title: Combining boundary-based methods with tensor-based morphometry in the measurement of longitudinal brain change.
abstract: Tensor-based morphometry is a powerful tool for automatically computing longitudinal change in brain structure. Because of bias in images and in the algorithm itself, however, a penalty term and inverse consistency are needed to control the over-reporting of nonbiological change. These may force a tradeoff between the intrinsic sensitivity and specificity, potentially leading to an under-reporting of authentic biological change with time. We propose a new method incorporating prior information about tissue boundaries (where biological change is likely to exist) that aims to keep the robustness and specificity contributed by the penalty term and inverse consistency while maintaining localization and sensitivity. Results indicate that this method has improved sensitivity without increased noise. Thus it will have enhanced power to detect differences within normal aging and along the spectrum of cognitive impairment.
authors.affiliation: IDeA Laboratory, Department of Neurology, University of California-Davis, Davis, CA 95618, USA. evanfletcher@gmail.com
authors.forename: Evan
authors.initials: E
authors.lastname: Fletcher
authors.forename: Alexander
authors.initials: A
authors.lastname: Knaack
authors.forename: Baljeet
authors.initials: B
authors.lastname: Singh
authors.forename: Evan
authors.initials: E
authors.lastname: Lloyd
authors.forename: Evan
authors.initials: E
authors.lastname: Wu
authors.forename: Owen
authors.initials: O
authors.lastname: Carmichael
authors.forename: Charles
authors.initials: C
authors.lastname: DeCarli
mesh_terms: D000375:Aging / Q000473:pathology*; D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008137:Longitudinal Studies; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique