How to Analyze dMRI

Most DSI Studio diffusion MRI workflows begin with the same three steps:

  1. Create SRC files (.sz) from DICOM or NIFTI diffusion data.
  2. Run SRC quality control and exclude or correct problematic data before group analysis.
  3. Reconstruct FIB files (.fz) using GQI for native-space analysis or QSDR when template-space reconstruction is needed.

After reconstruction, choose the analysis that matches the scientific question.

Region-Based Analysis

Use region-based analysis when the question concerns diffusion measurements within an anatomical region.

  1. Open the subject .fz file in Step T3: Fiber Tracking.
  2. Load or define regions. Built-in atlases are usually the simplest choice for standardized regions.
  3. If needed, use [Slices][Insert Other Images] to add registered measurements such as DKI, NODDI, PET, or other NIFTI data.
  4. Use [Regions][Statistics] to obtain diffusion or other image measurements from the selected regions.

For population/template-space region analysis, create a .dz connectometry database from QSDR FIB files reconstructed into the same template space and resolution, then open the database in Step T3. Regions used with a population database should be defined in the corresponding template space.

Tractometry

Tractometry quantifies diffusion or other measurements along white-matter pathways.

  1. Map the pathways using automatic fiber tracking or ROI-based fiber tracking.
  2. Add other image measurements with [Slices][Insert Other Images] when needed.
  3. Use [Tracts][Statistics] for tract-level summary measurements.
  4. Use the tract profile when the spatial distribution of a measurement along the pathway is important.

For population/template-space tractometry, a .dz database can be opened in Step T3 and analyzed with template-space pathways.

Example study: https://www.nature.com/articles/nn.3870

Differential Tractography

Differential tractography maps pathway segments showing changes in diffusion measurements between scans or relative to a reference population.

Use the dedicated Differential Tractography documentation for the four common designs:

Example study: https://pubmed.ncbi.nlm.nih.gov/31472253/

Correlational Tractography / Connectometry

Correlational tractography maps pathway segments whose diffusion measurements are associated with a study variable across a population. Connectometry uses permutation testing to estimate the statistical reliability of those findings.

The current workflow is:

  1. Reconstruct the cohort with QSDR using the same template space and resolution, then create a connectometry database (.dz) from those FIB files.
  2. Load and verify demographics, then select covariates, the study variable, and diffusion index.
  3. Run group connectometry and review the tract findings and FDR.

A current .dz database can store multiple diffusion indices, so separate database files are generally not required for QA, FA, RDI, and other available metrics.

Example studies: 1 · 2 · 3

Tract-to-Region (T2R) Connectome

The tract-to-region (T2R) connectome quantifies which named white-matter pathways innervate particular brain regions. It complements the conventional region-to-region (R2R) connectome by retaining the identity of the intervening tract.

  1. Map the pathways using AutoTrack.
  2. Load a brain parcellation from [Step T3a][Atlas], such as HCP-MMP.
  3. Use [Regions][Tract-to-Region Connectome] to generate the tract-by-region matrix.
  4. The parcellation can be colored by T2R values for visualization.

Example study: Yeh, Fang-Cheng. “Population-based tract-to-region connectome of the human brain and its hierarchical topology.” Nature Communications 13, 4933 (2022).