MRI signatures of brain macrostructural atrophy and microstructural degradation in frontotemporal lobar degeneration

Yu Zhang1, Maria Carmela Tartaglia, Norbert Schuff

  • 1Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA 94121, USA. Yu.Zhang@ucsf.edu

Insights

Diffusion tensor imaging (DTI) shows distinct white matter damage patterns in frontotemporal lobar degeneration (FTLD) subtypes. DTI, especially radial diffusivity, offers superior classification accuracy for FTLD compared to brain atrophy measurements.

Area of Science:

  • Neuroimaging
  • Neurology
  • Biomedical Engineering

Background:

  • Frontotemporal lobar degeneration (FTLD) encompasses subtypes like bvFTD, SD, and PNFA, each with distinct brain atrophy and white matter alterations.
  • Previous MRI studies have identified regional patterns of macrostructural atrophy and white matter microstructural changes in FTLD subtypes.

Purpose of the Study:

  • To investigate the correlation between white matter microstructural alterations and brain atrophy patterns in FTLD subtypes.
  • To compare the efficacy of various diffusion tensor imaging (DTI) indices in characterizing FTLD patients.
  • To determine if DTI measures offer superior classification power for FTLD compared to brain atrophy.

Main Methods:

  • Structural MRI and DTI scans were performed on 25 FTLD patients (13 bvFTD, 6 SD, 6 PNFA) and 19 healthy controls.
  • Voxel-based morphometry analyzed regional brain atrophy from T1-weighted MRI data.
  • Voxelwise and region-of-interest analyses of DTI indices (fractional anisotropy, axial diffusivity, radial diffusivity) assessed white matter degradation.

Main Results:

  • All FTLD subtypes exhibited characteristic regional patterns of brain atrophy and white matter damage compared to controls.
  • DTI measures provided significantly higher accuracy in classifying FTLD patients than brain atrophy measurements.
  • Radial diffusivity demonstrated greater sensitivity in detecting white matter damage in FTLD than other DTI indices.

Conclusions:

  • DTI is a more powerful tool for classifying FTLD patients from healthy controls than traditional brain atrophy measurements.
  • Radial diffusivity is particularly effective in assessing white matter microstructural damage in FTLD.
  • These findings support the use of DTI in the diagnostic evaluation of FTLD subtypes.

Related Concept Videos

Dementia l: Introduction01:22

Dementia l: Introduction

Dementia is an acquired, progressive syndrome characterized by a decline in multiple cognitive domains severe enough to impair daily functioning and reduce independence. Although memory loss is a central feature, the diagnosis requires additional deficits involving language, executive function, visuospatial skills, judgment, calculation, or abstract reasoning. These cognitive impairments reflect underlying neurodegenerative or vascular processes that gradually disrupt neuronal networks...
Alzheimer Disease ll: Pathophysiology01:23

Alzheimer Disease ll: Pathophysiology

Alzheimer disease involves structural changes in the brain that begin long before symptoms appear. The most distinctive features are extracellular neuritic plaques and intracellular neurofibrillary tangles.Neuritic plaques form in the cerebral cortex and around blood vessels. These plaques contain a dense core of beta-amyloid (Aβ)—a toxic protein fragment that clumps outside neurons. The core is surrounded by damaged neuronal extensions, as well as reactive astrocytes and microglia. Abnormal...
Alzheimer Disease l: Introduction01:29

Alzheimer Disease l: Introduction

Alzheimer disease is a chronic, progressive, and irreversible neurodegenerative disorder and the most common cause of dementia in older adults. It leads to gradual neuronal loss, causing cognitive decline, behavioral changes, and loss of functional independence.Risk Factors and EtiologyThe disease is multifactorial. Age is the strongest risk factor, with prevalence doubling every 5 years after age 65. Genetic factors include mutations in genes such as APP, PSEN1, and PSEN2, which are associated...