CN114403812A - Auxiliary analysis method, device and system for brain injury condition and storage medium - Google Patents
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Abstract
The invention relates to a method, a device and a system for auxiliary analysis of brain injury conditions and a storage medium. The auxiliary analysis method is used for carrying out auxiliary analysis on the neonatal brain injury condition and comprises the steps of obtaining near infrared data of a target area of a neonatal examinee in a resting state brain; and displaying a central node map of a tiling mode in a first region of a display interface based on the acquired near-infrared data, wherein the central node map comprises a first brain image and a mark of a central node, and at least part of the central node can be tiled in a background region outside a brain edge in the first brain image, so that each central node on the first brain image is not shielded. The invention displays the center node, the regional connection, the functional connection, the characteristic indexes related to the brain injury condition and the like on the interface in a form of image-text combination, so that a doctor can improve the accuracy, the reliability and the clinical diagnosis efficiency of analysis of the brain injury condition of the newborn through multi-angle viewing, multi-map comparison and multi-index reading.
Description
Technical Field
The invention relates to the technical field of medical diagnosis, in particular to a brain injury condition auxiliary analysis method, device, system and storage medium, which are used for carrying out auxiliary analysis on the brain injury condition of a newborn.
Background
Neonatal Hypoxic-Ischemic Brain injury (HIBD) is generally caused by perinatal asphyxia, which is the main cause of infant nerve disability, and survivors may have neurological sequelae such as mental retardation, cerebral palsy, convulsion, cognitive dysfunction and the like. Therefore, early diagnosis and intervention of hypoxic-ischemic brain injury of the newborn are very important for improving the neural development prognosis of the newborn with brain injury.
The current diagnosis of the hypoxic ischemic brain injury of the newborn mainly depends on the clinical manifestation of the sick children and the detection of the structural injury of the brain by medical imaging technologies such as functional magnetic resonance, CT and the like. However, in actual clinical work, on one hand, the early clinical manifestations of the brain injury of the newborn are atypical, and it is difficult to judge whether the newborn has the brain injury and the brain injury degree in the first time only by the bedside observation of the clinician, and it is easy to miss an important treatment time window, and the existing medical imaging technology also has the disadvantages of difficult bedside real-time monitoring, radiation, need of tranquilizer, etc., so that it is difficult to obtain the brain injury data, and the newborn is injured; on the other hand, in the prior art, no device capable of assisting a doctor in performing auxiliary analysis on the hypoxic-ischemic brain injury condition of the newborn exists, and no specific detection index capable of assisting the doctor in rapidly and accurately analyzing and judging the hypoxic-ischemic brain injury condition of the newborn exists, so that the timely discovery and intervention of the brain injury of the newborn are limited. Therefore, how to provide a means for assisting in analyzing the hypoxic-ischemic brain injury condition of a newborn for a doctor is a problem which needs to be solved urgently in clinic at present.
Disclosure of Invention
The present invention is provided to solve the above-mentioned drawbacks in the prior art. There is a need for an auxiliary analysis method, apparatus, system and storage medium for brain injury status of a newborn, which is used for performing auxiliary analysis on the brain injury status of the newborn, and which acquires near-infrared data of a target region of a brain of a newborn subject in a resting state by using a near-infrared spectral brain function imaging technology, calculates and processes the acquired near-infrared data, and displays a center node map generated after processing on a display interface, so that a user can check information such as the position of each center node as clearly as possible, and perform auxiliary analysis on the brain injury status of the newborn on the basis, thereby improving accuracy and reliability of diagnosis and efficiency of clinical diagnosis.
The first aspect of the invention provides an auxiliary analysis method for brain injury conditions, which is used for carrying out auxiliary analysis on brain injury conditions of a newborn, the auxiliary analysis method comprises the steps of acquiring near infrared data of a target area of a brain of a newborn examinee in a resting state, and displaying a central node map in a first area of a display interface based on the acquired near infrared data; the central node map of the tiled mode comprises a first brain image and an identification of a central node; wherein at least some of the hub nodes are tileable into a background region outside of a brain edge in the first brain image such that individual hub nodes on the first brain image are unobstructed.
A second aspect of the present invention provides an auxiliary analysis apparatus for brain injury condition of a newborn, which is used for auxiliary analysis of brain injury condition of the newborn, and the auxiliary analysis apparatus at least includes a processor and a memory, the memory stores computer executable instructions, and the processor executes the auxiliary analysis method for brain injury condition according to various embodiments of the present invention when executing the computer executable instructions.
A third aspect of the present invention provides an auxiliary analysis system for brain injury conditions, which is used for performing auxiliary analysis on brain injury conditions of newborns, and comprises a near infrared spectrum detection device and an auxiliary analysis device for brain injury conditions as described above.
A fourth aspect of the present invention provides a non-transitory computer-readable storage medium storing a program for causing a processor to perform various operations of a method for assisting in the analysis of a brain injury condition according to various embodiments of the present invention.
The method, the device, the system and the storage medium for auxiliary analysis of brain injury conditions provided by the embodiments of the invention are used for auxiliary analysis of neonatal brain injury conditions, the near infrared spectrum brain function imaging technology is adopted to acquire near infrared data of a target region of a neonatal examinee in a resting state brain, the acquired near infrared data is calculated and processed, a central node map associated with the brain injury conditions is displayed in a display interface based on the calculation and processing results, and in the central node map of a tiled mode, the identification of each central node is tiled and displayed in a first brain image, so that the central nodes are not mutually shielded or covered, and are not shielded by the first brain image, thereby being beneficial for a user to clearly and quickly and accurately acquire central node information, and the auxiliary analysis of the neonatal brain injury conditions on the basis has higher accuracy and reliability, so that the efficiency of clinical diagnosis of doctors can be further improved.
Drawings
In the drawings, which are not necessarily drawn to scale, like reference numerals may describe similar components in different views. Like reference numerals having letter suffixes or different letter suffixes may represent different instances of similar components. The drawings illustrate various embodiments generally by way of example and not by way of limitation, and together with the description and claims serve to explain the disclosed embodiments. Such embodiments are illustrative, and are not intended to be exhaustive or exclusive embodiments of the present apparatus or method.
Fig. 1 shows a flow chart of a method for assisted analysis of brain injury status according to an embodiment of the invention.
FIG. 2 shows a schematic diagram of a hub node graph of a tiling pattern according to an embodiment of the present invention.
FIG. 3 shows a schematic diagram of a hub node map of adsorption patterns according to an embodiment of the invention.
Fig. 4 shows a schematic diagram of a region join map according to an embodiment of the invention.
Fig. 5 shows a schematic diagram of a functional connectivity graph according to an embodiment of the invention.
Fig. 6 shows a schematic diagram of a feature index table associated with a brain injury condition according to an embodiment of the invention.
Fig. 7 is a partial schematic structural diagram of an auxiliary analysis device for brain injury conditions according to an embodiment of the present invention.
Fig. 8 is a partial schematic component diagram of an auxiliary analysis system for brain injury status according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings of the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the invention without any inventive step, are within the scope of protection of the invention.
Unless defined otherwise, technical or scientific terms used herein shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs. The word "comprising" or "comprises", and the like, means that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items.
To maintain the following description of the embodiments of the present invention clear and concise, a detailed description of known functions and known components of the invention have been omitted.
The method for auxiliary analysis of brain injury according to the embodiment of the present invention requires acquiring near-infrared data of a target region of a brain of a newborn subject in a resting state by using a near-infrared spectrum detection device or the like, and therefore, a typical process of measurement and data acquisition by the near-infrared spectrum detection device will be briefly described next.
In general, a near infrared spectrum detection apparatus includes a head cap, wherein the head cap may have a plurality of probes for transmitting and/or receiving near infrared signals, or mounting positions capable of being fitted with the respective probes, each of the plurality of probes is specifically configured as a transmitting probe (S) or a receiving probe (D), wherein each pair of probes arranged in pairs forms a channel, one transmitting probe may correspond to the plurality of receiving probes, or vice versa, and one receiving probe corresponds to the plurality of transmitting probes, and the pair relationship thereof may be specifically set in the SD arrangement according to a brain functional region to be detected, or the like. The SD layout is a preset relationship layout of the transmitting probe (S) and the receiving probe (D), and the user can see the preset relationship, layout position, etc. between the respective probes from the SD layout, for example, the transmitting probe S12 can form a channel 1 with the receiving probe D8, the transmitting probe S6 can form a channel 2 with the receiving probe D8, and all of the transmitting probe S12, the transmitting probe S6 and the receiving probe D8 are disposed in the left temporal lobe region of the subject. When the near infrared spectrum detection device is used, after the user assembles each probe on the near infrared spectrum detection device head cap according to the SD layout, the near infrared data of each region of the brain of the detected person can be measured and collected. In addition, before measurement, specific positions of the transmitting probes and/or the receiving probes on the head cap, which are mapped on the three-dimensional brain image, can be obtained by using positioning equipment, so that positioning information of channels formed by the probes arranged in pairs can be obtained, and the positioning information can comprise positioning data, brain area information corresponding to the channels and the like.
Fig. 1 shows a flow chart of a method for assisted analysis of brain injury status according to an embodiment of the invention.
First, in operation S101, near infrared data of a target region of a brain of a neonatal subject in a resting state may be acquired by, for example, a near infrared spectrum detection apparatus.
By way of example only, the target region of the brain may include processed brain regions that are related to some higher cognitive functions, such as six brain regions of the parietal lobe, temporal lobe, and prefrontal lobe of the left and right sides of the cerebral cortex, specifically including the right parietal lobe, left parietal lobe, right temporal lobe, left temporal lobe, right forehead, left forehead, and the like, and the associative cooperation capability between these brain regions may reflect, to some extent, the brain development of the neonate. The method for acquiring the near-infrared data of the target area of the brain of the newborn subject by using the near-infrared spectrum detection equipment only needs to detect the newborn in a resting state in a short time, does not harm the newborn, is simple to operate, and has strong anti-motion and anti-electromagnetic interference capabilities due to the near-infrared spectrum detection equipment, so that the method is less limited by the environment, can realize real-time continuous observation at the bedside, and can be well suitable for a newborn group.
In operation S102, a hub node map may be generated by processing the near-infrared data acquired in operation S101, and the hub node map may be displayed in the first region of the display interface.
In some embodiments, the hub node map within the first region may comprise a hub node map of a tiled pattern, which may comprise, for example, a first brain image and an identification of hub nodes, at least some of which may be tiled into a background region outside of a brain edge in the first brain image such that hub nodes on the first brain image are not occluded, including no mutual occlusion or coverage between hub nodes, and hub nodes are also not occluded by the first brain image. More specifically, the node types in the hub node map include common nodes and hub nodes, in the hub node map in the tiling mode, at least the identifiers of the hub nodes are displayed at corresponding positions on the first brain image, in general, the common nodes and the hub nodes may be displayed together on the first brain image, and when some of the hub node corresponding positions fall into a background region outside the brain edge in the first brain image, in order to enable a user to clearly see each hub node, the hub nodes may be arranged in the background region outside the brain edge, for example, in a tiling non-overlapping mode according to a relative positional relationship therebetween.
It is to be understood that the first brain image may be a two-dimensional brain image or a three-dimensional brain image, and the present invention is not limited thereto. It should be understood that, the hub node maps of the tiled mode in the embodiments of the present invention do not limit the mode in which each node in the hub node map is tiled as a whole and does not overlap, and may also be set such that only the hub node that is occluded by the first brain image or other nodes can be displayed in the tiled mode, as long as it is ensured that each hub node is not occluded, which is not specifically limited by the present invention.
In one embodiment, the first brain image is a two-dimensional brain image, and the positions of the nodes in the central node map may be determined by registering the positions of the channels formed on the SD layout with the two-dimensional brain image, in which case the nodes in the central node map are displayed on the two-dimensional brain image in a tiled-as-a-whole and non-overlapping mode, as shown in fig. 2.
In another embodiment, the first brain image is a three-dimensional brain image, and as shown in fig. 3, the positions of the nodes in the central node map may be determined and displayed based on the positioning data of the channels obtained in the positioning process. Specifically, the hub node that can be seen clearly within the visual angle range of the user can be directly displayed on the three-dimensional brain image according to the positioning data thereof, and the shielded hub node can be displayed in a tiled manner in the background area outside the brain edge in the three-dimensional brain image, so that the user can see the hub node clearly.
The central node map presented in operation S102 may effectively reflect the central node development retardation of the infant patient due to hypoxia/ischemia during the development process. Specifically, the central nodes are considered to play a central role in the functional integrity of the whole brain network, and the number of the central nodes can effectively reflect the development condition of important functional positions of the neonate, so that the central nodes are used as auxiliary analysis indexes to ensure the effectiveness and accuracy of an analysis result, and for a sick child, the number of the central nodes is less than that of a healthy neonate. Therefore, according to the central node map of the tiled mode in the embodiment of the present invention, the user can clearly obtain the number and distribution of the central nodes, so as to determine whether the neonate has brain damage or potential brain damage, or analyze the degree of the brain damage.
FIG. 2 shows a schematic diagram of a hub node graph of a tiling pattern according to an embodiment of the present invention. As shown in fig. 2, a center node map M1-1 of the tiled mode is displayed in the first area a1 of the display interface a0, and the center node map of the tiled mode may include the first brain image BI1 and the identification of the center node, for example, according to the illustration, the center node CN1, the center node CN2, the center node CN3, and the like in the figure may be distinguished and identified with different colors (or shades of colors, and the like) from the normal node NN1, and the like, and in other embodiments, the outline of the center node identification may be thickened to highlight. In addition, any other suitable form may be adopted, and the present invention is not particularly limited. In other embodiments, the labels of the nodes may be identified on the hub node map, so that the user can obtain the positioning information corresponding to the node according to the labels of the nodes.
In some embodiments, the current SD layout is displayed within the second region of the display interface with the identification of at least one of the hub nodes tiled in the first brain image in a background region outside the brain edges. In the central node map M1-1 in the tiling mode shown in fig. 2, there may be one or more central nodes located outside the range that can be displayed in the first brain image, such as the central node CN2 and the central node CN3, and the identification of these central nodes will be tiled in the background region outside the brain edge in the first brain image BI1, such as the central node CN2 and the central node CN3, according to the relative positional relationship between the nodes on the SD layout, in this case, in order to more accurately know the positional information of these central nodes located outside the brain edge, the SD layout L1 used when obtaining the current near-infrared data may be displayed in the second region a2 of the display interface a 0.
In the SD layout L1, the transmitting probe is designated by the letter S and the receiving probe is designated by the letter D, according to the illustration. The transmitting probe and the receiving probe at the corresponding positions form a channel, for example, the transmitting probe S12 and the receiving probe D8 form a channel 1, the transmitting probe S6 and the receiving probe D8 form a channel 2, and so on, which are not listed. In some embodiments, the near infrared data corresponding to each channel may be collected using the transmitting and receiving probes on the head cap of the near infrared spectrum detection apparatus according to the SD layout L1, and the central node map M1-1 may be generated based on the collected near infrared data, with a specific algorithm as follows.
First, a brain function network is constructed, a channel formed between each pair of the transmitting probe and the receiving probe in the SD arrangement diagram L1 is regarded as a node in the brain function network, and as can be seen from the SD arrangement diagram L1, 53 channels are shared in common from channel 1 to channel 53, and therefore, the brain function network includes 53 nodes in total from node 1 to node 53, and therefore, 53 nodes also exist in the central node map M1-1 corresponding to the brain function network. As described above, the node types in the hub node map M1-1 include the common nodes and the hub nodes, wherein the determination method of the hub nodes is as follows:
first, the length of the time series of the near-infrared data of each node is equal, and an arbitrary node pair (node) can be calculated by the following formula (1)iAnd nodej) Of the time series of Pearson correlation coefficientsr ij And will ber ij As nodesiAnd nodejThe connection strength between:
Wherein the content of the first and second substances,nwhich indicates the length of the time series,krepresenting the first on a time serieskThe point of the light beam is the point,X i (k)andX j (k) Respectively representing nodesiTime series ofX i And nodejTime series ofX j In the first placekThe value of the samples at a point is,
and
respectively representX i AndX j mean over the entire time series.
Assume co-inclusion in brain function networkmA node obtained by the formula (1)
The strength of the connection between pairs of individual nodes. The connection strength between the node pairs can then be binarized based on a preset threshold value, so as to construct and form a brain function network, for example, the connection strength can be measured atr ij When the node is greater than or equal to a preset threshold value, the node is connectediAnd nodejThe strength of the connection between is set to 1r ij When the node is smaller than the preset threshold value, the node is connectediAnd nodejThe strength of the connection therebetween is set to 0.
There are various ways to select the preset threshold, for example, a sparsity threshold may be used, and other threshold ways such as a similarity threshold may also be used. Taking the sparsity threshold as an example only, assuming the sparsity threshold P =0.3, then it means that all node pairs are (a) ((b)), (c) ((c))i，j) Middle joint strengthr ij The connection strength accounting for the first 30% is set as 1, and the rest is set as 0, so that the brain function network with the sparsity threshold value P of 0.3 is obtained. For the selection of the sparsity threshold, for example, a brain function network can be constructed based on a sparsity threshold P in a range of 0.3 to 0.34, the sparsity threshold in the range conforms to the sparsity of the brain function network of the newborn, and various detection indexes of the brain function network constructed in the threshold range can present obvious differences between the hypoxic and ischemic brain injury infant and the healthy newborn, so that the accuracy and the effectiveness of an analysis result can be improved.
Next, the hub nodes may be obtained by a node degree method. Specifically, an average value and a standard deviation of node values between all node pairs in the brain function network may be calculated, where a node value is the number of connecting edges of one node, and a node whose node value is higher than the average value plus the standard deviation is further set as a central node, and other nodes are common nodes. In addition, the pivot node may be determined by other methods, such as an betweenness centrality method. The betweenness centrality method sets a node with betweenness centrality value higher than the average value plus the standard deviation as a central node, wherein the betweenness centrality of a certain node refers to the proportion occupied by a path passing through the node in the shortest path between any node pair in the brain function network. For the above method, reference may be made to the related descriptions in the prior art, and the details are not repeated here.
In some embodiments, upon identifying a hub node from all nodes, the corresponding data may be stored in memory for later recall in computing processing or display, and the hub node identified in hub node map M1-1 to generate final hub node map M1-1.
In some embodiments, when the display interface a0 is initially presented to the user, in order for the physician user to grasp the overall situation of the hub node map, the hub node map may be presented first in a tiled mode as shown in fig. 2, in which the number and general distribution of hub nodes can be viewed very intuitively, and particularly through a comparison with the SD layout, the brain region location information and channel information corresponding to hub nodes located in background regions other than the brain edge can also be accurately known.
In some embodiments, in addition to displaying the hub node map in a tiled mode, a hub node map of a sorption mode may be displayed within the first region of the display interface. FIG. 3 shows a schematic diagram of a hub node map of adsorption patterns according to an embodiment of the invention. As shown in fig. 3, the center node map M1-2 of the adsorption pattern within the first region a1 may include, for example, a second brain image BI2 and identifications of respective center nodes such as a center node CN4, a center node CN5, a center node CN6, wherein the second brain image BI2 is a three-dimensional brain image, and such that the identifications of the respective center nodes remain closely attached to the corresponding center nodes in the three-dimensional brain image in a case where the displayed three-dimensional brain image changes position and/or angle. In connection with fig. 3, the second brain image BI2 is a three-dimensional brain image rotated to a side view angle, where the central node CN6 is located at the brain edge of the three-dimensional brain image at the angle, but the identification of the central node CN6 remains tightly attached to the three-dimensional brain image, and is not tiled into a background region outside the brain edge of the three-dimensional brain image like the partial central nodes in the central node map of the tiled mode in fig. 2. By way of example only, an option or button for hub node graph display mode switching is provided, for example, in a menu bar of the display interface, in a right-hand menu, and/or separately, so that the user can conveniently perform mode switching.
In some embodiments, the hub node map displaying the adsorption mode may also be switched within the first region in response to a first interaction of the user with the hub node map of the tiling mode. In some embodiments, the user may perform a first interaction, such as a mouse click, a double click, a menu bar, or a right-click menu option, on the hub node and/or the first brain image, and/or switch and display the hub node graph of the tiled pattern as the hub node graph of the absorption mode in the first area based on the first interaction applied by the user to the hub node in the background area in the hub node graph of the tiled pattern, and highlight the hub node applied by the user with the first interaction. By way of example only, since the second brain image is a three-dimensional brain image, the second brain image in the center node map of the adsorption mode may be turned to a direction in which the center node where the user applies the first interaction faces the user, so that the user can more clearly see the position of the center node on the brain area, and/or the center node where the user applies the first interaction is labeled in a color different from other center nodes, and the center node where the user applies the first interaction may also be caused to flash, and the like, and various highlighting manners may be used alone or in combination, which is not limited to the present invention. By the method, after the mode is switched to the central node map of the adsorption mode, the central node concerned by the user can still keep focused presentation, and the efficiency of obtaining the central node information by the user is improved.
In further embodiments, independently or additionally, the map of hub nodes displaying the adsorption mode may also be switched within the first region in the event that a tiling status of the identification of hub nodes in the background region of the first brain image satisfies a predetermined condition. For example only, when the number of the hub nodes tiled in the background area exceeds a certain proportion of the total number of the hub nodes, the display mode of the hub node map may be automatically or manually switched to the adsorption mode, so as to facilitate the user to view the information of each hub node. In another embodiment, the predetermined condition may be that the number of hub nodes in the background area is greater than 0, at which time the hub node map may be automatically displayed in a adsorption mode. In another embodiment, other display mode switching conditions may be set, and the present invention is not limited in particular.
In some embodiments, the user may further perform a second interaction operation, such as mouse dragging, clicking, labeling, information viewing, information remarking, on the hub node in the hub node map of the adsorption mode, and in response to the second interaction of the user on the hub node in the hub node map of the adsorption mode, the hub node to which the user applies the second interaction may be correspondingly highlighted, for example, the three-dimensional brain image may be turned to a direction in which the hub node to which the user applies the second interaction faces the user, so as to observe the brain region position information and the like in detail where the hub node is located. In other embodiments, hub nodes that the user has applied the second interaction may also be labeled in a different color than other hub nodes. In some embodiments, highlighting the hub node to which the user applied the second interaction may further include, for example, displaying brain region information corresponding to the hub node to which the user applied the second interaction, and/or the like.
The above responses to the second interaction may be used alone or in combination, and the specific response mode may be determined according to the indication of the actual second interaction operation of the user.
In some other embodiments, especially in the case that the hub nodes are dense, if the brain area information of each hub node is displayed in the hub node map in the tile mode, information blocking and overlapping may be caused, which may affect the user to obtain useful information, so for example, the user may not display the brain area information of the hub node by default, and may also perform a third interaction, such as a mouse click, a double click, a menu bar or a right-click menu option, directly on the hub node in the hub node map in the tile mode without switching to the display interface of the hub node map in the adsorption mode, and in response to the third interaction of the user on the hub node map in the tile mode, display the brain area information corresponding to the hub node to which the third interaction is applied by the user.
According to the method and the device, the central node map is displayed in the first area of the display interface, the switching between the tiling mode and the adsorption mode can be performed according to the selection of a user or under the condition that a preset condition is met, so that the user can master the number and the overall distribution of the central nodes through the central node map of the tiling mode, the central node map is switched to the adsorption mode to perform detailed checking on the exact position, specific information and the like of the concerned central node when necessary, the maps of different modes are not displayed simultaneously, but are presented to the user in the same area in a switching mode, information redundancy and interface confusion can be effectively avoided, and the user can conveniently acquire the concerned information.
In some embodiments, in addition to the characteristics of the number and distribution of the central nodes, the connection strength between different brain regions can also reflect the communication capacity between the brain regions, and can be directly or indirectly used for measuring the coordination capacity, information transmission and integration efficiency, and the like between the brain regions. Thus, in addition to the hub node map, based on the acquired near-infrared data, an area connection map may be displayed in a third area of the display interface, for example. Fig. 4 shows a schematic diagram of a region join map according to an embodiment of the invention. In fig. 4, the map of area junction M2 is shown in the third area A3 of the display interface a0, wherein the map of area junction M2 may include six brain areas of the left and right bilateral cerebral cortex, namely, the prefrontal, temporal and parietal lobes, which are involved in the processing of some higher cognitive functions, and whether their associative cooperation reflects the brain development level of the newborn. As shown in fig. 4, each region of the right parietal lobe, the left parietal lobe, the right temporal lobe, the left temporal lobe, the right forehead and the left forehead has a node marking the region, each node is connected with each other by line segments, the connecting line segments are used for identifying the connection relationship between the regions and the connection strength between the regions, and the strength can represent the cooperative ability between brain regions. The diagram on the right side of fig. 4 shows a specific way of identifying the inter-region connection relationship (including the strength of the connection) by line segments, i.e., different colors may be used to represent specific numerical values of different connection strengths, or fractions after normalization (i.e., fractions between [0, 1 ]) representing the connection strengths. The intensity is not limited to be represented by color, and in other embodiments, the connection intensity may be differentiated in various manners such as gray scale, line type, marked line segment, and the like, and the invention is not particularly limited.
The region connection map M2 and the calculation method of the connection strength of the line segments between the brain regions in the map are specifically as follows.
First, as previously described, each node pair can be calculated based on equation (1) ((i，j) Of the time series of Pearson correlation coefficientsr ij Then for every two region pairs (e.g., region r)1And region r2) From all node pairs (i，j) Select out nodeiAnd nodejRespectively belong to the region r1And region r2And on the basis of the Pearson correlation coefficients of the time series of all node pairs satisfying the above conditionr ij The connection strength between the two regions is determined. Specific algorithms include, but are not limited to, all node pairs or representative node pairs that will satisfy the above conditions according to equation (2) ((2))i，j) Of the time series of Pearson correlation coefficientsr ij As the region r1And region r2Strength of connection between
：
Wherein the content of the first and second substances,nto satisfy
Node pair of (a)i，j) The number of the cells.
With the left temporal lobe (r)1) And the left forehead (r)2) The connection strength of the region connecting line segment LK1 between isFor example, all the genes belonging to the left temporal lobe (r) can be treated1) Node (a) ofiAnd belongs to the left forehead (r)2) Node (a) ofj(ii) ai，j) Pearson correlation coefficient of time series of node pairsr ij Taking the arithmetic mean value, and taking the arithmetic mean value
As the connection strength of the area connection line segment LK1, the color (or gradation) of the area connection line segment LK1 is identified based on the correspondence between the corresponding strength value and the color (or gradation) defined in the color (or gradation) bar shown in the right side diagram of fig. 4, for example, by the predetermined definition of the connection strength value.
In other embodiments, other algorithms than arithmetic averaging may be used, such as one of geometric mean, squared mean (root mean square mean), harmonic mean, weighted mean, etc., to find all satisfied nodesiAnd nodejNode pairs respectively belonging to two different areas: (i，j) Pearson correlation coefficient of (1)r ij On the basis of the above-mentioned two regions to obtain the connection strength between the above-mentioned two regions
The present invention is not limited in this regard.
It will be appreciated that the values of the connection strengths between the respective regions need not be absolute values, but may be normalized values, in which case the connection strengths between all the regions may be first calculated, and the connection strengths between each pair of regions may be normalized with respect to the maximum value thereof, and then identified in the region connection map M2.
The embodiment of the invention provides favorable support for the auxiliary analysis and accurate diagnosis of the characteristics of the brain injury condition associated with the strength of functional connection of the cross-brain region by presenting the regional connection map, and the user can analyze and judge the phenomena of central node development delay, low coordination capability among brain regions, low information transmission and integration efficiency and the like of a newborn possibly caused by hypoxia and ischemia in the development process by visually checking the functional connection relationship and the specific connection strength among different brain regions of the newborn.
Besides displaying the center node map and the area connection map in the display interface, the function connection map can be displayed in a fourth area of the display interface based on the acquired near infrared data. Fig. 5 shows a schematic diagram of a functional connectivity graph according to an embodiment of the invention. In fig. 5, in a fourth area a4 of the display interface a0, a functional connection map M3 is displayed, and in M3, connection relationships between channels are displayed, and connection strengths between channels are indicated by image blocks of different colors. As described above, according to the SD layout, channels can be formed between the transmitting probes and the receiving probes at corresponding positions, and assuming that the number of the channels is N, the functional connection map M3 is an N × N matrix, where each element in the matrix is an image block with a color, and different colors represent connection strengths between the channels. The color (or grayscale) bar graph in FIG. 5 is similar to the graph in FIG. 4, showing the specific numerical values of the different joint strengths represented by the different colors (or grays), or the scores representing the joint strengths after normalization (i.e., [0, 1]]The decimal between). Specifically, the connection strength of each element in the functional connection map M3 corresponds to the connection strength between a pair of channels (a pair of nodes), and the specific value may be the node pair: (i，j) Of the time series of Pearson correlation coefficientsr ij The detailed calculation method can refer to the algorithm in the formula (1) in fig. 2, which is not described herein again.
In addition, for the convenience of viewing by the user, when channels are arranged, the channels may be arranged in groups according to the brain regions to which the channels belong, so that in the function connection map M3 matrix, the user can grasp the connection strength between a certain channel and other channels by observing the color tone of a certain row (or a certain column) in the function connection map M3. In this way, through the function connection map, particularly after the channels are orderly arranged, the user can more conveniently grasp the connection strength between the concerned specific channels, between the specific channels and each brain region and between different brain regions, and make more accurate analysis and diagnosis on the basis.
In some embodiments, in addition to presenting the acquired near infrared data in the form of a visualized atlas, a feature index associated with a brain injury condition may be displayed within a fifth region of the display interface based on the acquired near infrared data, wherein the feature index may include, but is not limited to, at least one of an average functional connection strength of a whole brain region, an average functional connection strength across a hemisphere, and an average functional connection strength associated with a parietal lobe.
Fig. 6 shows a schematic diagram of a feature index table associated with a brain injury condition according to an embodiment of the invention. For example, the average functional connection strength of the whole brain region, the average functional connection strength across hemispheres and the average functional connection strength related to the parietal lobe can be displayed in the fifth region a5 of the display interface a0 in the form of a characteristic index table T1, and the inventor has found through a large number of experiments that the numerical ranges of the three indexes have a great significance for the doctor user to judge the brain injury condition, are also indexes that are easy to understand and use by the doctor, and can provide the doctor with a more intuitive and easy-to-understand basis for auxiliary analysis and diagnosis.
By way of example only, specific calculation methods for the average functional connectivity strength of the whole brain region, the average functional connectivity strength across the hemisphere, and the average functional connectivity strength associated with the parietal lobe will be given below.
It can be understood that the connection strength between the nodes in the target brain region obtained based on the formula (1) can be obtainedr ij Calculating the average value, and taking the average value as the average functional connection strength of the whole brain region
. The average may be an arithmetic average, may be weighted and averaged according to the importance degree, attention degree, and the like of the node, and may be one of other geometric average, square average (root mean square average), harmonic average, and the like, for example, and the present invention is not limited in particular.
Similarly, the cerebral cortex may be divided into a left hemisphere and a right hemisphere, and the connection strength between two brain regions respectively located in the two hemispheres is taken as a trans-hemispheric functional connection strength, which can be obtained by averaging all the obtained trans-hemispheric functional connection strengths. Similarly, the average value may be an arithmetic average value, or may be an algorithm other than the arithmetic average value, such as one of a geometric average value, a square average value (root mean square average value), a harmonic average value, a weighted average value, and the like, and the present invention is not particularly limited.
It will be appreciated that in calculating the average functional connection strength associated with the apical lobe, it may be that all
And (3) selecting a subset of node pairs related to the left top leaf or the right top leaf from each node pair, calculating the connection strength between the node pairs by using a formula (1) aiming at each node pair or representative node pair in the subset, and averaging the connection strengths between all the node pairs in the subset to obtain the average functional connection strength related to the top leaf. Similarly, the average value may be an arithmetic average value, or may be an algorithm other than the arithmetic average value, such as one of a geometric average value, a square average value (root mean square average value), a harmonic average value, a weighted average value, and the like, and the present invention is not particularly limited. In other embodiments, when the average functional connection strength associated with the left top leaf or the right top leaf needs to be known separately, the connection strength of each node pair in the subset may be determined only for the subset of node pairs related to one of the left top leaf or the right top leaf, and the average of the connection strengths may be used as the average functional connection strength associated with one of the left top leaf and the right top leaf.
In other embodiments, not limited to the three characteristic indexes, other indexes beneficial to auxiliary analysis of the brain injury condition may also be provided for the user, which are not specifically listed.
The embodiment of the invention also provides an auxiliary analysis device for the brain injury condition. Fig. 7 is a partial schematic structural diagram of an auxiliary analysis device for brain injury conditions according to an embodiment of the present invention. The apparatus 700 for assisting in analyzing a brain injury condition shown in fig. 7 may include at least a processor 701 and a memory 702, the memory 702 having stored thereon computer-executable instructions, and may further store near-infrared data of a target region of a brain of a newborn subject in a resting state acquired via a near-infrared spectrum detection device or the like for generating a central node map, a region connection map, a function connection map, a feature index associated with the brain injury condition, which need to be presented on a display interface, and a user may indicate a need to record the stored data and index or the like based on various interactions.
The processor 701 shown in fig. 7, when executing the computer-executable instructions, may perform various operations of the method for assisting in analyzing a brain injury condition according to various embodiments of the present invention, for example, may perform operations including, but not limited to: acquiring near-infrared data of a target region of a brain of a neonatal subject in a resting state; displaying a central pivot node map in a first area of a display interface based on the acquired near-infrared data; the central node map of the tiled mode comprises a first brain image and identification of central nodes, so that the central nodes on the first brain image are not shielded, the central nodes are not shielded or covered with each other, and the central nodes are not shielded by the first brain image.
The processor 701 may be a processing device, such as a microprocessor, Central Processing Unit (CPU), Graphics Processing Unit (GPU), etc., including one or more general-purpose processing devices. More specifically, the processor 701 may be a Complex Instruction Set Computing (CISC) microprocessor, Reduced Instruction Set Computing (RISC) microprocessor, Very Long Instruction Word (VLIW) microprocessor, processor running other instruction sets, or processors running a combination of instruction sets. The processor 701 may also be one or more special-purpose processing devices such as an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), a system on a chip (SoC), or the like. The processor 701 may be communicatively coupled to the memory 702 and configured to execute computer-executable instructions stored thereon to perform the method of assisted analysis of brain injury conditions of the various embodiments described above.
The memory 702 may be a non-transitory computer-readable medium, such as Read Only Memory (ROM), Random Access Memory (RAM), phase change random access memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Electrically Erasable Programmable Read Only Memory (EEPROM), other types of Random Access Memory (RAM), flash disk or other forms of flash memory, cache, registers, static memory, compact disk read only memory (CD-ROM), Digital Versatile Disks (DVD) or other optical storage, magnetic cassettes or other magnetic storage devices, or any other possible non-transitory medium that can be used to store information or instructions that can be accessed by a computer device, and so forth.
The embodiment of the invention also provides an auxiliary analysis system for the brain injury condition. Fig. 8 is a partial schematic component diagram of an auxiliary analysis system for brain injury status according to an embodiment of the present invention. The system 800 for assisting analysis of brain injury condition shown in fig. 8 may include, for example, a near infrared spectrum detection device 801 and an auxiliary analysis apparatus 802 for brain injury condition according to various embodiments of the present invention, wherein the auxiliary analysis apparatus 802 for brain injury condition implements various operations of the method for assisting analysis of brain injury condition.
Embodiments of the present invention also provide a non-transitory computer-readable storage medium storing a program that causes a processor to perform various operations of the method for assisting in the analysis of a brain injury condition according to various embodiments of the present invention.
The method, the device and the system for auxiliary analysis of brain injury conditions provided by the embodiment of the invention can utilize near infrared spectrum detection equipment and the like to obtain near infrared data of a target area of a brain of a newborn examinee in a resting state, have no harm to the newborn, are simple to operate, can realize real-time continuous observation at bedside, generate data and images such as a central node map, an area connection map, a function connection map and characteristic indexes related to the brain injury conditions, which can effectively reflect the difference between a child with brain injury and a healthy newborn through calculation and processing of the detection data, and present the data and the images in a form of image-text combination and flexible switching on a display interface, and provide various interaction modes for a user, so that the user can perform multi-angle viewing, multi-map comparison and multi-index reading on concerned contents, and accordingly auxiliary analysis and cooperative judgment of the newborn brain injury conditions by referring to the maps, the indexes and the like The method has higher accuracy and reliability, and the efficiency of clinical diagnosis can be further improved.
Moreover, although exemplary embodiments have been described herein, the scope thereof includes any and all embodiments based on the present invention with equivalent elements, modifications, omissions, combinations (e.g., of various embodiments across), adaptations or alterations. The elements of the claims are to be interpreted broadly based on the language employed in the claims and not limited to examples described in the present specification or during the practice of the invention, which examples are to be construed as non-exclusive. It is intended, therefore, that the specification and examples be considered as exemplary only, with a true scope and spirit being indicated by the following claims and their full scope of equivalents.
The above description is intended to be illustrative and not restrictive. For example, the above-described examples (or one or more versions thereof) may be used in combination with each other. For example, other embodiments may be used by those of ordinary skill in the art upon reading the above description. In addition, in the above-described embodiments, various features may be grouped together to streamline the disclosure. This should not be interpreted as an intention that a disclosed feature not claimed is essential to any claim. Rather, inventive subject matter may lie in less than all features of a particular disclosed embodiment. Thus, the following claims are hereby incorporated into the detailed description as examples or embodiments, with each claim standing on its own as a separate embodiment, and it is contemplated that these embodiments may be combined with each other in various combinations or permutations. The scope of the invention should be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.
The above embodiments are only exemplary embodiments of the present invention, and are not intended to limit the present invention, and the scope of the present invention is defined by the claims. Various modifications and equivalents may be made by those skilled in the art within the spirit and scope of the present invention, and such modifications and equivalents should also be considered as falling within the scope of the present invention.
Claims (14)
1. An auxiliary analysis method for brain injury conditions, which is used for auxiliary analysis of brain injury conditions of newborns, and is characterized in that the auxiliary analysis method comprises the following steps:
acquiring near-infrared data of a target region of a brain of a neonatal subject in a resting state;
displaying a central pivot node map in a first area of a display interface based on the acquired near-infrared data; wherein the content of the first and second substances,
the central node map of the tiled mode comprises a first brain image and an identification of a central node; wherein the content of the first and second substances,
at least some of the hub nodes can be tiled into a background region in the first brain image outside of the brain edge such that individual hub nodes on the first brain image are not occluded.
2. The auxiliary analysis method according to claim 1, wherein displaying the hub node graph in the first region of the display interface specifically comprises:
displaying a center node map of an adsorption mode in a first area of a display interface, wherein the center node map of the adsorption mode comprises a second brain image and an identification of a center node; wherein the content of the first and second substances,
the second brain image is a three-dimensional brain image such that the identity of each hub node remains closely attached to the corresponding hub node in the three-dimensional brain image in the event that the displayed three-dimensional brain image changes position and/or angle.
3. The aided analysis method of claim 2, further comprising:
switching to display a pivot node map of a snap-in mode within the first region in response to a user's first interaction with the pivot node map of the tile mode, and/or in the event that a tiling condition of an identification of a pivot node in a background region of the first brain image satisfies a predetermined condition.
4. The auxiliary analysis method according to claim 3, wherein switching to display the hub node map of the adsorption mode within the first region in response to a first interaction of the user with the hub node map of the tiling mode specifically comprises:
switching a display of the pivot node graph of the adsorption mode in the first region based on a first interaction applied by a user to a pivot node in a background region in the pivot node graph of the tiling mode, and highlighting the pivot node applied by the user to the first interaction.
5. The auxiliary analysis method according to claim 4, wherein highlighting the hub node to which the user applies the first interaction specifically comprises at least one of:
turning the second brain image to a direction such that a hub node at which the user applies the first interaction faces the user;
labeling the hub nodes to which the user applies the first interaction in a different color than other hub nodes;
causing a hub node to flash where the user applied the first interaction.
6. The aided analysis method of claim 3, wherein, in response to a second user interaction with a hub node in the hub node graph of the adsorption pattern, highlighting a hub node to which the second interaction is applied by the user, comprises at least one of:
turning the three-dimensional brain image to a direction such that a hub node at which the user applies the second interaction faces the user;
labeling the hub nodes to which the user applies the second interaction in a different color than other hub nodes;
and displaying the brain area information corresponding to the central node applied by the user to the second interaction.
7. The aided analysis method of claim 1, further comprising:
displaying a current SD layout within a second region of the display interface with the identification of at least one of the hub nodes tiled in a background region in the first brain image outside the brain edge.
8. The auxiliary analysis method according to claim 1, wherein in response to a third interaction of the user with the map of hub nodes of the tiled pattern, brain area information corresponding to the hub node to which the third interaction is applied by the user is displayed.
9. An auxiliary analysis method according to any one of claims 1 to 8, further comprising: displaying a region connection map in a third region of the display interface based on the acquired near-infrared data.
10. An auxiliary analysis method according to any one of claims 1 to 8, wherein the auxiliary analysis method further comprises:
displaying a function connection map in a fourth area of the display interface based on the acquired near-infrared data, displaying a function connection relation among channels of each brain region on the function connection map, and marking function connection strength among the channels by image blocks with different colors.
11. An auxiliary analysis method according to any one of claims 1 to 8, further comprising:
displaying, in a fifth region of the display interface, a characteristic indicator associated with a brain injury condition based on the acquired near-infrared data, the characteristic indicator including at least one of:
average functional connectivity strength of the whole brain region, average functional connectivity strength across the hemisphere, and average functional connectivity strength associated with the parietal lobe.
12. An auxiliary analysis device for brain injury condition of a newborn, comprising at least a processor and a memory, wherein the memory stores computer executable instructions, and the processor executes the auxiliary analysis method for brain injury condition according to any one of claims 1 to 11 when executing the computer executable instructions.
13. An auxiliary analysis system for brain injury conditions of a newborn, comprising a near infrared spectrum detection device and an auxiliary analysis apparatus for brain injury conditions of claim 12.
14. A non-transitory computer-readable storage medium storing a program that causes a processor to execute operations of the method for assisted analysis of brain injury condition of any one of claims 1-11.
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