Detecting frontotemporal dementia syndromes using MRI biomarkers

Marie Bruun(University of Copenhagen), Juha Koikkalainen, Hanneke Rhodius‐Meester(Amsterdam Neuroscience), Marta Baroni(University of Perugia), Le Gjerum(University of Copenhagen), Mark van Gils(VTT Technical Research Centre of Finland), Hilkka Soininen(University of Eastern Finland), Anne M. Remes(Oulu University Hospital), Päivi Hartikainen(Kuopio University Hospital), Gunhild Waldemar(University of Copenhagen), Patrizia Mecocci(University of Perugia), Frederik Barkhof(Amsterdam Neuroscience), Yolande A.L. Pijnenburg(Amsterdam Neuroscience), Wiesje M. van der Flier(Amsterdam Neuroscience), Steen Gregers Hasselbalch(University of Copenhagen), Jyrki Lötjönen, Kristian Steen Frederiksen(University of Copenhagen)
NeuroImage Clinical
January 1, 2019
Cited by 77Open Access
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Abstract

BACKGROUND: Diagnosing frontotemporal dementia may be challenging. New methods for analysis of regional brain atrophy patterns on magnetic resonance imaging (MRI) could add to the diagnostic assessment. Therefore, we aimed to develop automated imaging biomarkers for differentiating frontotemporal dementia subtypes from other diagnostic groups, and from one another. METHODS: In this retrospective multicenter cohort study, we included 1213 patients (age 67 ± 9, 48% females) from two memory clinic cohorts: 116 frontotemporal dementia, 341 Alzheimer's disease, 66 Dementia with Lewy bodies, 40 vascular dementia, 104 other dementias, 229 mild cognitive impairment, and 317 subjective cognitive decline. Three MRI atrophy biomarkers were derived from the normalized volumes of automatically segmented cortical regions: 1) the anterior vs. posterior index, 2) the asymmetry index, and 3) the temporal pole left index. We used the following performance metrics: area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. To account for the low prevalence of frontotemporal dementia we pursued a high specificity of 95%. Cross-validation was used in assessing the performance. The generalizability was assessed in an independent cohort (n = 200). RESULTS: The anterior vs. posterior index performed with an AUC of 83% for differentiation of frontotemporal dementia from all other diagnostic groups (Sensitivity = 59%, Specificity = 95%, positive likelihood ratio = 11.8, negative likelihood ratio = 0.4). The asymmetry index showed highest performance for separation of primary progressive aphasia and behavioral variant frontotemporal dementia (AUC = 85%, Sensitivity = 79%, Specificity = 92%, positive likelihood ratio = 9.9, negative likelihood ratio = 0.2), whereas the temporal pole left index was specific for detection of semantic variant primary progressive aphasia (AUC = 85%, Sensitivity = 82%, Specificity = 80%, positive likelihood ratio = 4.1, negative likelihood ratio = 0.2). The validation cohort provided corresponding results for the anterior vs. posterior index and temporal pole left index. CONCLUSION: This study presents three quantitative MRI biomarkers, which could provide additional information to the diagnostic assessment and assist clinicians in diagnosing frontotemporal dementia.


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