Differences between revisions 20 and 83 (spanning 63 versions)

[TUTORIAL UNDER CONSTRUCTION: NOT READY FOR PUBLIC USE]

FEM tensors estimation with BrainSuite

Authors: Takfarinas Medani, Francois Tadel, Anand Joshi and Richard Leahy

In this tutorial, we describe the estimation of realistic conductivity tensors of living brain tissues using the BrainSuite software. These results are used in FEM forward modeling, as described in the tutorials: FEM with DUNEuro and FEM median nerve example.

The realistic tensors are estimated from the Diffusion-Weighted Images (DWI): Brainstorm calls the BrainSuite software to compute the diffusion tensors on each brain MRI voxel (DTI), then Effective Medium Approach (EMA) is applied to estimate the conductivity tensors for each element of a tetrahedral FEM mesh. This is particularly interesting for the modeling the anisotropy of the white matter.

BrainSuite is also used for other purposes in Brainstorm, particularly the T1 MRI segmentation, as documented in this tutorial: MRI segmentation: BrainSuite.

Contents

Download and installation
Import the anatomy
FEM mesh
FEM conductivity tensors
Visualization
Simulated conductivity tensor
Additional documentation

Download and installation

Requirements

You have already followed all the introduction tutorials.
You have a working copy of Brainstorm installed on your computer.
For the DWI data, only the NIfTI files (.nii) are supported.

Install Brainsuite

Download the latest version of BrainSuite from http://forums.brainsuite.org/download/.
Install it on your computer by following the instructions in BrainSuite's quick start installation guide.
You will be using BrainSuite Diffusion Pipeline (BDP), so you need to install a compatible MATLAB Runtime (2019b for BrainSuite 21a).
In Brainstorm, menu File > Edit preferences > Enter the BrainSuite installation folder:

Download the dataset

Download the files: MRI T1w and MRI DWI (from the BrainSuite diffusion tutorial).
Unzip it outside of any of the Brainstorm folders (program folder or database folder).
Start Brainstorm (Matlab scripts or stand-alone version)
Select the menu File > Create new protocol. Name it "TutorialTensors" and select:
- No, use individual anatomy
- No, use one channel file per condition

Import the anatomy

T1 MRI

Switch to the "anatomical data" view, the left button in the toolbar above the database explorer.
Right-click on the TutorialFem folder > New subject > Subject01
- Keep the default options you set for the protocol.
Right-click on the subject node > Import MRI:
- Set the file format: All MRI files (subject space)
- Select the T1 file: BrainSuiteTutorialSVReg/2523412.nii.gz
Click on the link "Click here to compute MNI normalization": option "maff8". This estimates an affine transformation to the MNI space and sets default positions for the anatomical fiducials. The NAS/LPA/RPA fiducials are needed for defining the Brainstorm subject coordinate system, in which the surfaces and FEM meshes are stored.

Diffusion imaging

This computes the This requires BrainSuite to be installed on your computer, with the bdp program available in the system path.

Right-click on Subject01 > Convert DWI to DTI
Select the DWI file: DWI/2523412.dwi.nii.gz
The associated text files *.bvec (orientation of the gradient) and *.bval (value of the gradient) must be in the same folder, with the same file name. Theses files are created from for the DWI acquisition. If you don't have them, ask the person who programmed your DWI sequence and get the files that are specific to your use case.
The process can take up to 30min. At the end, a new file DTI-EIG appears in the database (DTI=diffusion tensors images, EIG=eigenvalue). This file contains 12 volumes, ie. 12 values for each voxel. From 1 to 9: components of the three eigenvectors; from 10 to 12: the values of their norm to the eigenvalue.

FEM mesh

The FEM approach requires a segmentation of the head volume in different tissues, represented as hexahedral or tetrahedral 3D meshes. The methods available within Brainstorm are listed in the tutorial FEM mesh generation.

Here we illustrate only the use of Brain2mesh: this is not the most accurate solution for MRI segmentation but it is probably the fastest solution to obtain a tetrahedral mesh of the head with 5 tissues (gray matter, white matter, CSF, skull, skin). For more accurate results, we recommend using SimNIBS with T1+T2, as illustrated in the tutorial FEM median nerve example.

Right-click on the T1 MRI > MRI segmentation > Generate FEM mesh > Brain2mesh.
After less than 15 minutes, you will obtain a new FEM mesh in the database.

FEM conductivity tensors

Once the FEM mesh and the DTI tensors are available in the Brainstorm database, the next step is to compute the conductivity tensor for each of the FEM mesh element.

Right-click on the FEM mesh > Compute FEM tensors.
Brainstorm checks the available tissues in the FEM mesh and assigns a default isotropic conductivity value of the conductivity for each compartment. Users can change these values to their own if needed.
When selecting "Anisotropic" for a tissue, the DTI values are used to generate conductivity tensors: this is used mostly for the white matter (and in some cases for the grey matter). Note that DWI can be used only for the brain tissues and not for the outers compartments (skull and skin). The methods available are:
- EMA: Effective Medium Approach: See (Tuch 2001).
- EMA + VC: EMA with volume constraints: The final tensors are constrained to fit the volume of the equivalent isotropic tensor volume.
- Simulated: Artificial anisotropy (DTI is not required)
For this example, select: WM:Anisotropic and Isotropic for the other tissues, EMA+VA.
The FEM conductivity tensors are saved in the the FEM mesh file, in the field Tensors.

Visualization

Right-clicking on the FEM head > Display FEM tensors. The tensors can be displayed as ellipsoids or arrows (vectors in the direction of the main eigenvector) and overlaid on the MRI slices or the FEM mesh.
On the FEM mesh: left=ellipsoids, right=arrows
The orientation of the tensor is color-coded as follows:
- Red: right-left
- Green: anterior-posterior
- Blue: superior-inferior
To change the display options: Right-click on the figure > FEM tensors.
Use the keyboard shortcuts Up and Down to change the size of the graphical elements representing the tensors.
Note that the quality of the tensors depends on the DWI data and the number of acquisition direction.

Advanced

Simulated conductivity tensor

In the case where the DWI is not available, or in the case where the users desire to evaluate the effect of the conductivity change on the head model, the artificial conductivity can be used.

Users can reach this option by following this tutorial and select the third method in this panel.

Two approaches are integrated within Brainstorm. Either Wang's constraint or the volume's constraint (Wolters). The common feature between these methods is the ratio between the transversal and longitudinal conductivity ratio.

A common example is the skull anisotropy simulation, where the longitudinal conductivity can be higher than the transversal conductivity, the ratio can vary from 2 to 10 [ref]. In this tutorial, we keep all the tissue as isotropic, except the skull, we use a ratio of 0.1 and select the volume constraint. The following figures show the results of this example.

"eigenvalues parallel (longitudinal) and perpendicular (transverse) to the fiber directions" for 1:10 anisotropy (transverse:longitudinal)

Additional documentation

Articles

Medani T, Garcia-Prieto J, Tadel F, Schrader S, Joshi A, Engwer C, Wolters CH, Mosher JC, Leahy RM, Realistic head modeling of electromagnetic brain activity: An integrated Brainstorm pipeline from MRI data to the FEM solution (preprint), SPIE Medical Imaging, 2021
Tuch DS, Wedeen VJ, Dale AM, George JS, Belliveau JW, Conductivity tensor mapping of the human brain using diffusion tensor MRI, PNAS, 2001

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-## page was renamed from brainsuiteBDP
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+'''[TUTORIAL UNDER CONSTRUCTION: NOT READY FOR PUBLIC USE]'''

----
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-'''[TUTORIAL UNDER WRITING: NOT READY FOR PUBLIC USE]'''
+In this tutorial, we describe the estimation of realistic conductivity tensors of living brain tissues using the [[http://brainsuite.org/|BrainSuite software]].   These results are used in FEM forward modeling, as described in the tutorials: [[https://neuroimage.usc.edu/brainstorm/Tutorials/Duneuro#DUNEuro_options:_Advanced|FEM with DUNEuro]] and [[https://neuroimage.usc.edu/brainstorm/Tutorials/FemMedianNerve#FEM_tensors|FEM median nerve example]].
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-Describe brainsuite here : here we will describe the process of the brain tissues anisotrpy estimation and the different functions that brainstorm offers.
+The realistic tensors are estimated from the Diffusion-Weighted Images (DWI): Brainstorm calls the BrainSuite software to compute the diffusion tensors on each brain MRI voxel (DTI), then Effective Medium Approach (EMA) is applied to estimate the conductivity tensors for each element of a tetrahedral FEM mesh. This is particularly interesting for the modeling the anisotropy of the white  matter.
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-This tutorial explains how to use Brainsuite to estimate the anisotropy of the brain tissues.

refer to this page

[[https://neuroimage.usc.edu/brainstorm/Tutorials/SegBrainSuite?highlight=(Anand)|https://neuroimage.usc.edu/brainstorm/Tutorials/SegBrainSuite?highlight=%28anand%29]]

The realistic tensors are estimated from the Diffusion-Weighted Images (DWI). For this purpose, Brainstorm calls internally the BrainSuite Diffusion Pipeline to compute the diffusion tensors on each brain voxel. Afterward, the Effective Medium Approach is applied to convert the diffusion tensors to the conductivity tensors. The following section shows the users how to do it from the graphical interface.

Only the NIfTI is supported. All the diffusion data, including the DWI file and direction and the value of the gradient files, respectively the *.nii, the *.bval and the *.bvec are required. Ideally, these files should have the same name and saved in the same folder.
+BrainSuite is also used for other purposes in Brainstorm, particularly the T1 MRI segmentation, as  documented in this tutorial: [[Tutorials/SegBrainSuite|MRI segmentation: BrainSuite]].
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+Line 16:
-== Requirement ==
 * You have already followed all the introduction tutorials
 * You have a working copy of Brainstorm installed on your computer
+== Download and installation ==
==== Requirements ====
 * You have  already  followed all the  introduction tutorials.
 * You have a working copy of   Brainstorm  installed on your computer.
 * For the DWI data, only the NIfTI files (.nii) are supported.
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+Line 22:
-== Brainsuite Installation ==
 1. Download the latest version of BrainSuite from http://www.brainsuite.org/download.
+==== Install Brainsuite ====
 1. Download the latest version of BrainSuite from http://forums.brainsuite.org/download/.
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+Line 26:
-. Note that you will be using BrainSuite Diffusion Pipeline(BDP), so you need to install a compatible [[http://www.mathworks.com/products/compiler/mcr|MATLAB Compiler Runtime]](last version).
 1. Start BrainSuite to check if the installation (It's not required to open BrainSuite to run this tutorial).
 1. The BrainSuite installation folder should be informed in the Brainstorm preferences
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+Line 27:
-{{attachment:brainsuiteInstalation.JPG||height="250",width="650"}}
+. You will be using BrainSuite Diffusion Pipeline (BDP), so you need to install a compatible [[https://www.mathworks.com/products/compiler/matlab-runtime.html|MATLAB Runtime]] (2019b for BrainSuite 21a).

 1. In Brainstorm, menu File > Edit preferences > Enter the BrainSuite installation folder:<<BR>><<BR>> {{attachment:brainsuiteInstall.gif}}

==== Download the dataset ====
 * Download the files: [[http://brainsuite.org/WebTutorialData/BrainSuiteTutorialSVReg_Sept16.zip|MRI T1w]] and [[http://brainsuite.org/WebTutorialData/DWI_Feb15.zip|MRI DWI]] (from the [[http://brainsuite.org/tutorials/dtiexercise/|BrainSuite diffusion tutorial]]).

 * Unzip it outside of any of the Brainstorm folders (program   folder or database folder).
 * Start Brainstorm (Matlab scripts or stand-alone version)
 * Select the menu File > Create new protocol. Name it "'''TutorialTensors'''" and select:
  * No, use individual anatomy
  * No, use one channel file per condition

== Import the anatomy ==
=== T1 MRI ===
 * Switch to the "anatomical data" view, the left button in the toolbar above the database explorer.
 * Right-click on the TutorialFem folder > New subject > '''Subject01'''
  * Keep the default options you set for the protocol.

 * Right-click on the subject node > '''Import MRI''':
  * Set the file format: '''All MRI files (subject space)'''

  * Select the T1 file: BrainSuiteTutorialSVReg/'''2523412.nii.gz'''

 * Click on the link "'''Click here to compute MNI normalization'''": option "'''maff8'''". This estimates an affine transformation to the [[https://neuroimage.usc.edu/brainstorm/CoordinateSystems#MNI_coordinates|MNI space]] and sets default positions for the anatomical fiducials. The NAS/LPA/RPA fiducials are needed for defining the Brainstorm [[CoordinateSystems|subject coordinate system]], in which the surfaces and FEM meshes are stored. <<BR>><<BR>> {{attachment:importT1.gif}}

=== Diffusion imaging ===
This computes the  This requires BrainSuite to be installed on your computer, with the bdp program available in the system path.

 * Right-click on Subject01''' '''> '''Convert DWI to DTI'''

 * Select the DWI file: DWI/'''2523412.dwi.nii.gz'''

 * The associated text files '''*.bvec''' (orientation of the gradient) and '''*.bval''' (value of the gradient) must be in the same folder, with the same file name. Theses files are created from for the DWI acquisition. If you don't have  them, ask the person who programmed your DWI sequence and get the files  that are specific to your use case.

 * The process can take up to 30min. At the end, a new file '''DTI-EIG'''  appears in the database (DTI=diffusion tensors images, EIG=eigenvalue). This file contains 12 volumes, ie. 12 values  for each voxel. From 1 to 9: components of the three eigenvectors; from  10 to 12:  the values of their norm to the eigenvalue.  <<BR>><<BR>> {{attachment:importDTI.gif}}

== FEM mesh ==
The FEM approach requires a segmentation of the head volume in different  tissues, represented as hexahedral or tetrahedral 3D meshes. The  methods available within Brainstorm are listed in the tutorial [[https://neuroimage.usc.edu/brainstorm/Tutorials/FemMesh|FEM mesh generation]].

Here we illustrate only the use of '''Brain2mesh''': this is not the most accurate solution for MRI segmentation but it is probably the fastest solution to obtain a tetrahedral mesh of the head with 5 tissues (gray matter, white matter, CSF, skull, skin). For more accurate results, we recommend using '''SimNIBS with T1+T2''', as illustrated in the tutorial [[https://neuroimage.usc.edu/brainstorm/Tutorials/FemMedianNerve#FEM_mesh_with_SimNIBS|FEM median nerve example]].

 * Right-click on the T1 MRI > MRI segmentation > '''Generate FEM mesh''' > '''Brain2mesh'''.<<BR>><<BR>> {{attachment:femMesh1.gif}}
 * After less than 15 minutes, you will obtain a new FEM mesh in the database.<<BR>><<BR>> {{attachment:femMesh2.gif}}

== FEM conductivity tensors ==
Once the FEM mesh and the DTI tensors are available in the Brainstorm database, the next step is to compute the conductivity tensor for each of the FEM mesh element.

 * Right-click on the FEM mesh > '''Compute FEM tensors'''.
 * Brainstorm checks the available tissues in the FEM mesh and assigns a default '''isotropic conductivity''' value of the conductivity for each compartment. Users can change these values to their own if needed.
 * When selecting "'''Anisotropic'''" for a tissue, the DTI values are used to generate conductivity tensors: this is used mostly for the '''white matter''' (and in some cases for the grey matter). Note that DWI can be used only for the brain tissues and not for the outers compartments (skull and skin). The methods available are:
  * '''EMA''': Effective Medium Approach: See [[http://www.pnas.org/content/98/20/11697|(Tuch 2001)]].
  * '''EMA + VC''': EMA with volume constraints: The final tensors are constrained to fit the volume of the equivalent isotropic tensor volume.
  * '''Simulated''': Artificial anisotropy (DTI is not required)
 * For this example, select: WM:Anisotropic and Isotropic for the other tissues, EMA+VA.<<BR>><<BR>> {{attachment:computeTensors.gif}}
 * The FEM conductivity tensors are saved in the the FEM mesh file, in the field Tensors.<<BR>><<BR>> {{attachment:femContents.gif}}

== Visualization ==
 * Right-clicking on the FEM head > '''Display FEM tensors'''. The tensors can be displayed as ellipsoids or arrows (vectors in the direction of the main eigenvector) and overlaid on the MRI slices or the FEM mesh. <<BR>><<BR>> {{attachment:displayMenu.gif}}
 * On the FEM mesh: left=ellipsoids, right=arrows<<BR>><<BR>>{{attachment:femDisp1.gif}}
 * The orientation of the tensor is color-coded as follows:
  * '''Red''': right-left
  * '''Green''': anterior-posterior
  * '''Blue''': superior-inferior
 * To change the display options: Right-click on the figure > '''FEM tensors'''.
 * Use the keyboard shortcuts '''Up''' and '''Down''' to change the size of the graphical elements representing the tensors.
 * Note that the quality of the tensors depends on the DWI data and the number of acquisition direction.
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-== Dataset ==
In this tutorial, we use the Brainsuite dataset example available on the Brainsuite tutorial webpage
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-http://brainsuite.org/tutorials/. The T1w of the subject can be download from this link  [[http://brainsuite.org/WebTutorialData/BrainSuiteTutorialSVReg_Sept16.zip|BrainSuiteTutorialSVReg_Sept16.zip]]. The DWI from this link  [[http://brainsuite.org/WebTutorialData/DWI_Feb15.zip|DWI_Feb15.zip]]
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-The first link contains the T1 MRI, with the name '2523412.nii.gz'. as in this figure,
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-{{attachment:vierMriFolder.JPG||height="130",width="580"}}
+ {{attachment:tensorsOnMri.JPG||width="300",height="300"}}
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-The second file is the DWI and should contain at least three files
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-{{attachment:vierDWIFolder.JPG||height="150",width="580"}}
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-Where the *.bval is a text file that contains the value of the gradient, and the *.bvec is also a text file that contains the orientation of the gradient. The nii.gz file is the NifTi file of the DWI where the images are stored.
+<<TAG(Advanced)>>
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-== Realistic condctivity tensors ==
First, you need to create a new subject in your protocol, let call it the 'BrainSuiteSubject'. Then import the T1 MRI of the subject and set the fiducials points as explained in the previous tutorial.
+== Simulated conductivity tensor ==
In the case where the DWI is not available, or in the case where the users desire to evaluate the effect of the conductivity change on the head model, the artificial conductivity can be used.
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+Line 108:
-{{attachment:mri.JPG||height="100",width="250"}}
+Users can reach this option by following this tutorial and select the third method in this panel. {{attachment:artificialTensors.JPG||width="280",height="450"}}
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+Line 110:
-=== Diffusion tensor generation (DTI) from DWI ===
Right-click on the subject and then select the item "Convert DWI to DTI".
+Two approaches are integrated within Brainstorm. Either Wang's constraint or the volume's constraint (Wolters). The common feature between these methods is the ratio between the transversal and longitudinal conductivity ratio.
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+Line 112:
-Then follow the popup windows by selecting the DWI, bval, and bval. If these files are in the same folder, Brainstorm will detect them automatically, otherwise, the user will be asked to browse the files one by one (as it's the case in this tutorial).
+A common example is the skull anisotropy simulation, where the longitudinal conductivity can be higher than the transversal conductivity, the ratio can vary from 2 to 10 [ref]. In this tutorial, we keep all the tissue as isotropic, except the skull, we use a ratio of 0.1 and select the volume constraint. The following figures show the results of this example.
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-In this step, Brainstorm calls the Brainsuite internally, and the diffusion tensors are computed. At the end of this process, a new node will appear in the Brainstorm database with the name 'DTI-EIT'. This name refers to, DTI: diffusion tensors images, and EIG for eigenvalue, since the eigenvalues and eigenvectors are computed at voxel and stored in Brainstorm database.
+"eigenvalues parallel (longitudinal) and perpendicular (transverse) to the fiber directions" for 1:10 anisotropy (transverse:longitudinal)
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+Line 116:
-{{attachment:mriAndDTI-EIG.JPG||height="100",width="250"}}
+{{attachment:skullAniso.JPG||width="300",height="250"}} {{attachment:skullAniso2.JPG||width="300",height="250"}}
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-=== Conductivity tensor generation from DTI ===
The Effective Medium Approach is applied to convert the diffusion tensors to the conductivity tensors. This step requires the FEM mesh of the head model. You can generate the FEM head model from the MRI as explained on this page (add link).
+== Additional documentation ==
==== Related tutorials ====
 * [[https://neuroimage.usc.edu/brainstorm/Tutorials/Duneuro|Realistic head model: FEM with DUNEuro]]
 * [[https://neuroimage.usc.edu/brainstorm/Tutorials/FemMesh|FEM mesh generation]]
 * [[https://neuroimage.usc.edu/brainstorm/Tutorials/FemTensors|FEM tensors estimation]]
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-For the following, we used the SimNibs FEM mesh generation. The following figure shows the FEM mesh obtained from using the T1 MRI. Note that this mesh is obtained only from the T1, the use of the T2 is highly recommended if it's available.

The FEM head model to use for tensors should be selected and highlighted with the green color (double click on the FEM mesh node to select it)

When this is done, then right-click on the subject > Convert DWI to DTI,

Brainstorm will load the available tissue in the FEM head model and the following windows appear.

Select the WM anisotropy and kee all the other tissues as isotropic.

The process of conversion from DWI to Conductivity tensors uses the EMA, furthermore, brainstorm proposes the option to use the adaptative EMA with the volume constraint option [ref]. In this example, we select the EMA with the VC.

The process will take around 10 min, and then the FEM tensors are computed and stored in the FEM structure. [explain how it is organized and how to use it outside brainstorm ]

=== Display the tensors ===
== Artificial/simulated conductivity tensors ==
In the case where the DWI is not available, or the users desire to evaluate the effect of the conductivity change on the model, the artificial conductivity can be used.

Two approaches are integrated within Brainstorm. Either the

== References ==
+==== Articles ====
 * Medani T, Garcia-Prieto J, Tadel F, Schrader S, Joshi A, Engwer C, Wolters CH, Mosher JC, Leahy RM, [[https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11595/1159554/Realistic-head-modeling-of-electromagnetic-brain-activity--an-integrated/10.1117/12.2580935.short?SSO=1|Realistic head modeling of electromagnetic brain activity: An integrated Brainstorm pipeline from MRI data to the FEM solution]] ([[http://arxiv.org/abs/2011.01292|preprint]]), '''SPIE Medical Imaging''', 2021
 * Tuch DS, Wedeen VJ, Dale AM, George JS, Belliveau JW, [[https://www.pnas.org/content/98/20/11697|Conductivity tensor mapping of the human brain using diffusion tensor MRI]], '''PNAS''', 2001

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