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Neurodegenerative changes in Alzheimer's disease: A comparative study of manual, semi-automated and fully automated assessment using MRI

: Fritzsche, K.H.; Giesel, F.L.; Heimann, T.; Thomann, P.A.; Hahn, H.K.; Pantel, J.; Schröder, J.; Essig, M.; Meinzer, H.-P.


Giger, M.L. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.; American Association of Physicists in Medicine -AAPM-:
Medical imaging 2008 - computer-aided diagnosis : 19 - 21 February 2008, San Diego, California, USA
Bellingham, WA: SPIE, 2008 (SPIE Proceedings Series 6915)
ISBN: 978-0-8194-7099-7
Art. 69151V
Medical Imaging Meeting <2008, San Diego/Calif.>
Conference Paper
Fraunhofer MEVIS ()

Objective quantification of disease specific neurodegenerative changes can facilitate diagnosis and therapeutic monitoring in several neuropsychiatrie disorders. Reproducibility and easy-to-perform assessment are essential to ensure applicability in clinical environments. Aim of this comparative study is the evaluation of a fully automated approach that assesses atrophic changes in Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI). 21 healthy volunteers (mean age 66.2), 21 patients with MCI (66.6), and 10 patients with AD (65.1) were enrolled. Subjects underwent extensive neuropsychological testing and MRI was conducted on a 1.5 Tesla clinical scanner. Atrophic changes were measured automatically by a series of image processing steps including state of the art brain mapping techniques. Results were compared with two reference approaches: a manual segmentation of the hippocampal formation and a semi-automated estimation of temporal horn volume, which is based upon interactive selection of two to six landmarks in the ventricular system. All approaches separated controls and AD patients significantly (10-5 < p < 10-4) and showed a slight but not significant increase of neurodegeneration for subjects with MCI compared to volunteers. The automated approach correlated significantly with the manual (r = -0.65, p < 10 -6) and semi automated (r = -0.83, p < 10-13) measurements. It proved high accuracy and at the same time maximized observer independency, time reduction and thus usefulness for clinical routine.