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How many streamlines are required for reliable probabilistic tractography? Solutions for microstructural measurements and neurosurgical planning
Author(s) -
Lee B. Reid,
Marcela Céspedes,
Kerstin Pannek
Publication year - 2020
Publication title -
neuroimage
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.259
H-Index - 364
eISSN - 1095-9572
pISSN - 1053-8119
DOI - 10.1016/j.neuroimage.2020.116646
Subject(s) - streamlines, streaklines, and pathlines , tractography , probabilistic logic , computer science , geology , radiology , artificial intelligence , medicine , diffusion mri , physics , magnetic resonance imaging , mechanics
Diffusion MRI tractography is commonly used to delineate white matter tracts. These delineations can be used for planning neurosurgery or for identifying regions of interest from which microstructural measurements can be taken. Probabilistic tractography produces different delineations each time it is run, potentially leading to microstructural measurements or anatomical delineations that are not reproducible. Generating a sufficiently large number of streamlines is required to avoid this scenario, but what constitutes "sufficient" is difficult to assess and so streamline counts are typically chosen in an arbitrary or qualitative manner. This work explores several factors influencing tractography reliability and details two methods for estimating this reliability. The first method automatically estimates the number of streamlines required to achieve reliable microstructural measurements, whilst the second estimates the number of streamlines required to achieve a reliable binarised trackmap than can be used clinically. Using these methods, we calculated the number of streamlines required to achieve a range of quantitative reproducibility criteria for three anatomical tracts in 40 Human Connectome Project datasets. Actual reproducibility was checked by repeatedly generating the tractograms with the calculated numbers of streamlines. We found that the required number of streamlines varied strongly by anatomical tract, image resolution, number of diffusion directions, the degree of reliability desired, the microstructural measurement of interest, and/or the specifics on how the tractogram was converted to a binary volume. The proposed methods consistently predicted streamline counts that achieved the target reproducibility. Implementations are made available to enable the scientific community to more-easily achieve reproducible tractography.

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