title: Detection of structural changes of the human brain in longitudinally acquired MR images by deformation field morphometry: methodological analysis, validation and application.
abstract: The progression of neurodegenerative diseases as well as healthy aging is accompanied by structural changes of the brain. These changes are often only subtle when considered over time intervals of several months. Therefore morphometrical techniques for their detection in longitudinally acquired MR images must be highly sensitive, and they require a careful validation. In the present study, a novel processing chain for a longitudinal analysis based on deformation field morphometry is described. Procedures for its quantitative validation are also reported: Deformation fields were computed for the simulation of non-linear, local structural changes of human brains. Applying these deformation fields to "original" MR images yielded deformed MR images. The volume changes defined by the deformation fields represented the standard, against which the results of the longitudinal analysis of each pair of original and deformed MR image were compared. The proposed processing chain enabled to localize and to quantify simulated local atrophies near the cortex as well as in deep brain structures. An exemplary analysis of serial MR images of a patient suffering from an atypical Parkinson syndrome (cortico-basal degeneration, CBD) and healthy control subjects is presented, showing a characteristic pattern of volume changes in the brain of the patient which is strikingly different from the controls' patterns of changes.
authors.affiliation: Institute of Neurosciences and Biophysics, Medicine Research Centre Jülich, Jülich, Germany. p.pieperhoff@fz-juelich.de
authors.forename: P
authors.initials: P
authors.lastname: Pieperhoff
authors.forename: M
authors.initials: M
authors.lastname: Südmeyer
authors.forename: L
authors.initials: L
authors.lastname: Hömke
authors.forename: K
authors.initials: K
authors.lastname: Zilles
authors.forename: A
authors.initials: A
authors.lastname: Schnitzler
authors.forename: K
authors.initials: K
authors.lastname: Amunts
mesh_terms: D000465:Algorithms; D001921:Brain / Q000473:pathology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D019636:Neurodegenerative Diseases / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013382:Subtraction Technique