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Article type: Research Article
Authors: Muñoz-Ruiz, Miguel Ángela | Hartikainen, Päivia; b | Hall, Anettea | Mattila, Jussid | Koikkalainen, Juhad | Herukka, Sanna-Kaisaa; b | Julkunen, Valtteria | Vanninen, Ritvac | Liu, Yawua; c | Lötjönen, Jyrkid | Soininen, Hilkkaa; b; *
Affiliations: [a] Institute of Clinical Medicine, Neurology, University of Eastern Finland, Kuopio, Finland | [b] Department of Neurology, Kuopio University Hospital, Kuopio, Finland | [c] Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland | [d] VTT Technical Research Centre of Finland, Tampere, Finland
Correspondence: [*] Correspondence to: Hilkka Soininen, MD, PhD, Department of Neurology and Neuroscience, University of Eastern Finland, Kuopio University Hospital, Kuopio, Finland. E-mail: [email protected].
Abstract: Background:Disease State Index and Disease State Fingerprint represent a novel tool which collates data information from different sources, helping the clinician in the diagnosis and follow-up of dementia diseases. It has been demonstrated that it is applicable in the diagnosis of Alzheimer’s disease (AD). Objective:We applied this novel tool to classify frontotemporal dementia (FTD) cases in comparison with controls, AD, and mild cognitive impairment (MCI) subjects. Methods:Thirty seven patients with FTD, 35 patients with AD, 26 control subjects, and 64 subjects with MCI were included in the study. The Disease State Index encompassed data from cognitive performance assessed by Mini-Mental State Examination, cerebrospinal fluid biomarkers, MRI volumetric and morphometric parameters as well as APOE genotype. Results:We applied the Disease State Index for comparisons at the group level. The data showed that FTD patients could be differentiated with a high accuracy, sensitivity, and specificity from controls (0.84, 0.84, 0.83) and from MCI (0.79, 0.78, 0.80). However, the correct accuracy was lower in the FTD versus AD comparison (0.69, 0.70, 0.71). In addition, we demonstrated the use of Disease State Fingerprint by comparing one particular FTD case with control, AD, and MCI population data. Conclusion:The results suggest that the Disease State Fingerprint and the underlying Disease State Index are particularly useful in differentiating between normal status and disease in patients with dementia, but it may also help to distinguish between the two dementia diseases, FTD and AD.
Keywords: Alzheimer's disease, cognition, frontotemporal dementia, memory, mild cognitive impairment
DOI: 10.3233/JAD-122260
Journal: Journal of Alzheimer's Disease, vol. 35, no. 4, pp. 727-739, 2013
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