Acquisition-related morphological variability in structural MRI.
OBJECTIVE
Significant effort has been spent during the past decades to develop innovative image-processing algorithms and improve existing methods in terms of precision, reproducibility, and computational efficiency, but relatively little research was undertaken to find out the extent to which the validity of results obtained with these methods is limited by inherent imperfections of the input images. This observation is especially true for magnetic resonance imaging (MRI)-based morphometry, which aims at precise and highly reproducible determination of geometric properties of anatomic structures, although MRI images are geometrically distorted.


METHODS
A method for characterization of site-specific geometric distortions and results of a long-term study designed to find the extent to which imperfections in the data-acquisition process limit the reliable detection of subtle morphological changes in MRI data acquired with state-of-the-art scanners are presented. Because of the long-term character of the study, results include effects resulting from limited hardware stability, as well as from imperfections in patient repositioning.


RESULTS
Maximal relative morphological changes detected in our phantom data series were 1.0 mm positional and 2.0% volumetric difference (relative to a 7600-mm3 cuboid) in a subvolume relevant for whole-brain morphometry. Morphological variability was even greater for human volunteer data (up to 5% in local gray matter volume) because of movements during scan, natural morphological variability, and a presumably less precise segmentation procedure.


CONCLUSIONS
Imperfections in the MRI data-acquisition process in combination with practical limitations in patient repositioning can substantially confound studies of subtle morphological changes.
Littmann
Arne
A
Siemens Medical Solutions, Magnetic Resonance, MREA, Karl-Schall-Str 6, 91052 Erlangen, Germany. arne.littmann@siemens.com
Guehring
Jens
J
Buechel
Christian
C
Stiehl
Hans-Siegfried
HS
D000465:Algorithms; D016477:Artifacts; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity