Automatic MRI Quantifying Methods in Behavioral-Variant Frontotemporal Dementia Diagnosis

Research output: Contribution to journalJournal articleResearchpeer-review

  • Antti Cajanus
  • Anette Hall
  • Juha Koikkalainen
  • Eino Solje
  • Antti Tolonen
  • Timo Urhemaa
  • Yawu Liu
  • Ramona M Haanpää
  • Päivi Hartikainen
  • Seppo Helisalmi
  • Ville Korhonen
  • Daniel Rueckert
  • Hasselbalch, Steen
  • Waldemar, Gunhild
  • Patrizia Mecocci
  • Ritva Vanninen
  • Mark van Gils
  • Hilkka Soininen
  • Jyrki Lötjönen
  • Anne M Remes

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.

Original languageEnglish
JournalDementia and Geriatric Cognitive Disorders Extra
Volume8
Issue number1
Pages (from-to)51-59
Number of pages9
ISSN1664-5464
DOIs
Publication statusPublished - 2018

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