiation or radioactivity and can assess the structure and function of human tissues. However, clinical MRI uses water protons as signals to observe the nucleus, while the lungs are mainly composed of cavities with low water content; therefore, traditional MRI techniques face challenges in assessing lung physiological function.

[0003] Hyperpolarization techniques, such as spin-exchange optical pumping, can significantly improve the performance of inert gases (e.g., 129 The polarization of Xe is measured, making gas magnetic resonance imaging possible. This is achieved by analyzing the hyperpolarization of inhaled gas in the lungs. 129 Xe gas in magnetic resonance imaging can provide information on lung ventilation function. Furthermore, because... 129 Xe can dissolve in alveolar walls, plasma, and erythrocytes, exhibiting different chemical shifts (197 ppm in tissue / plasma, i.e., the TP peak; and 212 ppm in erythrocytes, i.e., the RBC peak). Lung tissue samples were collected at different exchange times using Chemical Shift Saturation Recovery (CSSR) sequences. 129 Xe magnetic resonance spectroscopy, combined with gas-blood exchange models, such as the Model of Xenon Exchange (MOXE), can extract parameters including hematocrit (HCT) and pulmonary capillary transit time (t). X ) and the barrier-to-septal ratio (G / S) of the gas exchange membrane. Multiple lung physiological parameters, including )

[0004] However, CSSR technology also has some limitations and drawbacks, such as: (1) it requires the acquisition of magnetic resonance spectral data at multiple exchange time points, resulting in a long sampling time and difficulty in obtaining specific local gas-blood exchange function information; (2) cardiac motion can lead to dissolved state129 Fluctuations in the signal strength of Xe may affect the fitting effect of the gas-blood exchange model.

[0005] Existing research indicates that dissolved state 129 Xe magnetic resonance signals are highly sensitive to cardiac motion, exhibiting oscillatory characteristics synchronized with the heart's periodic activity, and the amplitude of these oscillations is associated with various lung diseases. These signal oscillations are thought to be caused by changes in pulmonary vascular bed volume due to cardiac motion. Based on this finding, theoretically, pulmonary physiological parameters (such as hemodialysis) could be measured by establishing the relationship between the intensity of dissolved-state signal oscillations and changes in the volume of red blood cells, plasma, and lung tissue. (etc.). However, this theoretical assumption has not yet been experimentally realized. Summary of the Invention

[0006] The purpose of this invention is to address the aforementioned problems in the prior art by providing a method based on... 129 Xe magnetic resonance imaging method for measuring lung physiological function.

[0007] The above-mentioned objectives of the present invention are achieved through the following technical means:

[0008] A type based on 129 The method for measuring lung physiological function using Xe magnetic resonance imaging includes the following steps:

[0009] Step 1: Acquire hyperpolarization using a highly selective dynamic exchange sampling sequence 129 Magnetic resonance spectral data of Xe signal oscillations;

[0010] Step 2: Hyperpolarization collected in Step 1 129 Hyperpolarization was obtained from the magnetic resonance spectral data of the Xe signal oscillation. 129 The oscillation amplitude and frequency of the Xe signal, hyperpolarization 129 The amplitude and frequency of the Xe signal oscillation include those dissolved in red blood cells when unaffected by cardiac activity. 129 Xe baseline signal strength M RBC_con When dissolved in lung tissue and plasma and unaffected by cardiac activity 129 Xe baseline signal strength M TP_con Red blood cells caused by cardiac activity 129 Xe signal oscillation amplitude M RBC_osc Lung tissue and plasma caused by cardiac exercise 129 Xe signal oscillation amplitude M TP_osc and the effects of cardiac activity 129 The frequency f of the Xe signal oscillation;

[0011] Step 3: Establish formulas for lung physiological function parameters, and then, based on the hyperpolarization obtained in Step 2... 129The oscillation amplitude and frequency of the Xe signal are used to calculate pulmonary physiological function parameters, including hematocrit (HCT) and the ratio of gas exchange membrane thickness to interpulmonary septal thickness. and the time of blood residence in the lungs (t) X .

[0012] As described above, step 1 specifically includes the following steps:

[0013] Step 1.1: The subject lies flat on the MRI scanning table and wears a lung support belt. 129 The Xe imaging coil enters the scanning magnet and is drawn into hyperpolarized... 129 Hold your breath after consuming Xe gas;

[0014] Step 1.2: High-selectivity - dynamic exchange sampling sequence will be dissolved in the state 129 The frequency center of the Xe signal is set to the RF center of each RF pulse, and RF pulses of a set repetition number are applied to excite the dissolved state. 129 Xe signal, to minimize the effect on gaseous state 129 The off-resonance effect of the Xe signal; radio frequency pulse-excited dissolved state 129 Xe signal and dynamic acquisition of hyperpolarization 129 The magnetic resonance spectral data of the Xe signal oscillation is repeated a set number of times;

[0015] The exchange time set in the high-selectivity dynamic exchange sampling sequence enables 129 Xe reaches a dynamic equilibrium in the gaseous, blood, and tissue states, and the exchange time is less than half of a complete cardiac cycle.

[0016] As described above, step 2 specifically includes the following steps:

[0017] Step 2.1: Fit the hyperpolarization data collected in Step 1 using peak segmentation. 129 The relationship between signal intensity and time in extracting erythrocyte RBC signals from Xe signal oscillation magnetic resonance spectroscopy data. RBC (t) and the relationship between signal intensity and time of TP signals in lung tissue and plasma. TP (t):

[0018]

[0019]

[0020] In the formula, It is caused by heart movement. 129 The phase of the Xe signal oscillation, T1 app The apparent relaxation time is T1;

[0021] Step 2.2: The relationship between the signal intensity and time of the erythrocyte RBC signal obtained in Step 2.1. RBC (t) and the relationship between signal intensity and time of TP signals in lung tissue and plasma M TP (t) Correction is performed for the apparent T1 relaxation time. The specific process is as follows:

[0022] Using the single exponential function exp(-t / T1) app The relationship between signal intensity and time of red blood cell RBC signal M RBC (t) and the relationship between signal intensity and time of TP signals in lung tissue and plasma. TP (t) is fitted to extract T1 app Then M RBC (t) and M TP (t) are multiplied by exp(t / T1) respectively app The relationship between signal intensity and time of erythrocyte RBC signal after apparent T1 relaxation time correction was obtained. RBC_cor And the relationship between signal intensity and time of TP signals in lung tissue and plasma after apparent T1 relaxation time correction. TP_cor :

[0023]

[0024]

[0025] Step 2.3, M at all time points RBC_cor After adding (t) and averaging, we get M. RBC_cor The mean M of (t) RBC_con M at all time points TP_cor After adding (t) and averaging, we get M. TP_cor The mean M of (t) TP_con Then M RBC_cor (t) and M TP_cor (t) minus M respectively RBC_con and M TP_con Then use the sine function Fit the residual signal to extract M RBC_osc M TP_osc f and

[0026] As mentioned above, in step 3, the hematocrit (HCT) is calculated based on the following formula:

[0027]

[0028] λ RBC yes 129 The solubility of Xe gas in red blood cells, λRBC It is 0.27; λ plasma yes 129 The solubility of Xe gas in blood plasma, λ plasma It is 0.09;

[0029] As mentioned above, in step 3, the thickness of the gas exchange membrane / lung septum is... Calculated based on the following formula:

[0030]

[0031] λ tissue yes 129 The solubility of Xe gas in the alveolar wall, λ tissue It is 0.20;

[0032] As mentioned above, the blood residence time t in the lungs in step 3 X Calculated based on the following formula:

[0033]

[0034] Compared with the prior art, the present invention has the following advantages:

[0035] 1. This invention uses a highly selective, dynamically exchanged sampling sequence to dynamically acquire hyperpolarization. 129 Xe magnetic resonance signals only need to cover 2-3 cardiac cycles, which significantly shortens the data acquisition time and enables rapid assessment of lung physiological function. Taking the rats in step 1.2 of Example 1 as an example, conventional CSSR takes about 4 seconds, while this method only needs to cover 2-3 cardiac cycles, which is about 0.5 seconds.

[0036] 2. Improve signal-to-noise ratio: This invention uses a sufficiently long switching time to enable... 129 Xe reaches dynamic equilibrium in the alveolar cavity, lung tissue, erythrocytes, and plasma. The method of this invention repeatedly samples at large exchange time points (greater than 20 ms), avoiding the low signal-to-noise ratio problem at small exchange times (0-20 ms), and hyperpolarization. 129 The magnetic resonance spectral data of Xe signal oscillations have a higher signal-to-noise ratio, thus improving the accuracy of the assessment. (Taking the rats in step 1.2 of Example 1 as an example, the exchange time points of conventional CSSR are distributed between 2-400 ms, while this method only applies to hyperpolarization at an exchange time of 50 ms.) 129 (The magnetic resonance spectral data of the Xe signal oscillations were repeatedly sampled.)

[0037] 3. Optimized gas-blood exchange model of the lungs: This invention is based on hyperpolarization caused by cardiac motion. 129The Xe magnetic resonance signal oscillation phenomenon leads to a novel gas-blood exchange model. Therefore, it eliminates the need to consider the impact of cardiac motion on the model's fitting performance, providing a new approach for accurately assessing lung physiological function. Conventional CSSR methods require multiple data acquisitions or repeated sampling to avoid signal oscillations, while this method utilizes signal oscillations themselves, thus eliminating the need to avoid them; in fact, the oscillation amplitude can be larger, further enhancing the advantages of this invention. (Taking steps 3.1 and 3.3 in Example 1 as examples, this method utilizes hyperpolarization caused by cardiac motion.) 129 Xe magnetic resonance signal fluctuations were used to extract HCT and t X Therefore, the signal oscillations caused by cardiac activity are not only harmless but also beneficial; and in step 3.2 The extraction uses the signal mean M of RBC and TP after correcting for apparent T1. RBC_con and M TP_con This also reduces the impact of cardiac activity. Attached image description:

[0038] Figure 1 This is a flowchart of the method of the present invention;

[0039] Figure 2 This is a schematic diagram of the highly selective dynamic exchange sampling sequence in step 1 of Embodiment 1 of the present invention (where RF represents a radio frequency pulse, and 90°@dissove represents the response to the dissolved state). 129 A 90° radio frequency pulse is applied to the frequency center of Xe; Grad represents the damage gradient; ADC represents analog-to-digital signal conversion.

[0040] Figure 3 The signal intensity of the erythrocyte RBC signal in step 2 of Embodiment 1 of the present invention, and the relationship between the signal intensity of the erythrocyte RBC signal after apparent T1 relaxation time correction and time. RBC_cor Resulting graph;

[0041] Figure 4 The use of a sine function in step 2 of embodiment 1 of the present invention. For M RBC_cor (t) minus M RBC_con The fitting result of fitting the residual signal;

[0042] Figure 5 This is a schematic diagram of the lung gas-blood exchange model in step 3 of Embodiment 1 of the present invention (where Tissue represents the gas-blood exchange membrane composed of lung tissue with a thickness of δ, RBC and Plasma represent red blood cells and plasma in pulmonary vessels, respectively, and the gas-blood exchange membrane and pulmonary vessels together form the pulmonary septum with a thickness of d). Detailed implementation method:

[0043] To facilitate understanding and implementation of the present invention by those skilled in the art, the present invention will be further described in detail below with reference to examples. It should be understood that the embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0044] Example 1:

[0045] A type based on 129 The method for measuring lung physiological function using Xe magnetic resonance imaging includes the following steps:

[0046] Step 1: Utilize highly selective dynamic exchange sampling sequences (i.e., dynamic over time, continuously monitoring 2-3 complete cardiac cycles (i.e., the time interval between one heartbeat) to observe the dissolved state. 129 (Dynamic changes in the Xe signal) Acquisition of hyperpolarization 129 The magnetic resonance spectral data of Xe signal oscillations specifically includes the following steps:

[0047] Step 1.1: The subject lies flat on the MRI scanning table and wears a lung support belt. 129 The Xe imaging coil enters the scanning magnet and is drawn into hyperpolarized... 129 Hold your breath after consuming Xe gas.

[0048] Step 1.2: High-selectivity - dynamic exchange sampling sequence will be dissolved in the state 129 The frequency center of the Xe signal is set to the RF center of each RF pulse, and a highly selective RF pulse with a set number of repetitions is applied to excite the dissolution state. 129 Xe signal, to minimize the effect on gaseous state 129 The off-resonance effect of the Xe signal; radio frequency pulse-excited dissolved state 129 Xe signal and dynamic acquisition of hyperpolarization 129 The magnetic resonance spectral data of the Xe signal oscillations were repeated a set number of times to ensure that at least 2-3 complete cardiac cycles were covered;

[0049] The time interval between two radio frequency pulses is called the switching time. A high-selectivity dynamic switching sampling sequence is configured with sufficient switching time to... 129 Xe reaches a dynamic equilibrium in the gas, blood, and tissues; and the exchange time is strictly controlled within half of a complete cardiac cycle to meet the Nyquist sampling requirements for cardiac motion.

[0050] When the subjects were rats, the following parameters were used: exchange time set to 50 ms, radiofrequency pulse center frequency set to 205 ppm, radiofrequency pulse flip angle set to 90°, sampling bandwidth set to 600 ppm, number of sampling points set to 1024, and number of repetitions set to 50. For human subjects, the following parameters were used: exchange time set to 150 ms, radiofrequency pulse center frequency set to 208 ppm, radiofrequency pulse flip angle set to 90°, sampling bandwidth set to 600 ppm, number of sampling points set to 1024, and number of repetitions set to 20. For other animals, the parameters need to be adjusted according to the species' heart rate, etc. 129 Xe's signal recovery rate, and 129 The chemical shift of Xe is adjusted according to the relevant parameters.

[0051] Step 2: Hyperpolarization collected in Step 1 129 Hyperpolarization was obtained from the magnetic resonance spectral data of the Xe signal oscillation. 129 The oscillation amplitude and frequency of the Xe signal, hyperpolarization 129 The amplitude and frequency of the Xe signal oscillation include those dissolved in red blood cells when unaffected by cardiac activity. 129 Xe baseline signal strength M RBC_con When dissolved in lung tissue and plasma and unaffected by cardiac activity 129 Xe baseline signal strength M TP_con Red blood cells caused by cardiac activity 129 Xe signal oscillation amplitude M RBC_osc Lung tissue and plasma caused by cardiac exercise 129 Xe signal oscillation amplitude M TP_osc and the effects of cardiac activity 129 The frequency f of the Xe signal oscillation specifically includes the following steps:

[0052] Step 2.1: Fit the hyperpolarization data collected in Step 1 using peak segmentation. 129 Extracting the signal intensity of erythrocyte RBC signals (i.e., signals dissolved in erythrocytes) from the magnetic resonance spectroscopy data of Xe signal oscillations. 129 The relationship between the signal strength of Xe signal and time M RBC (t) and the signal intensity of TP signals in lung tissue and plasma (i.e., dissolved in lung tissue and plasma). 129 The relationship between the signal strength of Xe signal and time M TP (t):

[0053]

[0054]

[0055] In the formula, M RBC_conThis indicates the state when dissolved in red blood cells without being affected by cardiac activity. 129 Xe baseline signal strength, M TP_con This indicates the amount dissolved in lung tissue and blood plasma when unaffected by cardiac activity. 129 Xe baseline signal strength, M RBC_osc Indicates the red blood cells caused by heart movement 129 Xe signal oscillation amplitude, M TP_osc This indicates the amount of blood in lung tissue and plasma caused by cardiac activity. 129 Xe signal oscillation amplitude, f and These represent the effects caused by cardiac activity. 129 The frequency and phase of the Xe signal oscillation, T1 app The apparent T1 relaxation time is taken into account factors such as radio frequency, oxygen concentration, and gas exchange.

[0056] Step 2.2: The relationship between the signal intensity and time of the erythrocyte RBC signal obtained in Step 2.1. RBC (t) and the relationship between signal intensity and time of TP signals in lung tissue and plasma. TP (t) Correction is performed for the apparent T1 relaxation time. The specific process is as follows:

[0057] Using the single exponential function (exp(-t / T1)) app The hyperpolarization data collected in step 1 were analyzed separately. 129 The signal intensity versus time relationship of TP signals extracted from lung tissue and plasma using magnetic resonance spectroscopy data of Xe signal oscillations. TP (t) and the relationship between the signal intensity of erythrocyte RBC signal and time M RBC (t) is fitted to extract T1 app Use the obtained T1 app Relationship between signal intensity and time of erythrocyte RBC signal M RBC (t) and the relationship between signal intensity and time of TP signals in lung tissue and plasma. TP (t) is corrected (i.e., M) RBC (t) and M TP (t) are multiplied by (exp(t / T1) respectively app The corrected signal expression is obtained as follows:

[0058]

[0059]

[0060] In the formula, M RBC_cor This describes the relationship between the signal intensity and time of erythrocyte RBC signals after epigenetic T1 relaxation time correction. TP_corThis represents the relationship between the signal intensity and time of TP signals in lung tissue and plasma after apparent T1 relaxation time correction.

[0061] Step 2.3, M at all time points RBC_cor After adding (t) and averaging, we get M. RBC_cor The mean M of (t) RBC_cor (i.e., dissolved in red blood cells when not affected by cardiac activity) 129 Xe baseline signal strength), M at all time points TP_cor After adding (t) and averaging, we get M. TP_cor The mean M of (t) TP_con (i.e., dissolved in lung tissue and plasma without being affected by cardiac activity) 129 Xe baseline signal strength), then M RBC_cor (t) and M TP_cor (t) minus M respectively RBC_con and M TP_con Then use the sine function Fit the residual signal to extract M RBC_osc M TP_osc f and

[0062] Step 3: Based on the gas-blood exchange model proposed in this invention, establish formulas for lung physiological function parameters, and then, based on the hyperpolarization obtained in Step 2... 129 The oscillation amplitude and frequency of the Xe signal are used to calculate pulmonary physiological function parameters, including hematocrit (HCT) and the ratio of gas exchange membrane thickness to interpulmonary septal thickness. and the time of blood residence in the lungs (t) X Specifically, it includes the following steps:

[0063] The gas-blood exchange model proposed in this invention is as follows: the gas-blood exchange region includes lung tissue and pulmonary vessels, the pulmonary vessels include plasma and red blood cells, the thickness of the gas-blood exchange region is d, the thickness of the lung tissue is δ, and the thickness of the pulmonary vessels is d-2δ.

[0064] Step 3.1: Extract hematocrit (HCT) of erythrocytes. The specific process is as follows:

[0065] Hematocrit (HCT) is calculated based on the following formula:

[0066]

[0067] In the formula, V RBC and V plasma These represent the volume of red blood cells and the volume of blood plasma, respectively.

[0068] The subject inhaled hyperpolarization 129After Xe gas, hyperpolarization 129 Xe gas dissolves in lung tissue (i.e., alveolar walls), red blood cells, and plasma, reaching dynamic equilibrium after sufficient exchange time. 129 The signal intensity of the Xe signal is proportional to the volume of the alveolar wall, plasma, and red blood cells, that is:

[0069] M=kλV (6)

[0070] In the formula, M represents the amount dissolved in the alveolar wall, plasma, or red blood cells. 129 The signal strength of the Xe signal, k represents the signal coefficient (related to polarization, hardware performance, and acquisition parameters), and λ represents... 129 The solubility of Xe gas in the alveolar wall, plasma, or red blood cells, where V represents the volume of the alveolar wall, plasma, or red blood cells. Therefore, the volume of red blood cells is V. RBC for:

[0071]

[0072] In the formula, M RBC Indicates dissolved in red blood cells 129 The signal strength of the Xe signal, λ RBC express 129 The solubility of Xe gas in erythrocytes, according to literature reports, λ RBC It is 0.27.

[0073] Volume V of alveolar walls tissue for:

[0074]

[0075] In the formula, M tissue This indicates that it dissolves in the alveolar walls. 129 The signal strength of the Xe signal, λ tissue express 129 The solubility of Xe gas in the alveolar walls, according to literature reports, λ tissue It is 0.20.

[0076] Blood plasma volume V plasma for:

[0077]

[0078] In the formula, M plasma Indicates dissolved in blood plasma 129 The signal strength of the Xe signal, λ plasma express 129 The solubility of Xe gas in blood plasma, according to literature reports, λ plasma It is 0.09.

[0079] Substituting formulas (7) and (9) into formula (5), we get:

[0080]

[0081] Considering that cardiac exercise has a relatively small impact on the hematocrit (HCT) of pulmonary vessels, and given the relative stability of hemodynamics, the composition of the fresh blood pumped into the pulmonary vessels during one cardiac cycle is essentially the same as the existing blood in the pulmonary vessels. Therefore, the HCT of the fresh blood pumped into the pulmonary vessels due to cardiac exercise can be used as a measure of HCT. OSC Hematocrit (HCT) is the total blood volume present in the pulmonary vessels. OSC =HCT, the hematocrit of fresh blood pumped into the pulmonary vessels by the heart. OSC Calculated using the following formula:

[0082]

[0083] In the formula, M plasma_osc This indicates the plasma signal caused by cardiac activity (i.e., in the plasma) 129 The amplitude of the Xe signal oscillation.

[0084] In addition, because of the TP signal in lung tissue and plasma 129 The contribution of Xe signaling mainly comes from lung tissue and plasma, while cardiac exercise primarily causes changes in the volume of plasma and red blood cells within blood vessels. Therefore, cardiac exercise-induced changes in the volume of Xe signaling in lung tissue and plasma... 129 The Xe signal oscillation amplitude can be considered as the signal oscillation amplitude of the plasma signal, i.e., M. TP_osc =M plasma_osc ,therefore:

[0085]

[0086] In the formula, M RBC_osc It is the red blood cells extracted in step 2 caused by cardiac movement 129 Xe signal oscillation amplitude, M TP_osc It is the lung tissue and plasma extracted in step 2 caused by cardiac motion. 129 Xe signal oscillation amplitude; extract M RBC_osc and M TP_osc Substituting into formula (12), HCT can be calculated.

[0087] Step 3.2: Extract the thickness of the gas-blood exchange membrane / tissue septum. The specific process is as follows:

[0088] The gas-blood exchange model proposed in this invention (e.g.) Figure 5 (As shown), gas exchange membrane thickness / tissue septum thickness Based on the following formula:

[0089]

[0090] Combining formulas (7), (8), and (9), we can obtain:

[0091]

[0092] Furthermore, because the collected TP signals from lung tissue and plasma include both plasma signals and lung tissue signals (i.e., signals from lung tissue)... 129 Xe signal), that is:

[0093]

[0094] Combining formulas (5), (7), and (9), M plasma Use M RBC And HCT representation, we can obtain:

[0095]

[0096] The relationship between signal intensity and time of erythrocyte RBC signals after epigenetic T1 relaxation time correction in step 2.2 is used. RBC_cor The mean M RBC_con Let M in formula (16) represent RBC The relationship between signal intensity and time of lung tissue and plasma TP signals after apparent T1 relaxation time correction in step 2.2 is shown in Figure M. TP_cor The mean M TP_con Let M in formula (16) represent TP We can obtain:

[0097]

[0098] λ RBC yes 129 The solubility of Xe gas in red blood cells, λ RBC It is 0.27, λ tissue yes 129 The solubility of Xe gas in the alveolar wall, λ tissue λ is 0.20. plasma express 129 The solubility of Xe gas in blood plasma, λ plasma The value is 0.09, and HCT is the hematocrit obtained in step 3.1. Substituting these values ​​into formula (17) allows us to calculate the gas exchange membrane thickness / tissue septum thickness.

[0099] Step 3.3: Extracting the lung blood residence time t XThe specific process is as follows:

[0100] Lung blood residence time t X Calculated based on the following formula:

[0101] t X =V RBC_con / Q (18)

[0102] Among them, V RBC_con Q is the volume of all red blood cells in the pulmonary vessels without considering cardiac activity, and Q is the red blood cell flow velocity in the lungs per unit time. The expression for Q is:

[0103]

[0104] In the formula, f(t) represents the change in erythrocyte flow velocity in pulmonary vessels with time t, and f(t) is based on the following formula:

[0105]

[0106] In the formula, v represents the baseline flow velocity of red blood cells in the pulmonary vessels without considering cardiac activity. RBC_osc It is the amount of change in the velocity of red blood cells in the pulmonary vessels caused by cardiac activity, f and The cardiac motion extracted in step 2 is respectively caused by 129 The frequency and phase of the Xe signal oscillation.

[0107] The waveform of f(t), a function of the velocity of erythrocytes in pulmonary vessels changing with time t, is similar to a sine function. To simplify the model, we assume the lowest velocity of pulmonary blood flow is 0, so the trough of f(t), a function of the velocity of erythrocytes in pulmonary vessels changing with time t, is 0, i.e., vv RBC_osc =0 (at the trough) (where -1). Formula (18) can be simplified to:

[0108]

[0109] The observation time of this invention is greater than or equal to 2-3 cardiac cycles, and the observation time t is relatively long, so the pulmonary blood retention time t during the time interval 0 to t can be used. X The average value is used to represent the lung blood residence time t. X That is, the time it takes for blood to remain in the lungs (t). X It can be calculated using the following formula:

[0110]

[0111] Next, we need to v RBC_osc The process of transforming it into other easily measurable variables is as follows:

[0112] Without considering cardiac activity, the flow rate v of red blood cells entering the pulmonary vessels in and the flow rate v of red blood cells leaving the pulmonary vessels out The following relationship exists:

[0113] v in =v out =v (23)

[0114] However, due to heart movement, v in and v out There are differences; the volume of red blood cells in pulmonary vessels fluctuates periodically over time, namely:

[0115]

[0116] For V RBC When (t) reaches its maximum value, we have:

[0117]

[0118] And because:

[0119] V RBC_max =V RBC_con +V RBC_osc (26)

[0120] In the formula, V RBC_osc This indicates the amount of change in the volume of red blood cells in the pulmonary blood vessels due to cardiac activity.

[0121] Combining formulas (22), (25), and (26), we can obtain:

[0122]

[0123] V in the formula RBC_con and V RBC_osc Combining formula (6) with the above, we can obtain:

[0124]

[0125]

[0126] Substituting formulas (28) and (29) into formula (27), we get:

[0127]

[0128] In the formula, M RBC_osc It is the red blood cells extracted in step 2 caused by cardiac movement 129 Xe signal oscillation amplitude, M RBC_conThe relationship between signal intensity and time of erythrocyte RBC signal after epigenetic T1 relaxation time correction in step 2 is M. RBC_cor The mean of M in step 2 RBC_osc and M RBC_con Substituting into formula (30), the blood residence time t in the lungs can be calculated. X .

[0129] A type based on 129 The Xe MRI lung physiological function measurement device includes:

[0130] The first parameter calculation module is used to implement step 2 above: from the acquired hyperpolarization... 129 Hyperpolarization was obtained from the magnetic resonance spectral data of the Xe signal oscillation. 129 The oscillation amplitude and frequency of the Xe signal, hyperpolarization 129 The amplitude and frequency of the Xe signal oscillation include those dissolved in red blood cells when unaffected by cardiac activity. 129 Xe baseline signal strength M RBC_con When dissolved in lung tissue and plasma and unaffected by cardiac activity 129 Xe baseline signal strength M TP_con Red blood cells caused by cardiac activity 129 Xe signal oscillation amplitude M RBC_osc Lung tissue and plasma caused by cardiac exercise 129 Xe signal oscillation amplitude M TP_osc and the effects of cardiac activity 129 The frequency f of the Xe signal oscillation;

[0131] The second parameter calculation module is used to implement step 3 above: establishing formulas for lung physiological function parameters, and then based on hyperpolarization. 129 The oscillation amplitude and frequency of the Xe signal are used to calculate pulmonary physiological function parameters, including hematocrit (HCT) and the ratio of gas exchange membrane thickness to interpulmonary septal thickness. and the time of blood residence in the lungs (t) X .

[0132] A terminal, comprising a processor and a storage medium;

[0133] The storage medium is used to store instructions;

[0134] The processor is used to operate according to the instructions to execute steps 2 and 3.

[0135] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements steps 2 and 3.

[0136] It should be noted that the specific embodiments described in this invention are merely illustrative of the spirit of the invention. Those skilled in the art to which this invention pertains can make various modifications or additions to the described specific embodiments or use similar methods to substitute them, without departing from the spirit of the invention or exceeding the scope defined by the appended claims.

Claims

1. A method based on 129 The method for measuring lung physiological function using Xe magnetic resonance imaging is characterized by, Includes the following steps: Step 1, acquisition of hyperpolarization using high selectivity - dynamic exchange sampling sequence 129 magnetic resonance spectroscopy data of Xe signal oscillation; Step 2: Hyperpolarization collected in Step 1 129 Hyperpolarization was obtained from the magnetic resonance spectral data of the Xe signal oscillation. 129 The oscillation amplitude and frequency of the Xe signal, hyperpolarization 129 The amplitude and frequency of the Xe signal oscillation include those dissolved in red blood cells when unaffected by cardiac activity. 129 Xe baseline signal strength When dissolved in lung tissue and plasma and unaffected by cardiac activity 129 Xe baseline signal strength Red blood cells caused by cardiac activity 129 Xe signal oscillation amplitude Lung tissue and plasma caused by cardiac exercise 129 Xe signal oscillation amplitude and the effects of cardiac activity 129 The frequency of Xe signal oscillation ; Step 3: Establish formulas for lung physiological function parameters, and then, based on the hyperpolarization obtained in Step 2... 129 The oscillation amplitude and frequency of the Xe signal are used to calculate lung physiological function parameters, including hematocrit in the lungs. Gas exchange membrane thickness / lung septum thickness and the time blood stays in the lungs , Step 1 specifically includes the following steps: Step 1.1: The subject lies flat on the MRI scanning table and wears a lung support belt. 129 The Xe imaging coil enters the scanning magnet and is drawn into hyperpolarized... 129 Hold your breath after consuming Xe gas; Step 1.2: The highly selective dynamic exchange sampling sequence will be dissolved in the state. 129 The frequency center of the Xe signal is set to the RF center of each RF pulse, and RF pulses of a set repetition number are applied to excite the dissolution state. 129 Xe signal, to minimize the effect on gaseous state 129 The off-resonance effect of the Xe signal; radio frequency pulse-excited dissolved state 129 Xe signal and dynamic acquisition of hyperpolarization 129 The magnetic resonance spectral data of the Xe signal oscillation is repeated a set number of times; The exchange time set in the high-selectivity dynamic exchange sampling sequence enables 129 Xe reaches a dynamic equilibrium in the gaseous, blood, and tissue states, and the exchange time is less than half of a complete cardiac cycle. The hematocrit in step 3 Calculated based on the following formula: yes 129 The solubility of Xe gas in red blood cells It is 0.27; yes 129 Solubility of Xe gas in blood plasma It is 0.09; In step 3, the thickness of the gas exchange membrane / lung septum is mentioned. Calculated based on the following formula: yes 129 Solubility of Xe gas in alveolar walls It is 0.20; The pulmonary blood residence time in step 3 Calculated based on the following formula: 。 2. A method based on claim 1 129 The method for measuring lung physiological function using Xe magnetic resonance imaging is characterized by, Step 2 specifically includes the following steps: Step 2.1: Fit the hyperpolarization data collected in Step 1 using peak segmentation. 129 Relationship between signal intensity and time in extracting erythrocyte RBC signals from Xe signal oscillation magnetic resonance spectroscopy data and the relationship between signal intensity and time of TP signals in lung tissue and plasma. : wherein is the heart motion induced 129 the phase of the Xe signal oscillation, is the apparent T1 relaxation time; Step 2.

2. Signal intensity versus time relationship of the RBC signal obtained in step 2.1 Signal intensity versus time relationship of the lung tissue and plasma TP signal The correction of apparent Tl relaxation time was performed as follows: Using a single exponential function Relationship between signal intensity and time of erythrocyte RBC signal and the relationship between signal intensity and time of TP signals in lung tissue and plasma. Perform fitting and extract Then and Multiply by respectively The relationship between signal intensity and time of erythrocyte RBC signals after epigenetic T1 relaxation time correction was obtained. And the relationship between signal intensity and time of TP signals in lung tissue and plasma after apparent T1 relaxation time correction. : Step 2.3, under all time points After adding them together, we take the average to get... mean Under all time points After adding them together, we take the average to get... mean Then and Subtract respectively and Then use the sine function Fit the residual signal to extract , , ,as well as .

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