ADNI data for HCP Pipeline

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Scott Gurney

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Apr 16, 2024, 11:40:00 AMApr 16

to Alzheimer's Disease Neuroimaging Initiative (ADNI) Data

Good afternoon,

I wish to use the HCP Pipeline to preprocess ADNI subjects. From their FAQ page I need to have the following data:

3. What MRI data do I need to use the HCP Pipelines?

For structural analysis, one needs a high-resolution 3D (<=1mm) T1w image and either a high-resolution 3D (<=1mm) T2w image or a high-resolution 3D (<=1mm) FLAIR image. Higher than 1mm resolution is recommended if possible (e.g. <=0.8mm). FatSat is recommended for the T1w image. Scanner-based intensity normalizations (like Siemens PreScan Normalize) must be either on for both T1w and T2w images or off for both.
For functional analysis, one needs an fMRI timeseries (if the scans are multi-band, it is highly recommended to save the single-band reference scan) and either a standard gradient echo field map (magnitude and phase difference) or a spin echo field map (two phase encoding direction reversed spin echo volumes with the same geometrical and echo spacing parameters as the fMRI timeseries). High spatial (<=2.5mm) and temporal (TR<=1s) resolution fMRI data is recommended.
For diffusion analysis, one needs phase encoding direction reversed diffusion data. High spatial (<=1.5mm) and angular (>=120 directions) resolution diffusion data is recommended with multiple shells that include a higher bvalue (>=1500).
Functional and diffusion preprocessing also require the scans needed for structural preprocessing.
For the Siemens HCP 3T Connectom scanner, we found the 32-channel head coil and higher maximum gradient strength to be very helpful.
- The use of Connectom when referring to the scanner itself is not a typographical error. Siemens considers the custom 3T scanner used for the Human Connectome Project to be the "Connectom" scanner.

I have already selected my subjects and have structural and functional data for each but I am unsure which exact file(s) I need to use.

If it is any help I have previously successfully used these ADNI subjects, converting to BIDS and then importing and preprocess with CONN, so I have that output too.