title: A novel measure of reliability in Diffusion Tensor Imaging after data rejections due to subject motion.
abstract: Diffusion Tensor Imaging (DTI) is commonly challenged by subject motion during data acquisition, which often leads to corrupted image data. Currently used procedure in DTI analysis is to correct or completely reject such data before tensor estimations, however assessing the reliability and accuracy of the estimated tensor in such situations has evaded previous studies. This work aims to define the loss of data accuracy with increasing image rejections, and to define a robust method for assessing reliability of the result at voxel level. We carried out simulations of every possible sub-scheme (N=1,073,567,387) of Jones30 gradient scheme, followed by confirming the idea with MRI data from four newborn and three adult subjects. We assessed the relative error of the most commonly used tensor estimates for DTI and tractography studies, fractional anisotropy (FA) and the major orientation vector (V1), respectively. The error was estimated using two measures, the widely used electric potential (EP) criteria as well as the rotationally variant condition number (CN). Our results show that CN and EP are comparable in situations with very few rejections, but CN becomes clearly more sensitive to depicting errors when more gradient vectors and images were rejected. The error in FA and V1 was also found depend on the actual FA level in the given voxel; low actual FA levels were related to high relative errors in the FA and V1 estimates. Finally, the results were confirmed with clinical MRI data. This showed that the errors after rejections are, indeed, inhomogeneous across brain regions. The FA and V1 errors become progressively larger when moving from the thick white matter bundles towards more superficial subcortical structures. Our findings suggest that i) CN is a useful estimator of data reliability at voxel level, and ii) DTI preprocessing with data rejections leads to major challenges when assessing brain tissue with lower FA levels, such as all newborn brain, as well as the adult superficial, subcortical areas commonly traced in precise connectivity analyses between cortical regions.
authors.affiliation: Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland; HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital Finland, P.O. Box 340, FI-00029 HUS, Finland. Electronic address: viljami.sairanen@helsinki.fi.
authors.forename: Viljami
authors.initials: V
authors.lastname: Sairanen
authors.affiliation: Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland; HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital Finland, P.O. Box 340, FI-00029 HUS, Finland.
authors.forename: L
authors.initials: L
authors.lastname: Kuusela
authors.affiliation: HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital Finland, P.O. Box 340, FI-00029 HUS, Finland.
authors.forename: O
authors.initials: O
authors.lastname: Sipilä
authors.affiliation: Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland; HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital Finland, P.O. Box 340, FI-00029 HUS, Finland.
authors.forename: S
authors.initials: S
authors.lastname: Savolainen
authors.affiliation: Departments of Children's Clinical Neurophysiology and HUS Imaging, Children's Hospital, Helsinki University Central Hospital, Helsinki, Finland; Department of Neurological Sciences, University of Helsinki, Finland.
authors.forename: S
authors.initials: S
authors.lastname: Vanhatalo
mesh_terms: D000328:Adult; D000465:Algorithms; D016880:Anisotropy; D016477:Artifacts; D003198:Computer Simulation; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007231:Infant, Newborn; D008297:Male; D009038:Motion; D015203:Reproducibility of Results; D066127:White Matter
keywords: Condition number; Diffusion Tensor Imaging; Fractional anisotropy; Neonatal MRI; Quality; Tractography