CN109920550A - A method of teenager's lafora's disease is studied based on dMRI - Google Patents
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Abstract
The present invention relates to a kind of methods based on dMRI research teenager's lafora's disease, including the following steps: building QBI model obtains the orientation distribution function ODF of description hydrone spatial diffusion direction information；NODDI model is constructed, the parameter ICVF of cerebral white matter Microstructure Information is described；Orientation distribution function ODF based on QBI model constructs the three-dimensional nerve fibre bundle of entire brain；In conjunction with constructed brain three-dimensional nerve fibre bundle, 90 brain areas divide and ICVF data, construct the brain structure network based on ICVF of JME patient and normal person；Extract the network characterization of brain ICVF structural network, Statistical Comparison JME patient and normal person's indicator difference.
Description
Technical field
The present invention relates to medical image, computer generated image and art of mathematics, by image preprocessing and model construction, and
Complex network Mathematical Method based on graph theory realizes the research to JME pathogenesis.
Background technique
JME is a kind of using generalized tonic-clonic breaking-out as the intractable epilepsy of Clinical symptoms.Patient is usually in the youth
Phase morbidity, symptom are usually expressed as random, arythmia myoclonia convulsive seizure, and often hair is often short from morning in upper limb
Breaking-out in time.It is obvious that JME patient takes Antiepileptic Drugs effect, but recurrence is easy after being discontinued, and Most patients need
Want lifelong medication.JME pathogenesis is not also completely clear, but has had a large amount of research to have shown that JME and brain structure are abnormal,
Especially frontal lobe is related with abnormal findings of white matter with the grey matter at thalamus position.
Tradition research method to teenager's lafora's disease is brain science research method, mainly by functional magnetic
Resonance image-forming (functional magnetic resonance imaging, FMRI) and electroencephalogram
(electroencephalogram, EEG) studies the exception of brain in patients function, and this method can only study brain in patients function
Energy obstacle cannot but study brain structure exception.In recent years, with the emergence and development of neuroimaging, this non-intrusion type is ground
The method for studying carefully brain structure is widely used in the research of brain structure exception of various neurological diseases.Than as usual
T1 weighted imaging or T2 weighted imaging in the magnetic resonance imaging (magnetic resonance imaging, MRI) of rule etc.,
Available relatively clear cerebral gray matter and white matter image, but this image cannot in millimeter magnitude due to its resolving power
Show the microstructure of fiber and move towards mode, thus using conventional neuroimaging inspection cannot big intracerebral find with
The change of the relevant brain micro-structure of epilepsy.Emerging imaging mode utilizes the dMRI of the water diffusion characteristic imaging in tissue
Development and based on this reconstruction brain three-dimensional white matter fiber tractography development so that we are to cerebral white matter
The detection of micro-structure is possibly realized, the Clinics and Practices of this Central nervous disease, and is had to the research of cranial nerve science
Highly important meaning.Show that cerebral white matter fiber moves towards to carry out brain three by dMRI technology-diffusion tensor imaging (DTI)
Tie up the quantitative parameter fractional anisotropy (FA) and average diffusion coefficient (MD) of white matter reconstruction and association reaction Microstructure Information
Method, be used to earliest research neurogenic disease cerebral white matter micro-structure exception.With this method, researcher proves
The asynthesis of JME patient's corpus callosum and the damage of multiple white matter of frontal lobe fibre integrities and thalamus frontal lobe.But only according to
Rely such brain image, it is big teenager's lafora's disease patient can only to be explored from part rather than from the structure change of full brain
Exception in brain structure, it is not comprehensive enough.
The cause of disease of teenager's lafora's disease is not only related with the grey matter or abnormal findings of white matter of the certain privileged sites of brain, also
The mutual synergistic effect being related between each brain area, traditional research method can not obtain in this respect well research at
Fruit.We need to study the brain of JME patient by the comprehensive method of a system, using brain network to cerebral function
Or the abnormal research of structure extensively to be sent out is applied in various neurological diseases in recent years, brain network variation
The effect played in epilepsy occurrence and development is also paid more and more attention.Cerebral nerve network is that one kind being capable of high efficiency extraction and integration
It is insane to be used to research teenager's myoclonic to the analysis of complex network based on Graph-theoretical Approach for the complex network of various effective informations
Epilepsy, the index of multiple network topological property provided by it, including global network feature and local network characteristics, can help me
Meticulously study comprehensively brain in patients network topology it is abnormal, and then it is abnormal to study the connection between each brain area.There is research
Person goes the cerebral white matter exception for studying some neurogenic diseases such as alzheimer's disease with this method and achieves very well
Result.Also researcher demonstrates JME patient's network topology attribute abnormal using DTI and graph-theory techniques building brain network.
However, when carrying out full brain fiber reconstruction using DTI, since the limitation of its imaging characteristics is only able to display a fiber orientation
It is as a result inaccurate without can solve the problem of big intracerebral fibre bundle intersects.
Summary of the invention
The main object of the present invention be by based on QBI full brain fiber reconstruction technology and brain network analysis method apply
To in the research of teenager's lafora's disease brain in patients white matter micro-structure exception.Technical solution is as follows:
A method of teenager's lafora's disease is studied based on dMRI, including the following steps:
It a) is 2000s/mm by b value2DWI data construct QBI model, obtain description hydrone spatial diffusion direction letter
The orientation distribution function ODF of breath；
It b) is 0,1000 and 2000s/mm by b value2DWI data construct NODDI model, describe the micro- knot of cerebral white matter
The parameter ICVF of structure information；
C) the orientation distribution function ODF based on QBI model constructs the three-dimensional nerve fibre bundle of entire brain；
D) constructed brain three-dimensional nerve fibre bundle is combined, 90 brain areas divide and ICVF data, and building JME suffers from
The brain structure network based on ICVF of person and normal person；
E) network characterization of brain ICVF structural network, including three kinds of global network features are extracted: characterizing path length,
Global efficiency and transitivity and three kinds of local network characteristics: degree, component efficiency and cluster coefficients, Statistical Comparison JME patient and
Normal person's indicator difference.
The present invention shows that nerve fibre moves towards building cerebral white matter fiber, solution using the QBI for being different from tradition DTI method
DTI method of having determined cannot show the limitation of complicated intersection nerve fibre.The present invention uses the ICVF from NODDI model
Data, this data represent the density value of cerebral white matter neural process, and traditional parameter from DTI, with nerve density, fiber
Orientation dispersion, axon diameter compare with myelinization degree many factors correlation FA value, more specifically more can show that trouble
Person's cerebral white matter textural anomaly.
Detailed description of the invention
Fig. 1 holistic approach flow chart
Fig. 2 orientation distribution function schematic diagram
Fig. 3 brain DWI data and ICVF Parameter Map
Fig. 4 brain structure network struction schematic diagram
Fig. 5 global network characteristic statistics result
Fig. 6 local feature degree exception brain area
Fig. 7 local feature cluster coefficients exception brain area
Fig. 8 local feature component efficiency exception brain area
Specific embodiment
The present invention uses two kinds of dMRI technologies: QBI and NODDI.Orientation distribution function (orientation is rebuild using QBI
Distribution function, ODF) display nerve fibre trend, obtain the three-dimensional nerve fibre bundle of full brain.Use description
The quantitative parameter of brain tissue microstructure information: the parameters cell inner body fraction (intracellular from NODDI
volume fraction,ICVF).It, will be based on unified brain point later in conjunction with the Complex Networks Analysis method based on graph-theory techniques
90 brain areas of area's template connect the fibre bundle weighting ICVF value of brain area as network edge, construct 33 as network node
The brain structure network of JME patient and 10 normal persons of gender and age-matched: ICVF weighted network.To two groups of crowds'
Brain structure network characterization, including three kinds of global network features: path length, global efficiency, transitivity, three kinds of parts are characterized
Network characterization: degree, component efficiency, cluster coefficients are for statistical analysis, obtain the network characterization difference of two groups of crowds, and then study
The brain structure network topology exception and cerebral white matter micro-structure of JME patient is abnormal, and the illness machine of JME patient is studied with this
System.
The invention will be further described with example with reference to the accompanying drawing:
1, research object
Research object is from 33 JME patients' of epileptics therapeutic community, ancient Chinese name for Venus memorial hospital, Taoyuan City, Taiwan, China Linkou County
Sample (male/female: 16/17, average age: 27.7 ± 10.3 years old), 10 normal person's samples (male/female: 5/5, average age:
28.0 ± 2.8 years old).Each subject meets the standard of being included in without any exclusion criteria, and 33 JME patients' is included in mark
Standard includes: the common recognition [8] of (A) according to domestic anti-epileptic alliance to the classification diagnosis [7] and international expert of JME about JME:
(1) clinical symptoms: bilateral myoclonic breaking-out when awakening is taken place mostly in；(2) electroencephalogram: normal background and at least once
Broad sense peak value or multi-peak Interictal electroencephalogram more than or equal to 3Hz；(3) brain magnetic resonance imaging image (MRI)/brain CT: anencephaly
Tumor and other cerebral injuries.(B) neurological examination is normal.Exclusion criteria include: (A) have serious brain traumatism in addition to JME or
The patient of epilepsy syndromes medical history, such as progressive lafora's disease (PME).(B) meet the exclusion criteria for MRI scan,
There is metallic foreign body such as claustrophobia disease or in vivo.
2, data acquire
The data that the present invention studies are obtained by the 3.0T magnetic resonance scanner of ancient Chinese name for Venus memorial hospital, TaiWan, China peach garden Linkou County
?.Diffusion-Weighted MR Imaging (DWI) data add double spin echoes to obtain by using single Echo-plane imaging (EPI) sequence, adopt
Two kinds of diffusion-sensitive parameter b value (1000s/mm are collected2And 2000s/mm2) with respectively apply 64 different gradient directions image
Data, acquisition parameter are as follows: number of sections 55,220 × 220mm of slice thickness 2.3mm, FOV2, matrix size 96 × 96, body
The size of element is isotropism 2.3mm, repetition time (TR) 8300ms, echo time 100ms, sweep time 17min51s.
In addition to this, also acquire two kinds of phase-encoding directions without diffusion weighted images (b=0s/mm2), number (NEX) 10 is excited,
Sweep time is 1min23s, remaining parameter is same as described above.No diffusion weighted images are the structure of the NODDI data of high s/n ratio
Build and prepare, also for further for correct because sensitivity induction distortion provide non homogen field estimation.
3, data prediction
For the accuracy for improving image, some pretreatments are carried out to initial data first and carry out exclusive PCR factor.All originals
The image data of beginning DICOM format is converted to NIfTI format using MRIcro software.Using MRtrix3 to two kinds of b values
It DWI data and is pre-processed without diffusion weighted data, including vortex induction distortion correction, motion correction and sensitive induction distortion
Correction.Finally, constructing diffusion model QBI and NODDI using the data after correction.
4, model construction
This research uses DSI-studio software, and the DWI data of b=2000 are carried out with the QBI changed based on spherical harmonics
Reconstruct obtains the Orientation Distribution Function (ODF) of water diffusion.ODF is used for full brain three-dimensional white matter fiber weight in next research
The problem of building, can solve fiber crossovers.
The present invention selects the AMICO-NODDI-Toolbox of MATLAB software to utilize b=0, b=1000, b=2000's
DWI data carry out the building of NODDI data.The DWI data building of the different b values of NODDI Model Fusion can distinguish it is different every
Between: freely isotropic Gaussian, extracellular anisotropic Gaussian limit anisotropy with intracellular to cerebrospinal fluid
Non-gaussian diffusion, therefore three kinds of parameters: ICVF can be obtained, isotropism volume fraction (ISO) orients diffusion index
(ODI).Wherein ICVF has been applied in the research to epilepsy because describing the density of nerve fibre.Present invention selection
ICVF is for constructing brain structure network
5, brain structure network struction
It is fine that the certainty fibre bundle tracing algorithm of research and utilization DSI-studio software of the present invention carries out brain three-dimensional white matter
Reconstruction process is tieed up, the ODF comprising water dispersal direction is used for determining fibre bundle traveling.Design parameter setting is as follows: fibre bundle number
Amount is 100000, and QA threshold value 0.4 is 60 ° as the condition for stopping fibre bundle tracking, the threshold value of fibre bundle turning angle, step
A length of 1mm, smoothness 0.5mm.Minimum length is 20mm, maximum length 450mm.Existing research is proved using QA as fibre
More accurate fiber traveling can be obtained than FA by tieing up termination condition.
By the coincidence corresponding with full brain ICVF value of obtained full brain white matter integrity in DSI-Studio, it is based on brain region
90 brain areas of AAL template are as node, and the average ICVF value of fibre bundle is as network edge weight between every two brain area
Matrix element obtains two kinds of 90*90 connection matrix as brain structure network.In order to reduce the influence of pseudo- connection, building is fine
Dimension mesh matrix, it is 1 that ribbon number, which is greater than 3 elements, is 0 less than 3.ICVF matrix is corrected by this matrix.
6, networking character value calculates
Some researches show that the structure and function network of brain all has the feature of complex network, is based on graph-theory techniques research
Brain network becomes a kind of new method.Network performance feature includes global network feature and local network characteristics.The present invention point
Not Yan Jiu brain structure network three kinds of global characteristics and three kinds of local features, it is all to be defined as follows:
(1) global network feature: global network feature describes the global feature of a network.
Characterize path length (characteristic path length, CPL): path length be from a node to
The minimum amount of edge that another node must traverse, CPL calculate the average path length of all possible node pair in network,
That is a node is transmitted to the amount of edge between another node, indicates the ability of overall network information integration.
Global efficiency (global efficiency, GE): global efficiency is the measurement standard of a Network integration ability,
It is the inverse of CPL, represents the efficiency degree for transmitting information in a network.
Transitivity (transitivity, T): transitivity is cluster coefficients (clustering coefficient, CC)
One global expression, indicates the gathereding degree of a network entirety.
(2) local network characteristics: local network characteristics are the performance indicators for measuring each node in a network, often
One node has a kind of local network characteristics value.
Spend (degree, D): node degree is that most basic and most important index, each node degree refer in local network characteristics
The number of edges for being attached to the node.
Component efficiency (local efficiency, LE): component efficiency, that is, individual node neighborhood global efficiency, with network
The cluster coefficients of local feature have certain correlation, represent the ability of individual node information transmitting.
Cluster coefficients (CC): the adjacent node of cluster coefficients measuring node trend interconnected.The cluster of single node
Coefficient is defined as between the neighbours of node existing connection quantity divided by its all possible connection.
The all-network feature that the present invention studies passes through the Brain Connectivity Toolbox (BCT) of MATLAB
(https: //sites.google.com/site/bctnet/) is calculated.It is as a result soft with DSI-Studio to ensure accuracy
Part calculated result is compared, and the two is consistent.
7, it statisticallys analyze
Through the above steps the present invention obtain 33 JME patients and 10 normal persons 3 global network features and
3 local network characteristics of 90 brain areas, the present invention are calculated by MATLAB software, examine (two- using double sample T
Sample test) it is next for statistical analysis using JME patient's network characterization corresponding with normal person as two samples, compare
Network characterization difference between JME patient and normal person.As a result statistically significant using p < 0.05 as standard determination as difference.
The full brain fiber reconstruction technology based on QBI that the present invention uses solves traditional based on diffusion tensor imaging
(DTI) the problem of brain intersects nerve fibre can not be shown in full brain Fiber tractography.Using brain network analysis method
The limitation that can only be studied for the exception of the cerebral white matter of certain concrete positions in traditional method is overcome, is realized complete
The abnormal findings of white matter of surface analysis teenager's lafora's disease brain in patients all sites.
Claims (1)
1. a kind of method based on dMRI research teenager's lafora's disease, including the following steps:
It a) is 2000s/mm by b value2DWI data construct QBI model, obtain description hydrone spatial diffusion direction information
Orientation distribution function ODF；
It b) is 0,1000 and 2000s/mm by b value2DWI data construct NODDI model, describe cerebral white matter Microstructure Information
Parameter ICVF；
C) the orientation distribution function ODF based on QBI model constructs the three-dimensional nerve fibre bundle of entire brain；
D) combine constructed brain three-dimensional nerve fibre bundle, 90 brain areas divide and ICVF data, building JME patient and
The brain structure network based on ICVF of normal person；
E) network characterization of brain ICVF structural network, including three kinds of global network features are extracted: characterizing path length, it is global
Efficiency and transitivity and three kinds of local network characteristics: degree, component efficiency and cluster coefficients, Statistical Comparison JME patient and normal
People's indicator difference.
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Cited By (7)
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| CN111402198A (en) * | 2020-02-11 | 2020-07-10 | 山东师范大学 | Alzheimer disease classification method and system based on anatomical landmarks and residual error network |
| CN111523617A (en) * | 2020-06-09 | 2020-08-11 | 天津大学 | Epilepsy detection system based on white matter fusion characteristic diagram and residual error attention network |
| CN113057620A (en) * | 2021-03-05 | 2021-07-02 | 兰州理工大学 | Effective connection method for coupling relations of different brain areas of juvenile myoclonus epileptic patient |
| CN114376522A (en) * | 2021-12-29 | 2022-04-22 | 四川大学华西医院 | Method for constructing computer recognition model for recognizing juvenile myoclonus epilepsy |
| CN114983389A (en) * | 2022-06-15 | 2022-09-02 | 浙江大学 | Quantitative evaluation method for human brain axon density based on magnetic resonance diffusion tensor imaging |
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