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Brain Struct Funct. 2018 Jun;223(5):2269-2285. doi: 10.1007/s00429-018-1628-y. Epub 2018 Feb 20.

Diffusion MRI-based cortical connectome reconstruction: dependency on tractography procedures and neuroanatomical characteristics.

Author information

1
Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht/Utrecht University, Yalelaan 2, 3584 CM, Utrecht, The Netherlands. m.r.t.sinke@umcutrecht.nl.
2
Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht/Utrecht University, Yalelaan 2, 3584 CM, Utrecht, The Netherlands.
3
Department of Pediatric Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht/Utrecht University, Utrecht, The Netherlands.
4
Department of Electrical Engineering, KU Leuven, ESAT/PSI, Leuven, Belgium.
5
Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
6
Department of Anatomy, University of Rostock, Rostock, Germany.
7
Image Sciences Institute, University Medical Center Utrecht/Utrecht University, Utrecht, The Netherlands.
8
Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht/Utrecht University, Utrecht, The Netherlands.
9
University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.

Abstract

Diffusion MRI (dMRI)-based tractography offers unique abilities to map whole-brain structural connections in human and animal brains. However, dMRI-based tractography indirectly measures white matter tracts, with suboptimal accuracy and reliability. Recently, sophisticated methods including constrained spherical deconvolution (CSD) and global tractography have been developed to improve tract reconstructions through modeling of more complex fiber orientations. Our study aimed to determine the accuracy of connectome reconstruction for three dMRI-based tractography approaches: diffusion tensor (DT)-based, CSD-based and global tractography. Therefore, we validated whole brain structural connectome reconstructions based on ten ultrahigh-resolution dMRI rat brain scans and 106 cortical regions, from which varying tractography parameters were compared against standardized neuronal tracer data. All tested tractography methods generated considerable numbers of false positive and false negative connections. There was a parameter range trade-off between sensitivity: 0.06-0.63 interhemispherically and 0.22-0.86 intrahemispherically; and specificity: 0.99-0.60 interhemispherically and 0.99-0.23 intrahemispherically. Furthermore, performance of all tractography methods decreased with increasing spatial distance between connected regions. Similar patterns and trade-offs were found, when we applied spherical deconvolution informed filtering of tractograms, streamline thresholding and group-based average network thresholding. Despite the potential of CSD-based and global tractography to handle complex fiber orientations at voxel level, reconstruction accuracy, especially for long-distance connections, remains a challenge. Hence, connectome reconstruction benefits from varying parameter settings and combination of tractography methods to account for anatomical variation of neuronal pathways.

KEYWORDS:

Brain; Brain connectomics; Constrained spherical deconvolution; Diffusion MRI; Diffusion tractography; Neuronal tracers; Rats

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