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Create a connectometry database

This documentation introduces the steps to create a connectometry database. A connectometry database contains information of the subjects' diffusion profile that allows further connectometry analysis.

STEP1: Reconstruct data in the MNI space

The following steps reconstruct all subjects' diffusion data in the MNI space. 

STEP1a: Arrange the folder structure

    Store the image files using the following tree structure. The image data of each subject should be stored by a folder named by his/her subject ID, and all the folders are placed under a common study folder.

[study x]   -> the study folder storing all the study files
     |-[001]    -> the subject folder storing the image file of subject 001
     |-[002]    -> the subject folder storing the image file of subject 002

     The name of the image files should following the look-up rule details here.     

*I would recommend to preprocess nii files using FSL' TOPUP and eddy before proceeding to STEP2.  

STEP1b: Batch create the SRC files

Click on [Tools: Batch Processing][Create SRC files] and select the study folder. DSI Studio will generate an SRC within each subject's folder.

* You may also use [STEP2 Reconstruction] to reconstruct the SRC files. In the reconstruction window, you may need to specify [QSDR] as the method and check "Output ODF" in the advanced setting. The output resolution should be either 1mm or 2mm.

*If DSI Studio fails to create SRC file for your data, please contact Frank.

STEP1c: Check SRC files

as described here, discard problematic data set.

STEP1d: Reconstruct all image data 

Click [Diffusion MRI Connectometry][Reconstruct SRC files for connectometry] and select the study folder. DSI Studio will generate an FIB file within each subject's folder.

STEP1e: Post-reconstruction quality check

Get a list of the FIB files generated in the subjects' folders (search *.fib.gz file). Each FIB file generated from the previous step will has a file name such as *.odf8.f5rec.cdm.qsdr.1.25.2mm.R67.fib.gz. The R67 indicates that the R-sqaured value between the subject and the template's QA map is 0.67. 

**An R-squared value lower than 0.5 may require further inspection to confirm whether it is due to registration error**.

The most common cause for a low R2 is an inverse order of the axial slices, which can be corrected in the reconstruction step to flip the image volume at the Z direction. The second common cause is a prominent artifact in the background, which may be handled by introducing a brain mask and use [Edit][Trim Image] in the reconstruction step to clean up the background. 

If you still cannot solve the low R2 value problem, please feel free to send the data to me (uploaded provided in the webpage of the Discussion forum), and I will figure out a solution for you.

STEP2: Create a connectometry database

A connectometry database requires the ODF-containing fib files for all subjects and an atlas that serves as the sampling skeleton.

1) In the connectometry toolbox, click "Step 1: create connectometry database".

This brings up the following dialog.

2) Click the [Search in Directory] and select the study folder. You may also use the "Add" button to select individual FIB file. You can change the order of the files by the "up", "down", "sort" button. You can save/load a list of the SRC files.

*If you are going to study the change in a longitudinal study, make sure that you place baseline and followup scans of the same subject together (e.g. base of s#1, followup of #1, base of s#2, followup of s#2...etc.)

3) Assign the atlas file (skip if a default file is assigned). I recommend using the latest HCP 842 atlas, which is available at Atlas and sample images. The latest version of DSI Studio has it shipped with the package and will load it as the default. Using the default HCP842 template meaning that the HCP subjects (young aged adult) can be representative to your subject pool. If this is not true, you should consider create your own atlas. The choice depends entirely on your study and subject pool. 

4) Assign "Index of interest" (skip if using SDF as the default): You can also study other diffusion measures using connectometry. see Optional section at the bottom of this page).

4) Specify the output file name.

    Please assign the file extension as *.db.fib.gz

5) Click the "Create Database" button to create the connectometry database as a db.fib.gz file. You can add or remove subjects from the database using [Diffusion MRI Connectometry][Edit Connectometry Database]

6) Once you have the connectometry database, you can run group connectometry.

Optional: Constructing a connectometry database using other diffusion measures (e.g. FA, MD, ...etc)

It is possible to construct a connectometry using FA, MD, or any other voxel-based measures. This allows for testing any diffusion measures using the connectometry paradigm. Using FA as an example, the following is a list of the steps using graphic user interface to create such a connectometry database. You can also use command line to batch process a large amount of subjects.

STEP1: Generate FA map for each individuals in the native diffusion MRI space:
Open the SRC files in [STEP 2:Reconstruction] and run DTI reconstruction to get the FIB file. Open the FIB file in [STEP 3: Fiber tracking]. Export the FA map using [Views][Save fa volume as]. To export MD, change the drop list in the region window from "fa" to "md" and save the MD map by [Views][Save md volume as].

You can use anyother diffusion measures here as long as the image space is the same as the diffusion space. The file must be saved in the nifti format. 

STEP2: Spatial normalization
Open the subject's SRC file again in [STEP 2:Reconstruction]. Switch to the last tab and choose QSDR. Click [Add T1W/T2W] button and select the subject's FA map. You can click the button again to add other measures. 

Check "ODFs" in the Output section.

Run reconstruction to get the subjects FIB file.

STEP3: Constructing a connectometry database
Follow the "STEP2" on the top of this page and select "fa" in the [Index of interest] to create a connectometry database. The created connectometry database will use FA as the measurement for connectometry analysis.