Effects of diffusion MRI spatial resolution on human brain short-range association fiber reconstruction and structural connectivity estimation.

Short-range association fibers (SAFs) are critical for cortical communications but are often underestimated in conventional resolution diffusion magnetic resonance imaging (dMRI) since they locate within a ~1.5 mm thin layer of superficial white matter. With the advent of high-resolution diffusion imaging techniques, this study evaluated the effects of image spatial resolution on SAF reconstruction using two datasets: (1) prospectively acquired dMRI data from 20 healthy subjects, each scanned at 3 resolutions (i.e., 2, 1.5, and 0.96 mm iso.), and (2) retrospectively down-sampled dMRI data from the Human Connectome Project dataset, as well as 20 representative MRtrix3-based tractography pipelines. It was found that lower resolution degraded superficial white matter model fitting, lowered the SAF streamline counts, and reduced global and regional short-range connectivity fraction (SCF), defined as the fraction of SAF connections among all association fiber connections, across all tested methods. Temporal lobe cortical regions exhibited the greatest SCF declines at lower resolutions. Tractography methods differed in resolution sensitivity, with diffusion tensor imaging (DTI)-based single-tissue single-fiber tractography showing greater decreases in SCF than constrained spherical deconvolution (CSD)-based multi-tissue multi-fiber tractography at lower resolutions. Probabilistic, anatomically constrained tractography combined with spherical-deconvolution informed filtering of tractograms was more robust to decreases in resolution. Up-sampling to a nominally higher resolution partially improved model fitting and SCF accuracy across the evaluated pipelines, with the greatest effect observed for DTI. Using the 0.96 mm iso. gSlider data and optimized tractography pipelines from this study, we constructed the first human brain atlas of RSCF. In summary, this study provides a systematic and quantitative evaluation using MRtrix3 of how spatial resolution, fiber models, and tracking methodologies affect SAF reconstruction and structural connectivity estimation, serving as a reference framework for methodological choices. These advances may enhance the characterization of both healthy and diseased human brains across a wide range of neuroscientific and clinical applications.