help > loss of b-value during DICOM to NIFTI
Showing 1-2 of 2 posts
Display:
Results per page:
Mar 27, 2023  02:03 PM | ZHENKAI ZHAO
loss of b-value during DICOM to NIFTI
Hi, 

I just started learing DWI image processing with MATLAB. my code needs to use NIFTI as input, so I chose to use MRIcroGL for conversion from DICOM files. 

The scanner I am using is Siemens MAGNETOM Vida, and the software version is syngo MR XA31. 

I used Chris Roden's dcm2niiX version v1.0.20220720 to work with the conversion.

I can confirm that the data file has not been anonymized before being exported, and they are exported as enhanced DICOM. 

I first tried the b-value equals 500 and the conversion was successful on diffusion images with b-val, b-vec and nifti file exported. 

when I tried smaller b-value like 50, 20, and 10, the conversion tool can generate b-val, b-vec and nifti file as well, but when I tried to open the nifti file can convert to SRC file, it said b-val is missing from the header, and I need to load the b-val mannually. I am not sure why this happens. 

May I ask for some suggestions related to my issue? 


Zhao
Mar 27, 2023  03:03 PM | Chris Rorden
RE: loss of b-value during DICOM to NIFTI
You need a higher b-value to model the water diffusion. A typical scan for DTI analysis has some images acquired with a b-value near 0 and some with strong weightings (e.g. b = 1000). You need a combination of both scans. One must apply a little bit of b-weighting, so on a Siemens scanner if you request a b=0 image, the resulting DICOM will show a low but non-zero value (e.g. b=10).

https://github.com/rordenlab/dcm2niix/bl...

From your description, it is unclear whether your issue is with dcm2niix or some other tool that expects a stronger b-value. However, it does seem inappropriate to calculate tensors and other derived diffusion values if all your images have virtually no spatial specificity. So this sounds like the correct behavior.

----------

DICOM files have changed considerably for XA31. Therefore, you will need to use the developmental branch of dcm2niix (currently v1.0.20230320) until the next stable version is released. For this reason, dcm2niix will not report b-values and vectors if they are all below 50 (as the series effectively does not have any b-weighting):

If you use Windows, you can get a compiled version here:
  https://ci.appveyor.com/project/neurolabusc/dcm2niix/build/artifacts

For MacOS and Linux you can compile your own:

git clone --branch development https://github.com/rordenlab/dcm2niix.gi...
cd dcm2niix/console
make
./dcm2niix ....

Validation XA30 data is here
  https://github.com/neurolabusc/dcm_qa_xa30
and XA51 data is here
  https://github.com/neurolabusc/dcm_qa_cs_dl


Be warned that XA is a radical departure for Siemens, and we are actively reverse engineering this format. If you have any problems, post an issue on Github:
 https://github.com/rordenlab/dcm2niix/