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Automatic MRI Quantifying Methods in Behavioral-Variant Frontotemporal Dementia Diagnosis.

Antti Cajanus1,2, Anette Hall1, Juha Koikkalainen3

  • 1Institute of Clinical Medicine - Neurology, University of Eastern Finland, Kuopio, Finland.

Dementia and Geriatric Cognitive Disorders Extra
|April 3, 2018
PubMed
Summary
This summary is machine-generated.

Automated MRI quantification using volumetry (VOL) and voxel-based morphometry (VBM) aids in diagnosing behavioral-variant frontotemporal dementia (bvFTD) but struggles to differentiate it from Lewy body dementia (LBD). The C9orf72 genetic status showed a trend toward improved classification sensitivity.

Keywords:
DementiaFrontotemporal dementiaFrontotemporal lobar degenerationMRIMachine learningNeuroimaging

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Area of Science:

  • Neuroimaging
  • Neurology
  • Genetics

Background:

  • Behavioral-variant frontotemporal dementia (bvFTD) diagnosis is challenging.
  • Differentiating bvFTD from Alzheimer disease (AD), Lewy body dementia (LBD), and subjective memory complaints (SMC) is crucial.
  • The role of genetic factors, such as C9ORF72, in bvFTD presentation requires further investigation.

Purpose of the Study:

  • To evaluate automated MRI quantification methods for distinguishing bvFTD from AD, LBD, and SMC.
  • To assess the influence of C9ORF72 genetic status on diagnostic accuracy.

Main Methods:

  • Fifty bvFTD patients (17 C9ORF72 carriers) underwent MRI.
  • Six quantification methods were applied: VBM, tensor-based morphometry, VOL, manifold learning, grading, and white-matter hyperintensities.
  • Individual patient data were compared to a reference group for diagnostic suggestions.

Main Results:

  • Voxel-based morphometry (VBM) and volumetry (VOL) demonstrated utility in identifying bvFTD.
  • The combination of VOL + VBM achieved 60% sensitivity for bvFTD classification.
  • 32% of bvFTD cases were misclassified as LBD using VOL + VBM.
  • A trend suggested higher classification sensitivity in C9ORF72 expansion carriers.

Conclusions:

  • VOL, VBM, and their combination effectively differentiate bvFTD from AD and SMC.
  • Current MRI quantification methods struggle to reliably distinguish bvFTD from LBD due to similar atrophy patterns.
  • Further research is needed to refine MRI techniques for bvFTD and LBD differentiation.