Performance of Hippocampus Volumetry with FSL-FIRST for Prediction of Alzheimer’s Disease Dementia in at Risk Subjects with Amnestic Mild Cognitive Impairment

Article type: Research Article

Authors: Suppa, Per^{a; b} | Hampel, Harald^c | Kepp, Timo^b | Lange, Catharina^a | Spies, Lothar^b | Fiebach, Jochen B.^d | Dubois, Bruno^{c; 1} | Buchert, Ralph^{a; 1; *} | for the Alzheimer’s Disease Neuroimaging Initiative²

Affiliations: [a] Department of Nuclear Medicine, Charité, Berlin, Germany | [b] Jung diagnostics GmbH, Hamburg, Germany | [c] Université Pierre et Marie Curie, Institut de la Mémoire et de la Maladie d’Alzheimer & INSERM U1127, Institut du Cerveau et de la Moelle épinière (ICM), Département de Neurologie, Hôpital de la Pitié-Salpétrière, Paris, France | [d] Center for Stroke Research Berlin, Charité, Berlin, Germany

Correspondence: [*] Correspondence to: Ralph Buchert, PhD; Charité – Universitätsmedizin Berlin, Department of Nuclear Medicine, Charitéplatz 1, 10117 Berlin, Germany. Tel.: +49 30 450627059; Fax: +49 30 4507527959; E-mail: [email protected].

Note: [1] The authors contributed equally to this work as senior authors.

Note: [2] Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

Abstract: MRI-based hippocampus volume, a core feasible biomarker of Alzheimer’s disease (AD), is not yet widely used in clinical patient care, partly due to lack of validation of software tools for hippocampal volumetry that are compatible with routine workflow. Here, we evaluate fully-automated and computationally efficient hippocampal volumetry with FSL-FIRST for prediction of AD dementia (ADD) in subjects with amnestic mild cognitive impairment (aMCI) from phase 1 of the Alzheimer’s Disease Neuroimaging Initiative. Receiver operating characteristic analysis of FSL-FIRST hippocampal volume (corrected for head size and age) revealed an area under the curve of 0.79, 0.70, and 0.70 for prediction of aMCI-to-ADD conversion within 12, 24, or 36 months, respectively. Thus, FSL-FIRST provides about the same power for prediction of progression to ADD in aMCI as other volumetry methods.

Keywords: ADNI, Alzheimer’s disease, aMCI-to-Alzheimer’s disease dementia conversion, amnestic mild cognitive impairment, FSL-FIRST, fully-automated, hippocampal volumetry, magnetic resonance imaging, model-based segmentation, prediction

DOI: 10.3233/JAD-150804

Journal: Journal of Alzheimer's Disease, vol. 51, no. 3, pp. 867-873, 2016