title: Statistical estimation of white matter microstructure from conventional MRI.
abstract: Diffusion tensor imaging (DTI) has become the predominant modality for studying white matter integrity in multiple sclerosis (MS) and other neurological disorders. Unfortunately, the use of DTI-based biomarkers in large multi-center studies is hindered by systematic biases that confound the study of disease-related changes. Furthermore, the site-to-site variability in multi-center studies is significantly higher for DTI than that for conventional MRI-based markers. In our study, we apply the Quantitative MR Estimation Employing Normalization (QuEEN) model to estimate the four DTI measures: MD, FA, RD, and AD. QuEEN uses a voxel-wise generalized additive regression model to relate the normalized intensities of one or more conventional MRI modalities to a quantitative modality, such as DTI. We assess the accuracy of the models by comparing the prediction error of estimated DTI images to the scan-rescan error in subjects with two sets of scans. Across the four DTI measures, the performance of the models is not consistent: Both MD and RD estimations appear to be quite accurate, while AD estimation is less accurate than MD and RD; the accuracy of FA estimation is poor. Thus, in some cases when assessing white matter integrity, it may be sufficient to acquire conventional MRI sequences alone.
authors.affiliation: Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States.
authors.forename: Leah H
authors.initials: LH
authors.lastname: Suttner
authors.affiliation: Department of Biostatistics, The Johns Hopkins University, Baltimore, MD 21205, United States.
authors.forename: Amanda
authors.initials: A
authors.lastname: Mejia
authors.affiliation: Translational Neuroradiology Unit, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disease and Stroke, National Institute of Health, Bethesda, MD 20892, United States.
authors.forename: Blake
authors.initials: B
authors.lastname: Dewey
authors.affiliation: Translational Neuroradiology Unit, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disease and Stroke, National Institute of Health, Bethesda, MD 20892, United States.
authors.forename: Pascal
authors.initials: P
authors.lastname: Sati
authors.affiliation: Department of Biostatistics, The Johns Hopkins University, Baltimore, MD 21205, United States; Translational Neuroradiology Unit, Division of Neuroimmunology and Neurovirology, National Institute of Neurological Disease and Stroke, National Institute of Health, Bethesda, MD 20892, United States.
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Reich
authors.affiliation: Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States.
authors.forename: Russell T
authors.initials: RT
authors.lastname: Shinohara
mesh_terms: D000328:Adult; D056324:Diffusion Tensor Imaging / Q000592:standards; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000592:standards*; D008297:Male; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000000981:diagnostic imaging*; D066127:White Matter / Q000000981:diagnostic imaging*
keywords: Image synthesis