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{
"name": "Van Gils, M.",
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{
"name": "Soininen, H.",
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{
"name": "Lötjönen, J.",
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{
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],
"titles": [
{
"title": "Supplementary Material for: Automatic MRI Quantifying Methods in Behavioral-Variant Frontotemporal Dementia Diagnosis"
}
],
"publisher": {
"name": "Karger Publishers"
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"subjects": [
{
"subject": "Medicine"
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],
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"dates": [
{
"date": "2018-02-23",
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{
"date": "2018-02-23",
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"date": "2018",
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"description": "Aims: We assessed the value of automated MRI quantification methods in the differential diagnosis of behavioral-variant frontotemporal dementia (bvFTD) from Alzheimer disease (AD), Lewy body dementia (LBD), and subjective memory complaints (SMC). We also examined the role of the C9ORF72-related genetic status in the differentiation sensitivity. Methods: The MRI scans of 50 patients with bvFTD (17 C9ORF72 expansion carriers) were analyzed using 6 quantification methods as follows: voxel-based morphometry (VBM), tensor-based morphometry, volumetry (VOL), manifold learning, grading, and white-matter hyperintensities. Each patient was then individually compared to an independent reference group in order to attain diagnostic suggestions. Results: Only VBM and VOL showed utility in correctly identifying bvFTD from our set of data. The overall classification sensitivity of bvFTD with VOL + VBM achieved a total sensitivity of 60%. Using VOL + VBM, 32% were misclassified as having LBD. There was a trend of higher values for classification sensitivity of the C9ORF72 expansion carriers than noncarriers. Conclusion: VOL, VBM, and their combination are effective in differential diagnostics between bvFTD and AD or SMC. However, MRI atrophy profiles for bvFTD and LBD are too similar for a reliable differentiation with the quantification methods tested in this study.",
"descriptionType": "Abstract"
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