A method for optimizing infant brain t2-weighted magnetic resonance imaging

Abstract

The application discloses an infant brain T2 weighted magnetic resonance imaging optimization method based on a fast spin echo sequence. First, T1, T2 and PD quantitative imaging of the infant brain from 0 to 24 months old is collected to obtain T1, T2 and PD values of the infant brain white matter and gray matter regions, and according to the relationship characteristics of the infant brain white matter T2 value and the gray matter T2 value, the infant is divided into different month groups. Then, based on the 3D T2 weighted imaging of the variable flip angle fast spin echo sequence, the signal intensity of the infant brain white matter and gray matter under different refocusing flip angle chains is calculated through an extended phase graph algorithm, and the best flip angle chain design scheme of each group is determined with the maximum white matter / gray matter contrast as the target. The application fills the blank of the infant brain T2 weighted imaging optimization, formulates the best flip angle chain optimization scheme of different month groups, and thus significantly improves the contrast of the infant brain T2 weighted imaging.

Description

Technical Field

[0001] This application relates to the field of brain magnetic resonance imaging optimization, and in particular to T2-weighted imaging optimization of infant brains. Background Technology

[0002] Magnetic resonance imaging (MRI) of the infant brain is a safe and widely used method for examining the structure, function, and early developmental disorders of infants and young children. However, due to the poor contrast in infant brain images, and the rapid changes in image contrast caused by rapid brain development within the first two years after birth, it is difficult to distinguish between gray and white matter in infants and young children, making automated image segmentation challenging. Because the myelin sheath of white matter (WM) is immature at birth, leading to prolonged T2 relaxation time, the contrast between white matter and gray matter (GM) in T2-weighted (T2w) images of the neonatal brain (≤1 month) is opposite to that of the adult brain. In older infants, the contrast is similar to that of adults. Before this reversal occurs, there is a period of time during which WM and GM signals are similar, causing most segmentation algorithms to fail; this period typically occurs between 6 and 10 months.

[0003] Currently, there are few studies on optimizing T2-weighted imaging of the brains of infants aged 0-24 months. Only one study optimized contrast by adjusting TE and TR; however, this method sacrifices signal-to-noise ratio and significantly prolongs scan time, reducing image acquisition efficiency, making it unsuitable for clinical scanning. Therefore, this study, based on fast spin echo imaging sequences, utilizes the flexibility of variable flip-chain control to optimize imaging contrast. A method is designed to iteratively calculate the flip-chain corresponding to the signal required for a specific T2 level using both extended and reverse extended phase maps, resulting in the optimal gray-white matter contrast design for different age groups. This method optimizes contrast by altering the signal evolution pattern, significantly improving the contrast of T2-weighted images of infant brains without affecting signal-to-noise ratio or acquisition efficiency, and can be applied to clinical MRI scans. Summary of the Invention

[0004] To improve the contrast of T2w images of infant brains from 0-24 months, this invention proposes a method for optimizing T2w magnetic resonance imaging of infant brains. The method first acquires quantitative T1, T2, and proton density (PD) images of the brains of infants aged 0-24 months, obtaining the average T1, T2, and PD values ​​of the brain's wm (wing mass) and GM (gross proton density). Based on the relationship between the WM T2 and GM T2 values, infants are divided into different age groups. Next, the WM and GM signals under different flip-chain angles are calculated using extended phase graphs (EPG). Subsequently, the optimal flip-chain angle optimization scheme is determined for each age group. Finally, this optimal flip-chain angle optimization scheme is applied to the target infant brain for 3D T2w magnetic resonance imaging. This invention fills the gap in the optimization of T2-weighted imaging of infants aged 0-24 months. Based on the relationship between the T2 values ​​of white and gray matter in the infant brain, infants are divided into different age groups, and the optimal flip-angle chain optimization scheme is then identified for each age group, significantly improving the contrast of T2-weighted imaging of the infant brain. This method is beneficial for the anatomical delineation of the infant brain and the detection of diseases, and its simplicity makes it convenient for routine clinical examinations.

[0005] To achieve the above objectives, the present invention employs the following technical solution:

[0006] In a first aspect, the present invention provides an optimized method for T2-weighted magnetic resonance imaging of infant brains based on fast spin echo sequences, comprising the following steps:

[0007] S1: Collect quantitative imaging magnetic resonance data of longitudinal relaxation time (T1), transverse relaxation time (T2) and proton density (PD) of the brain of infants aged 0-24 months to obtain the average T1 value, average T2 value and average PD value of white matter and gray matter of each infant's brain.

[0008] S2: Based on the relative differences between the average T2 value of white matter and the average T2 value of gray matter in the brains of infants and young children in each sample, the 0-24 month age range of infants and young children is divided into different age groups; the quantitative imaging magnetic resonance data collected in S1 is re-divided according to each age group, and then the average T1 value, average T2 value and average PD value of white matter and gray matter in the brains of infants and young children in each age group are calculated respectively.

[0009] S3: Based on the average T1 value, average T2 value and average PD value of the white matter and gray matter of the infant brain in each age group, the signal intensity of the white matter and gray matter of the infant brain generated by the 3DT2 weighted fast spin echo sequence under each optional flip-angle chain is calculated by the extended phase map (EPG) algorithm.

[0010] S4: The signal intensity of the white and gray matter of the infant brain in each age group obtained in S3 under each optional flipped corner chain is converted into the contrast of white and gray matter. According to the principle of maximizing contrast, the best flipped corner chain for each age group is selected from all optional flipped corner chains for T2-weighted magnetic resonance imaging of the infant brain.

[0011] Based on the solution in the first aspect described above, the following preferred implementation methods can be further provided for each step. It should be noted that the technical features in each preferred method can be combined with each other as long as there is no conflict. Of course, these preferred methods can also be implemented in other ways that achieve the same technical effect, and this does not constitute a limitation.

[0012] As a preferred embodiment of the first aspect above, the calculation methods for the average T1 value, average T2 value, and average PD value in step S1 are as follows:

[0013] S101: Collect quantitative T1, T2 and PD magnetic resonance imaging data of the brains of several infants aged 0-24 months;

[0014] S102: Based on the quantitative imaging magnetic resonance data of each infant's brain, delineate the regions of interest in the gray matter of the cerebral cortex and the white matter of the subcortical cerebral cortex;

[0015] S103: Based on the regions of interest (ROIs) delineated in the quantitative imaging magnetic resonance imaging (MRI) data of each infant's brain, calculate the average T1 value within the ROI of the subcortical white matter as the average T1 value of the infant's brain white matter; calculate the average T2 value within the ROI of the subcortical white matter as the average T2 value of the infant's brain white matter; calculate the average PD value within the ROI of the subcortical white matter as the average PD value of the infant's brain white matter; calculate the average T1 value within the ROI of the cortical gray matter as the average T1 value of the infant's brain gray matter; calculate the average T2 value within the ROI of the cortical gray matter as the average T2 value of the infant's brain gray matter; calculate the average PD value within the ROI of the cortical gray matter as the average PD value of the infant's brain gray matter.

[0016] As a preferred embodiment of the first aspect above, the method for grouping infants by age in step S2 is as follows:

[0017] Based on the dynamic changes in T2 values ​​of white and gray matter in the brains of infants at different ages as a function of brain development, the infants were divided into three-month age groups. The relative high and low values ​​of the three groups are as follows:

[0018] In the first group, the T2 value of white matter in the brain of infants of this age group was higher than the T2 value of gray matter in the brain of infants.

[0019] In the second group, the T2 value of the white matter in the brain of infants of this age group was close to the T2 value of the gray matter in the brain of infants.

[0020] In the third group, the T2 value of the white matter in the brain of infants of this age group was lower than that of the gray matter in the brain.

[0021] As a preferred embodiment of the first aspect above, the three age groups are 0-6 months (i.e., 0-180 days after birth), 6-12 months (i.e., 181-360 days after birth), and 12-24 months (i.e., 361-720 days after birth).

[0022] As a preferred embodiment of the first aspect above, the specific implementation steps of step S3 are as follows:

[0023] S301, For cases containing four key angles α first α min α cent α max The flipped angle chain, fixed α max The angle value, and in α min and α cent Sampling is performed within their respective angular ranges to construct a series of optional angle combinations, each of which corresponds to α. min α cent and α max A set of fixed values, α min It must be less than α cent ; where α first α is the first angle on the entire flipped angle chain. min It is the fifth angle on the entire flipped angle chain, and also the smallest angle on the flipped angle chain; α cent The flip angle corresponding to the echo signal at the center of K-space at that moment; α max This is the last corner of the flipped corner chain;

[0024] S302: For each possible angle combination, determine α... min α cent and α max Let S be the calculated static pseudo-steady-state signal value achievable in a fast spin echo sequence with a constant flip angle, α. SPSS The calculation formula is:

[0025]

[0026] Where P(·) is the Legendre polynomial;

[0027] Then take α respectively min α cent α max The static pseudo-steady-state signal value S obtained at that time SPSS These are the echo signal values ​​S corresponding to the three angles on the static pseudo-steady-state signal curve, respectively.min S cent S max ; and based on S min Calculate α corresponding to the current available angle combination first The calculation formula is:

[0028]

[0029]

[0030] Then, S is calculated using progressive interpolation. first With S min The static pseudo-steady-state signal between them is used to calculate S by asymptotic interpolation. min With S cent The static pseudo-steady-state signal values ​​between the two are calculated by linear interpolation. cent With S max The static pseudo-steady-state signal values ​​between these values ​​are used to obtain the static pseudo-steady-state echo signal chain corresponding to the currently selectable angle combination;

[0031] S303. For each static pseudo-steady-state echo signal chain corresponding to each optional angle combination, ignoring the longitudinal recovery and lateral attenuation process of the magnetization vector, T1 = 0 and T2 = ∞, the required flip angle chain for the static pseudo-steady-state echo signal chain is calculated using the inverse-EPG algorithm of the extended phase diagram; the flip angle chains calculated for all optional angle combinations are all optional flip angle chains for each age group.

[0032] S304: For each age group, based on the preset echo time (TE), flip-angle chain length (ETL), and echo interval (ESP) in the fast spin echo sequence, and using the average T1, average T2, and average PD values ​​of the white matter in the brain of infants in that age group, the Extended Phase Map (EPG) algorithm is used to calculate the average signal intensity S of white matter voxels at the moment when the 3D T2-weighted fast spin echo sequence fills the center point of K-space. WM Simultaneously, based on the average T1, average T2, and average PD values ​​of the gray matter in the brains of infants in this age group, the average signal intensity S of gray matter voxels at the moment when the 3D T2-weighted fast spin echo sequence fills the center point of K-space was calculated using the extended phase map (EPG) algorithm. GM .

[0033] As a preferred embodiment of the first aspect described above, the α max The angle value is fixed between 100 and 180 degrees, preferably 120 degrees.

[0034] As a preferred embodiment of the first aspect above, the optimal method for optimizing the flipping corner chain in step S4 for each age group is as follows:

[0035] S401: For each age group, calculate the image contrast under each flip angle chain, where absolute contrast = |S WM |-|S GM |, relative contrast = (|S WM |-|S GM |) / (|S WM |+|S GM |);

[0036] S402: For each age group, with improving relative contrast (RC) as the primary optimization objective and improving absolute contrast (AC) as the secondary optimization objective, and with the specific absorption rate (SAR) value meeting the specified range as the constraint, the optimal flip-angle chain is selected from all the corresponding optional flip-angle chains, and is used as the flip-angle chain selected for T2-weighted magnetic resonance imaging of the brain of infants in that age group.

[0037] As a preferred embodiment of the first aspect above, in S402, when selecting the best flip-corner chain from all available flip-corner chains for each age group, firstly, selectable flip-corner chains whose specific absorption rate (SAR) value does not meet the first limiting range or whose absolute contrast ratio (AC) does not meet the second limiting range are eliminated, and then the selectable flip-corner chain with the highest relative contrast ratio (RC) is selected from the remaining selectable flip-corner chains as the best flip-corner chain for that age group.

[0038] Secondly, this invention provides a method for T2-weighted magnetic resonance imaging of the infant brain based on fast spin echo sequences, specifically: selecting the optimal flipped angle chain corresponding to the target infant's current age group for 3D T2-weighted magnetic resonance imaging; wherein, if the current age is 0-6 months, the α value of the optimal flipped angle chain during 3D T2-weighted magnetic resonance imaging is... min Set to 80°, α cent Set to 90°; for infants aged 6-12 months, the optimal flip angle α for 3D T2-weighted magnetic resonance imaging is... min Set to 50°, α cent Set to 110°; for infants aged 12-24 months, the optimal flip angle α for 3D T2-weighted magnetic resonance imaging is... min Set to 50°, α cent Set to 110°; α in the three-month-old group max All are set to 120°, α first All based on α min The corresponding static pseudo-steady-state signal value S SPSS To be confirmed.

[0039] As a preferred option in the second aspect mentioned above, in the three-month-old group, the other parameters were set the same for 3D T2-weighted magnetic resonance imaging, with echo time (TE) set to 370ms, flip angle chain length (ETL) set to 180, and echo interval (ESP) set to 3.7ms.

[0040] Compared to existing technologies, this invention has the following characteristics: This invention is the first to achieve optimized T2w imaging of the brain in infants aged 0-24 months. Firstly, this invention divides the infant period into different age groups based on the relationship between the T2 values ​​of white and gray matter in the infant brain. It focuses on changing the size of two control angles, thereby altering the entire flip angle chain's variation pattern, ultimately achieving optimized imaging of the infant brain at different age stages. This method has the advantages of being easy to implement and having a short acquisition time, making it suitable for routine clinical scanning.

[0041] Secondly, this invention uses the EPG algorithm instead of bloch simulation to calculate signal values ​​because the EPG algorithm has the advantages of being simple and computationally efficient when simulating signals with variable flip angles in 3D fast spin echo sequences.

[0042] Furthermore, this invention is based on the static pseudo-steady state (SPSS) signal theory and uses two key control angles α. min and α cent The entire flip-off chain was designed to avoid the enormous computational burden of calculating the maximum contrast by exhaustively enumerating all possible pulse flip-off chains. At the same time, by constraining these key angles, the signal evolved in a reasonable mode, maintaining a certain image signal-to-noise ratio, reducing motion sensitivity, and reducing the SAR value during scanning.

[0043] Finally, this invention uses RC as the primary evaluation criterion for image contrast, rather than AC or AC derivatives used in other methods. This is because, as can be seen from the definition, the magnitude of AC depends on the signal strength of the image itself, while RC more accurately reflects the image's contrast. Attached Figure Description

[0044] Figure 1 It shows quantitative imaging of T2 in the brain of infants and young children at different ages and linear changes in T2 in the gray and white matter of the brain with age.

[0045] Figure 2 This is a flowchart of the T2w magnetic resonance imaging optimization method.

[0046] Figure 3 The EPG algorithm was used to calculate the WM / GM contrast and SAR value of the brains of infants in the 3-month-old group.

[0047] Figure 4 This is the optimized result of 3D T2w imaging of the brain from 0 to 6 months and the result of automatic gray and white matter segmentation.

[0048] Figure 5 This is an optimized result of 3D T2w brain imaging at 12-24 months. Detailed Implementation

[0049] The following examples, based on the method proposed in this invention, demonstrate its specific technical effects so that those skilled in the art can better understand the essence of this invention.

[0050] In a preferred embodiment of the present invention, such as Figure 1 and Figure 2 As shown, the steps for optimizing T2-weighted magnetic resonance imaging of the infant brain are as follows:

[0051] S1: For infants aged 0-24 months, T1, T2, and PD quantitative magnetic resonance imaging (MRI) data of the brains of multiple infants were collected using a 3T MRI scanner. These samples excluded subjects with any known alterations to T2w contrast or abnormalities found on MRI images. The samples should be distributed as evenly as possible across the different age groups from 0-24 months to minimize error. Then, the mean T1, mean T2, and mean PD values ​​for the white matter (WM) and gray matter (GM) regions of each infant's brain were calculated. The specific calculation method is as follows:

[0052] First, regions of interest (ROIs) were delineated in the gray matter and subcortical white matter of the sample images. Then, for each infant brain sample, the average T1 value within the subcortical white matter ROI was calculated as the average T1 value of the infant brain white matter; the average T2 value within the subcortical white matter ROI was calculated as the average T2 value of the infant brain white matter; the average PD value within the subcortical white matter ROI was calculated as the average PD value of the infant brain white matter; the average T1 value within the gray matter ROI was calculated as the average T1 value of the infant brain gray matter; the average T2 value within the gray matter ROI was calculated as the average T2 value of the infant brain gray matter; and the average PD value within the gray matter ROI was calculated as the average PD value of the infant brain gray matter.

[0053] S2: Based on the dynamic change curve of T2 values ​​of white and gray matter in the infant's brain with brain development in each sample, the infants are divided into different age groups. Rapid brain development within the first two years after birth leads to rapid changes in image contrast. As the infant's brain continues to develop, the relationship between T2 values ​​of white and gray matter in the brain of infants of different ages will develop different characteristics. These different relationships of white and gray matter T2 values ​​will affect the final imaging effect, therefore, they need to be differentiated. In this invention, infants can be divided into three age groups based on different relationship characteristics, with the following relationship characteristics for the three groups:

[0054] In the first group, the T2 value of white matter in the brain of infants of this age group was significantly higher than the T2 value of gray matter in the brain of infants.

[0055] In the second group, the T2 value of the white matter in the brain of infants of this age group was close to the T2 value of the gray matter in the brain of infants.

[0056] In the third group, the T2 value of the white matter in the brain of infants of this age group was significantly lower than that of the gray matter in the brain.

[0057] According to subsequent embodiments, a preferred method for dividing the three-month-old group in this invention is as follows:

[0058] Infants aged 0-180 days after birth are divided into the first group, namely 0-6 months.

[0059] Infants aged 181-360 days after birth were divided into the second group, namely 6-12 months old;

[0060] Infants aged 361-720 days after birth were divided into the third group, namely 12-24 months.

[0061] Since the brains of infants in the above three-month age groups have different characteristics, it is necessary to optimize the optimal flipping angle chain for each three-month age group to significantly improve the T2-weighted imaging contrast of the infant brain in each age group.

[0062] After dividing the samples into age groups, the samples collected in S1 need to be re-divided according to these age groups. Based on all samples within each age group, the arithmetic mean of the average T1, average T2, and average PD values ​​for the white and gray matter regions of the brain is calculated and used as the average T1, T2, and PD values ​​for the white and gray matter of the infant's brain in that age group. The specific procedure for any given age group is as follows:

[0063] The average T1 value of the white matter in the brains of infants in this age group is the arithmetic mean of the average T1 value of the white matter in the brains of all samples in this age group; the average T2 value of the white matter in the brains of infants in this age group is the arithmetic mean of the average T2 value of the white matter in the brains of all samples in this age group; the average PD value of the white matter in the brains of infants in this age group is the arithmetic mean of the average PD value of the white matter in the brains of all samples in this age group; the average T1 value of the gray matter in the brains of infants in this age group is the arithmetic mean of the average T1 value of the gray matter in the brains of all samples in this age group; the average T2 value of the gray matter in the brains of infants in this age group is the arithmetic mean of the average T2 value of the gray matter in the brains of all samples in this age group; the average PD value of the gray matter in the brains of infants in this age group is the arithmetic mean of the average PD value of the gray matter in the brains of all samples in this age group.

[0064] S3: Based on the average T1, average T2, and average PD values ​​of the white and gray matter of the infant brain in each age group, the signal intensity of the white and gray matter regions of the infant brain generated by the 3DT2-weighted fast spin echo sequence under each optional flip-angle chain is calculated using the Extended Phase Map (EPG) algorithm.

[0065] The flip-chain in this invention requires designing a static pseudo-steady-state signal curve first, ignoring the longitudinal recovery and lateral attenuation processes of the magnetization vector (i.e., assuming T1 = 0, T2 = ∞), and then calculating the flip-chain based on the designed static pseudo-steady-state signal curve using the inverse-EPG algorithm. To construct different selectable flip-chains, the four corners α at fixed positions on the flip-chain can be changed. first α min α cent α max To design different static pseudo-steady-state signal curves. Wherein, α first α is the first angle on the entire flipped angle chain. min It is the fifth angle on the entire flipped angle chain, and also the smallest angle on the flipped angle chain; α cent The flip angle corresponding to the echo signal at the center of K-space at that moment; α max This is the last corner of the flipped corner chain.

[0066] The following describes the optional flip-chain and the specific method for determining signal strength:

[0067] S301, For cases containing four key angles α first α min α cent α max The flipped angle chain, fixed α max Angle value (generally α)max The angle value is fixed between 100 and 180 degrees, preferably 120 degrees, and at α min and α cent Sampling is performed within their respective angular ranges to construct a series of optional angle combinations, each of which corresponds to α. min α cent and α max A set of fixed values, α min It must be less than α cent ;

[0068] S302: For each possible angle combination, determine α... min α cent and α max Using the flip angle α as the flip angle in a fast spin echo sequence with a constant flip angle, calculate the theoretically achievable static pseudo-steady-state signal value S. SPSS The calculation formula is:

[0069]

[0070] Where P(·) is the Legendre polynomial, P -1 / The expression for (x) is:

[0071]

[0072] Then take α in Formula 1 respectively min α cent α max The static pseudo-steady-state signal value S obtained at that time SPSS These are the echo signal values ​​S corresponding to the three angles on the static pseudo-steady-state signal curve, respectively. min S cent S max ; and based on formulas 3 and 4, S min Calculate α corresponding to the current available angle combination first The calculation formula is:

[0073]

[0074]

[0075] Then, S is calculated using progressive interpolation. first With S min The static pseudo-steady-state signal between them is used to calculate S by asymptotic interpolation. min With S cent The static pseudo-steady-state signal values ​​between the two are calculated by linear interpolation. cent With S maxThe static pseudo-steady-state signal values ​​between these values ​​are used to obtain the static pseudo-steady-state echo signal chain corresponding to the currently selectable angle combination;

[0076] The progressive interpolation in this invention is a non-linear interpolation method. In the current implementation, S is calculated using progressive interpolation. first With S min Between, S min With S cent The specific interpolation formulas for the static pseudo-steady-state signal values ​​between them are as follows:

[0077] 1)S first With S min The interpolation formula between the signals is:

[0078] S(n)=0.5[S(n-1)+S min ] [Formula 5]

[0079] In the formula, n is the ordinal number of the currently calculated echo in the current signal chain, n = 2, 3, ..., K-1, and K is the current calculated signal chain (i.e., from S). first To S min The total number of echoes in this signal chain segment; where S1 is taken as S first ;

[0080] 2)S min With S cent The formula for the progressive interpolation signal between them is:

[0081]

[0082] In the formula: Δ S The difference between the signal values ​​of the two interpolated signal points is n, where n is the current calculated signal point (i.e., the echo) in the current calculated signal chain (i.e., from S). min To S cent The ordinal numbers in this signal chain are n = 2, 3, ..., N, where N = K-1;

[0083] S303. For each static pseudo-steady-state echo signal chain corresponding to each optional angle combination, ignoring the longitudinal recovery and lateral attenuation process of the magnetization vector, T1 = 0 and T2 = ∞, the required flip angle chain for the static pseudo-steady-state echo signal chain is calculated using the inverse-EPG algorithm of the extended phase diagram; the flip angle chains calculated for all optional angle combinations are all optional flip angle chains for each age group.

[0084] S304: For each age group, based on the preset echo time (TE), flip-angle chain length (ETL), and echo interval (ESP) in the fast spin echo sequence, and using the average T1, average T2, and average PD values ​​of the white matter in the brain of infants in that age group, the Extended Phase Map (EPG) algorithm is used to calculate the average signal intensity S of white matter voxels at the moment when the 3D T2-weighted fast spin echo sequence fills the center point of K-space. WM Simultaneously, based on the average T1, average T2, and average PD values ​​of the gray matter in the brains of infants in this age group, the average signal intensity S of gray matter voxels at the moment when the 3D T2-weighted fast spin echo sequence fills the center point of K-space was calculated using the extended phase map (EPG) algorithm. GM .

[0085] S4: The signal intensity of the white and gray matter of the infant brain in each age group obtained in S3 under each optional flipped corner chain is converted into the contrast of white and gray matter. According to the principle of maximizing contrast, the best flipped corner chain for each age group is selected from all optional flipped corner chains for T2-weighted magnetic resonance imaging of the infant brain.

[0086] In this invention, the optimal flipping corner chain optimization method for each age group is as follows:

[0087] S401: For each age group specified in S2, calculate the image contrast under each flip angle chain. Image contrast is divided into absolute contrast and relative contrast. Wherein:

[0088] Absolute contrast (AC) = |S WM |-|S GM |

[0089] Relative contraction (RC) = (|S WM |-|S GM |) / (|S WM |+|S GM |)

[0090] S402: For each age group, with improving relative contrast (RC) as the primary optimization objective and improving absolute contrast (AC) as the secondary optimization objective, and with the specific absorption rate (SAR) value meeting the specified range as the constraint, the optimal flip-angle chain is selected from all the corresponding optional flip-angle chains, and is used as the flip-angle chain selected for T2-weighted magnetic resonance imaging of the brain of infants in that age group.

[0091] It is important to note that the determined α min It must be less than α cent ;α firstCalculated from Formula 4; the actual α used max It can be fixed at 120°. Since RC is less affected by the signal strength of the image itself compared to AC, this invention uses RC as the primary evaluation criterion. On the other hand, since AC is related to the signal-to-noise ratio, this invention uses AC as an auxiliary evaluation criterion. Simultaneously, this invention uses SAR value as a constraint condition, the magnitude of which is specifically reflected by the sum of the squares of the flip angles. In this invention, for each age group, different α values ​​are compared... min and α cent The image contrast was optimized primarily by improving relative contrast, with improving absolute contrast as a secondary objective. The SAR value range was used as a constraint to determine the corresponding α for each age group. min and α cent In the actual optimization process, the aforementioned primary and secondary optimization objectives can be understood as maximizing the primary optimization objective while ensuring that the secondary optimization objective meets the basic conditions. Therefore, when selecting the optimal flip-corner chain from all available flip-corner chains for each age group, we can first eliminate available flip-corner chains whose specific absorption rate (SAR) value does not meet the first limiting range or whose absolute contrast ratio (AC) does not meet the second limiting range (if either SAR or AC does not meet the limiting range requirements, it needs to be eliminated). Then, from the remaining available flip-corner chains, we select the available flip-corner chain with the highest relative contrast ratio (RC) as the optimal flip-corner chain for that age group.

[0092] According to subsequent embodiments, a preferred embodiment of the optimal flipping corner chain optimization scheme finally determined for the three-month-old group in this invention is as follows:

[0093] For the three-month-old group, some 3D T2-weighted magnetic resonance imaging parameters were set to be the same, namely: α max =120°, TE=370ms, ETL=180, ESP=3.7ms; while the angle parameters of the other flipping corner chains need to be differentiated according to the age of the infant:

[0094] The infants aged 0-6 months (i.e., 0-180 days after birth) were divided into the first group, and α was used during 3D T2-weighted magnetic resonance imaging. min and α cent Set them to 80° and 90° respectively, and set TR to 2000ms;

[0095] The infants aged 6-12 months (i.e., 181-360 days after birth) were divided into the second group, and α was used during 3D T2-weighted magnetic resonance imaging. min and α cent Set to 50° and 110° respectively, and set TR to 2300ms;

[0096] The infants aged 12-24 months (i.e., 361-720 days after birth) were divided into the third group, and α was used during 3D T2-weighted magnetic resonance imaging. min and α cent Set the angles to 50° and 110° respectively, and set the TR to 2300ms.

[0097] Once the above parameters are determined, the optimal flipping angle chain corresponding to the target infant's current age group can be selected for 3D T2-weighted magnetic resonance imaging.

[0098] The technical effects of the above method will be demonstrated below with reference to embodiments, so that those skilled in the art can better understand the essence of the present invention.

[0099] Example

[0100] The optimized method for T2-weighted magnetic resonance imaging (MRI) of infant brains was tested. First, a "MIX" sequence of brain images was acquired from 142 normally developing infants using a Philips 3T MRI scanner (Achieva; Philips Healthcare, Best, The Netherlands). The spin-echo (SE) and inversion recovery (IR) signal equations were solved using ratios and the least squares method to obtain T1, T2, and PD quantitative MRI data, respectively. The brain PD values ​​were then normalized using the lateral ventricle PD value as the standard.

[0101] Regions of interest (ROIs) including cortical gray matter (GM) and subcortical white matter (WM) were manually delineated on T2 quantitative images. For each infant's brain, the mean T1 value of the subcortical white matter was calculated as the mean T1 value of the infant's brain white matter; the mean T2 value of the subcortical white matter was calculated as the mean T2 value of the infant's brain white matter; the mean PD value of the subcortical white matter was calculated as the mean PD value of the infant's brain white matter; the mean T1 value of the cortical gray matter was calculated as the mean T1 value of the infant's brain gray matter; the mean T2 value of the cortical gray matter was calculated as the mean T2 value of the infant's brain gray matter; and the mean PD value of the cortical gray matter was calculated as the mean PD value of the infant's brain gray matter.

[0102] T2 measurement results ( Figure 1B) The results show that 6 months prior, the T2 value of subcortical white matter (WM) was higher than that of cortical general matter (GM); from 6 to 12 months, the T2 values ​​of WM and GM were close; after 12 months, the T2 value of WM was lower than that of GM. Based on this pattern, infants can be divided into three groups: 0-6 months (0-180 days after birth), 6-12 months (181-360 days after birth), and 12-24 months (361-720 days after birth). The arithmetic mean of the average T1, T2, and PD values ​​of the white and gray matter regions of the brain in each age group was calculated. The signal intensity of WM and GM in the brain of each age group under a specific flipped corner chain was then calculated using the EPG algorithm. The results are as follows:

[0103] 1) For the brains of infants aged 0-6 months, in α min <α cent Within the range, AC for α min Insensitive ( Figure 3 B), while RC follows α min and α cent Increases with the increase ( Figure 3 A) SAR value varies with α min and α cent Increases with the increase ( Figure 3 C), therefore, within the allowable range of SAR values, α should be taken. min For 80°, α cent It is 90°.

[0104] 2) Because the T2 relaxation times of the white matter (WM) and gross matter (GM) in infants aged 6-12 months are highly similar (109±9ms and 107±9ms respectively), for this stage, only the contrast enhancement of certain brain regions is pursued. Therefore, the actual T1 and T2 values ​​of gray and white matter used for EPG signal simulation at this stage are the T1 and T2 values ​​of gray and white matter in the brain 9-12 months prior. In α... min <α cent Within the range, AC varies with α min Increase and decrease ( Figure 3 E), while RC follows α min and α cent Increases with the increase ( Figure 3 Therefore, within the allowable range of SAR values, α should be taken as D). min The angle is 50°, and to ensure a high RC, α is taken at this point. cent It is 110°.

[0105] 3) For the brains of infants aged 12-24 months, in α min <α cent Within the range, AC and RC change with α min and αcent The trend of change is the same as that of the 6-12 month age group. Figure 3 G, Figure 3 H), therefore the angle selected is similar to that of the 6-12 month age group.

[0106] Based on the α values ​​determined for different age groups mentioned above min and α cent The Inverse-EPG algorithm is used to calculate the corresponding change pattern of the flipped corner chain.

[0107] In addition, a set of 3D T2w fast spin echo sequence images of the brains of infants aged 0-24 months were acquired. The field of view was 180mm x 180mm x 175mm, sagittal scan, matrix 180x 512x 512, TR / TE = 2000 / 370ms (TR = 2300ms for 6-12 months and 12-24 months), ESP = 3.7ms, ETL = 180, α max =120°, 2x SENSE (acceleration and phase encoding direction are consistent), scan time is 2.3 minutes. Based on EPG calculation results ( Figure 3 The following tests were conducted: 1) Setting α min =80°, α cent =90° (hereinafter referred to as the optimized sequence) and the flip angle is always equal to 35° (hereinafter referred to as the default sequence) to scan the brains of 7 infants aged 0-6 months; 2) Set α min =50°, α cent =110° (hereinafter referred to as the optimized sequence) and the flip angle is always equal to 35° (hereinafter referred to as the default sequence) to scan the brains of three infants aged 6-12 months; 3) Set α min =50°, α cent The brains of four infants aged 12-24 months were scanned using a flip angle of 110° (hereinafter referred to as the optimized sequence) and a flip angle of 35° (hereinafter referred to as the default sequence).

[0108] Figure 4 The results show that, for the brains of infants aged 0-6 months, image segmentation based on two sequences was performed on the images. Visually, it is evident that the optimized sequence has higher segmentation accuracy than the default sequence, especially in the segmentation between the subcortical WM and cortical GM. Figure 4 C Figure 4 (Arrows and boxes in D). Based on the segmentation results of GM and WM after later manual correction, the gray-white matter contrast of images obtained from both the default and optimized sequences decreased with age. The contrast of images obtained from the optimized sequence was consistently higher than that of the default sequence, approximately twice that of the default sequence. Figure 4E). Image segmentation based on multiple atlases was performed on the images obtained from the two scan sequences. Based on the brain region segmentation results of the optimized sequence images, pair-wise t-tests confirmed that the optimized sequence had higher RC values ​​than the default sequence images for five major brain regions (p < 0.001, n = 7). Figure 4 F).

[0109] For infants aged 12-24 months, the contrast of T2w images is close to that of adults, but weaker than that of brain images from infants aged 0-6 months. This group tested both optimized and default sequences. Similarly, it was visually apparent that the contrast of images obtained from both the default and optimized sequences increased with age, with the optimized sequence consistently showing higher contrast than the default sequence. Figure 5 ).

[0110] In summary, based on the results of this embodiment, a method for optimizing T2-weighted magnetic resonance imaging of the infant brain can be provided, the method of which is as follows:

[0111] First, based on the infant's current age, select the optimal flip-over corner chain optimization scheme:

[0112] For the three-month-old group, the standard parameters for 3D T2-weighted magnetic resonance imaging were all set as follows: α max =120°, TE=370ms, ETL=180, ESP=3.7ms;

[0113] The remaining parameters for the flipped corner chain need to be selected based on the baby's age, namely:

[0114] If the infant's age is 0-6 months (i.e., 0-180 days after birth), α should be used during 3D T2-weighted magnetic resonance imaging. min Set to 80°, α cent Set to 90°;

[0115] If the infant is 6-12 months old (i.e., 181-360 days after birth), α should be used during 3D T2-weighted magnetic resonance imaging. min Set to 50°, α cent Set to 110°;

[0116] If the infant is 12-24 months old (i.e., 361-720 days after birth), α should be used during 3D T2-weighted magnetic resonance imaging. min Set to 50°, α cent Set to 110°;

[0117] In addition, in the three-month-old group, α first All based on α min The corresponding static pseudo-steady-state signal value S SPSSFor confirmation, please refer to Formulas 3 and 4 above.

[0118] Then, based on the parameters determined above, 3D T2-weighted magnetic resonance imaging was performed on the target infant's brain to complete the magnetic resonance imaging optimization.

[0119] It should be noted that the above-described embodiments are merely preferred embodiments of the present invention and are not intended to limit the invention. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the invention. Therefore, all technical solutions obtained through equivalent substitution or transformation fall within the protection scope of the present invention.

Claims

1. An optimized method for T2-weighted magnetic resonance imaging of infant brains based on fast spin echo sequences, characterized in that, Includes the following steps: S1: Collect longitudinal relaxation time T1, transverse relaxation time T2 and proton density PD quantitative imaging magnetic resonance data of the brains of infants aged 0-24 months to obtain the average T1 value, average T2 value and average PD value of white matter and gray matter of each infant's brain. S2: Based on the relative differences between the average T2 value of white matter and the average T2 value of gray matter in the brains of infants and young children in each sample, the 0-24 month age range of infants and young children is divided into different age groups; the quantitative imaging magnetic resonance data collected in S1 is re-divided according to each age group, and then the average T1 value, average T2 value and average PD value of white matter and gray matter in the brains of infants and young children in each age group are calculated respectively. S3: Based on the average T1, average T2 and average PD values ​​of the white and gray matter of the infant brain in each age group, the signal intensity of the white and gray matter of the infant brain generated by the 3D T2-weighted fast spin echo sequence under each optional flip-angle chain is calculated by the extended phase map algorithm. S4: The signal intensity of white and gray matter in the brain of infants and young children in each age group obtained in S3 under each optional flipping angle chain is converted into the contrast of white and gray matter. According to the principle of maximizing contrast, the best flipping angle chain for each age group is selected from all optional flipping angle chains for T2-weighted magnetic resonance imaging of infants and young children. The optimal method for flipping the corner chain for each age group is as follows: S401: For each age group, calculate the image contrast under each flip angle chain, where absolute contrast = |S WM | - |S GM |, relative contrast = (|S WM | - |S GM |) / (|S WM | + |S GM |), S WM S represents the average signal intensity of white matter voxels. GM The average signal intensity of gray matter voxels; S402: For each age group, with improving relative contrast as the primary optimization objective and improving absolute contrast as the secondary optimization objective, and with the specific absorption rate value meeting the specified range as the constraint, the optimal flip-angle chain is selected from all the corresponding optional flip-angle chains, and is used as the flip-angle chain selected when performing T2-weighted magnetic resonance imaging on the brains of infants in that age group.

2. The method for optimizing T2-weighted magnetic resonance imaging of infant brains according to claim 1, characterized in that, The calculation methods for the average T1 value, average T2 value, and average PD value in step S1 are as follows: S101: Acquire quantitative T1, T2, and PD magnetic resonance imaging data of the brains of several infants aged 0-24 months; S102: Based on the quantitative imaging magnetic resonance data of each infant's brain, delineate the regions of interest in the gray matter of the cerebral cortex and the white matter of the subcortical cerebral cortex; S103: Based on the regions of interest delineated in the quantitative imaging magnetic resonance data of each infant's brain, the average T1 value within the subcortical white matter regions of interest is calculated as the average T1 value of the infant's brain white matter; the average T2 value within the subcortical white matter regions of interest is calculated as the average T2 value of the infant's brain white matter; and the average PD value within the subcortical white matter regions of interest is calculated as the average PD value of the infant's brain white matter. The average T1 value within the region of interest in the gray matter of the cerebral cortex was calculated as the average T1 value of the gray matter in the infant's brain; the average T2 value within the region of interest in the gray matter of the cerebral cortex was calculated as the average T2 value of the gray matter in the infant's brain. The average PD value within the region of interest in the gray matter of the cerebral cortex is calculated as the average PD value of the gray matter in the brain of infants and young children.

3. The method for optimizing T2-weighted magnetic resonance imaging of infant brains according to claim 1, characterized in that, The method for grouping infants by age in step S2 is as follows: Based on the dynamic changes in T2 values ​​of white and gray matter in the brains of infants at different ages as a function of brain development, the infants were divided into three-month age groups. The relative high and low values ​​of the three groups are as follows: In the first group, the T2 value of white matter in the brain of infants of this age group was higher than the T2 value of gray matter in the brain of infants. In the second group, the T2 value of the white matter in the brain of infants of this age group was close to the T2 value of the gray matter in the brain of infants. In the third group, the T2 value of the white matter in the brain of infants of this age group was lower than that of the gray matter in the brain.

4. The method for optimizing T2-weighted magnetic resonance imaging of infant brains according to claim 3, characterized in that, The three age groups mentioned are 0-6 months, 6-12 months, and 12-24 months.

5. The method for optimizing T2-weighted magnetic resonance imaging of infant brains according to claim 1, characterized in that, The specific implementation steps of step S3 are as follows: S301, For cases containing four key angles α first α min α cent α max The flipped angle chain, fixed α max The angle value, and in α min and α cent Sampling is performed within their respective angular ranges to construct a series of optional angle combinations, each of which corresponds to α. min α cent and α max A set of fixed values, α min It must be less than α cent ; where α first α is the first angle on the entire flipped angle chain. min It is the fifth angle on the entire flipped angle chain, and also the smallest angle on the flipped angle chain; α cent The flip angle corresponding to the echo signal at the center of K-space at that moment; α max This is the last corner of the flipped corner chain; S302: For each possible angle combination, determine α... min α cent and α max Using the flip angle α as the flip angle in a fast spin echo sequence with a constant flip angle, calculate the theoretically achievable static pseudo-steady-state signal value. The calculation formula is: Where P(·) is the Legendre polynomial; Then take α respectively min α cent α max The static pseudo-steady-state signal value obtained at that time These are the echo signal values ​​S corresponding to the three angles on the static pseudo-steady-state signal curve, respectively. min S cent S max ; and based on S min Calculate α corresponding to the current available angle combination first The calculation formula is: Then, S is calculated using progressive interpolation. first With S min The static pseudo-steady-state signal between them is used to calculate S by asymptotic interpolation. min With S cent The static pseudo-steady-state signal values ​​between the two are calculated by linear interpolation. cent With S max The static pseudo-steady-state signal values ​​between these values ​​are used to obtain the static pseudo-steady-state echo signal chain corresponding to the currently selectable angle combination; S303. For each static pseudo-steady-state echo signal chain corresponding to each optional angle combination, ignoring the longitudinal recovery and lateral attenuation process of the magnetization vector, T1=0 and T2=∞ are set. The required flip angle chain for the static pseudo-steady-state echo signal chain is calculated by the inverse algorithm of the extended phase diagram. The flip angle chains calculated for all optional angle combinations are all optional flip angle chains for each age group. S304: For each age group, based on the echo time (TE), flip-angle chain length, and echo interval in the preset fast spin echo sequence, and using the average T1, average T2, and average PD values ​​of the white matter in the brain of infants in that age group, the extended phase map algorithm is used to calculate the average signal intensity S of white matter voxels at the moment when the 3D T2-weighted fast spin echo sequence fills the center point of K-space. WM Simultaneously, based on the average T1, average T2, and average PD values ​​of the gray matter in the brains of infants in this age group, the average signal intensity S of gray matter voxels at the moment when the 3D T2-weighted fast spin echo sequence fills the center point of K-space was calculated using the extended phase map algorithm. GM .

6. The method for optimizing T2-weighted magnetic resonance imaging of infant brains according to claim 5, characterized in that, The α max The angle value is fixed between 100 and 180 degrees.

7. The method for optimizing T2-weighted magnetic resonance imaging of infant brains according to claim 5, characterized in that, The α max Fixed at 120 degrees.

8. The method for optimizing T2-weighted magnetic resonance imaging of infant brains according to claim 7, characterized in that, In step S402, when selecting the best flipped corner chain from all available flipped corner chains for each age group, firstly, selectable flipped corner chains whose specific absorption rate value does not meet the first limit range or whose absolute contrast does not meet the second limit range are eliminated, and then the selectable flipped corner chain with the highest relative contrast is selected from the remaining selectable flipped corner chains as the best flipped corner chain for that age group.

9. A method for T2-weighted magnetic resonance imaging of the infant brain based on fast spin echo sequences, characterized in that, Based on the current age of the target infant, the optimal flipped angle chain corresponding to the age group is selected for 3D T2-weighted magnetic resonance imaging (MRI). The optimal flipped angle chain for 3D T2-weighted MRI is optimized according to the method for optimizing infant brain T2-weighted MRI as described in any one of claims 1-8. If the current age is 0-6 months, the α value of the optimal flipped angle chain for 3D T2-weighted MRI is... min Set to 80°, α cent Set to 90°; for infants aged 6-12 months, the optimal flip angle α for 3DT2 weighted magnetic resonance imaging is... min Set to 50°, α cent Set to 110°; for infants aged 12-24 months, the optimal flip angle α for 3D T2-weighted magnetic resonance imaging is... min Set to 50°, α cent Set to 110°; α in the three-month-old group max All are set to 120°, α first All based on α min The corresponding static pseudo-steady-state signal value To be confirmed.

10. The method for T2-weighted magnetic resonance imaging of infant brain based on fast spin echo sequences as described in claim 9, characterized in that, In the three-month-old group, the other parameters were set the same for 3D T2-weighted magnetic resonance imaging: echo time was set to 370ms, flip angle chain length was set to 180, and echo interval was set to 3.7ms.

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