Table 3.
Summary of the tractographic analysis parameters of the included studies.
| Article | Signal modeling | Deterministic | Probabilistic | FA or other threshold | Max curvature | Steps (mm) | Streamline generation | Other (e.g., filtering) |
|---|---|---|---|---|---|---|---|---|
| He (2021) | DTI; CSD | SD-Stream, UKF-1 T, UKF-2 T | iFOD1 | seed = 0.006; stop = 0.005 (SD-Stream. iFOD1) | SD-Stream: 80° | NA | 40,000 fibers generated for each method | Fiber threshold length = 45 mm |
| seed = 0.02; stop = 0.01 (UKFs) | iFOD-1: 10° | |||||||
| Jin (2019) | DTI; GQI | DSI-Studio TRACKVIS | no | 0.04 | 50° | 1.2 | 1500 fibers reconstructed | |
| Kammen (2016) | CSD | No | ConTrack | NA | 2 mm | NA | 1000 streamlines generated | |
| Kamali (2014) | DTI | DTI-Studio software FACT | no | 0.22 | 60° | NA | Spurious fiber cleaning with ROEs (see Table 4) | |
| Maleki (2012) | DTI | No | FSL 4.1.3 | 0.2 | 0.2 | 0.5 | 25,000 streamlines generated | |
| Akazawa (2010) | DTI | PRIDE software (2 tensor model) | no | Principal diffusivities (λ1, λ2, and λ3) were restricted respectively to range 1.2–1.8, 0.2–0.7, and 0.2–0.7 (10−3 mm2/s), to capture highly oriented fibers | NA | NA | ||
| Hofer (2010) | DTI | Tensorline | no | 0.1 | 70° | NA | ||
| Staempfli (2007) | DTI | aFM | no | NA | NA | NA | 60,000 to 65,000 time steps | 8 to 12% voxel connectivity |
| Manners (2022) | CSD | No | iFOD1 | seed = 0.006; stop = 0.005 | 10° | NA | ||
| Puzniak (2021) | DTI; CSD | DT based, CSD based | iFOD2 | NA | 5°, 10°, 20°, 40°, 80° | 0.15; 0.75 | 15,000 streamlines generated | Minimum length 7.5 mm; LiFE method for filtering spurious streamlines |
| Ather (2019) | DTI | No | PROBTRACKX2 | 0.1 | 0.2 mm | 0.5 | 5000 streamlines generated; two reconstructions (seed and target reversed) averaged together | |
| J Puzniak (2019) | DTI; CSD | DT Tensor Prob | iFOD2 | DT Tensor Prob: 0.04; 0.08. iFOD2: 0.04; 0.08 | 30°; 45°; 60° | NA | 139,000 streamlines generated. | Different spurious streamline filtering strategies (LIFE, COMMIT-SZB, COMMIT-SB, SIFT2) |
| Takemura (2019) | DTI | No | ConTrack | NA | 90° | 1 | 5000 streamlines generated. Only 1000 retained; two runs were performed on different DTI acquisitions and merged together | max streamline length 80 mm |
| Lecler (2018) | CSD | no | CSD based | NA | NA | NA | ||
| Davies-Thompson (2013) | DTI | No | FSL Probtrackx | NA | 0.2 | 0.5 | 5000 streamlines generated | |
| Miller (2019) | CSD | no | Mrtrix 2 CSD based | NA | NA | NA | 5,000,000 fibers generated | AFQ toolkit used to remove fibers 2.6 sd distance away from the fiber core. Further manual cleaning (superimposed on T1w) |
| Allen (2018) | CSD | no | Mrtrix CSD-based | 0.2 | 60° | 2 | manual spurious fiber cleaning | |
| Altıntaş (2017) | DTI | FACT | no | NA | NA | NA | ||
| Chakravarthi (2021) | DTI | BrightMatter Plan software | no | NA | NA | NA | whole brain tractography that also reconstructed the whole anterior visual pathway | |
| Liang (2021) | GQI | DSI-Studio software | no | 0.20–0.35 | 70° | 1.2 | minimum length 10 mm; maximum length 300 mm | |
| Ho (2019) | GQI | DSI-Studio software | no | NA | 60° | 0.6 | 10,000 fibers generated | minimum length 30 mm |
| Jacquesson (2019) | CSD | no | Mrtrix 3 “tckgen” | 0.3 | 45° | 1 | 1000 fibers generated | Spurious fiber cleaning with ROEs (see Table 4) |
| Wu (2019) | DTI | No | PROBTRACKX | NA | 0.2 | NA | 5000 streamlines generated | 10% threshold |
| Lin (2018) | DTI | Mimics research 17.0 software | no | NA | NA | NA | ||
| Ma (2017) | DTI | 3D Slicer software | no | 0.18 | 0.7 | 0.5 | Path length between 20 and 800 | |
| Zolal (2017) | CSD; GQI | DSI-Studio software | FSL 5.0 | 0.5 | 80° | 0.4 | For probabilistic tractography PICo maps were created. To find the optimal probability threshold for localizing the nerve, the resulting PICo maps were filtered at threshold values of 0.05–0.95 in steps of 0.05 | |
| Yoshino (2016) | GQI | DSI-Studio | no | 0.02–0.5 | 60-70° | 1.2 | 1000 to 10 000 streamlines generated | To smooth each tract, the next directional estimate of each voxel was weighted by 20% of the previous moving direction and by 80% of the incoming direction of the fiber |
| Haijabadi (2016) | DTI | BrainLAB workstation | no | 0.01 | NA | NA | Minimum fiber length 5 mm | |
| Ge (2015) | DTI | Neuro 3D software | no | 0.05 | 30° | NA | ||
| Hajiabadi (2015) | DTI | BrainLAB workstation | no | 0.15 | NA | NA | minimum fiber length: 21 mm | |
| De Blank (2013) | DTI | DTI-Studio software FACT | no | 0.15 | 70° | NA | ||
| Lober (2012) | DTI | InVivo Dynasuite software | no | 0.05 | 30° | NA | ||
| Zhang (2012) | DTI | dTV 1.72 software | no | 0.2 | NA | NA | ||
| Hodaie (2010) | DTI | 3D Slicer software | no | 0.2 | 0.8 | 0.5 | Manual fiber cleaning using “ROI select NOT” operation on spurious fibers | |
| Salmela (2009) | DTI | FACT | no | 0.15 | 27 | NA | Minimum fiber length 10 mm | |
| Tao (2009) | DTI | dTV 2.0 software | no | 0.15 | NA | <200 | ||
| Techavipoo (2009) | DTI | FACT | no | 0.25 | 80° | 0.8 | ||
| Lacerda (2021) | CSD | No | MRTrix, CSD based | NA | NA | NA | based on command 3Tissue to extract CSD | |
| Yang (2011) | DTI | dTV 2.0, Volume One 1.72 software | no | NA | NA | NA |
Abbreviations: DT – diffusion tensor; UKF - unscented Kalman filter; CSD – constrained spherical deconvolution; LiFE – linear fascicle evaluation; COMMIT - convex optimization modeling for microstructure informed tractography; SIFT - spherical-deconvolution informed filtering of tractograms; FACT – fiber assignment by continuous tracking; ROI – region of interest; PICo - probabilistic index of connectivity; NA – not assessed, aFM - advanced fast marching algorithm; FOD - fiber orientation density.