Literature DB >> 18513834

Diffusion tensor imaging of deep gray matter brain structures: effects of age and iron concentration.

Adolf Pfefferbaum1, Elfar Adalsteinsson, Torsten Rohlfing, Edith V Sullivan.   

Abstract

Diffusion tensor imaging (DTI) of the brain has become a mainstay in the study of normal aging of white matter, and only recently has attention turned to the use of DTI to examine aging effects in gray matter structures. Of the many changes in the brain that occur with advancing age is increased presence of iron, notable in selective deep gray matter structures. In vivo detection and measurement of iron deposition is possible with magnetic resonance imaging (MRI) because of iron's effect on signal intensity. In the process of a DTI study, a series of diffusion-weighted images (DWI) is collected, and while not normally considered as a major dependent variable in research studies, they are used clinically and they reveal striking conspicuity of the globus pallidus and putamen caused by signal loss in these structures, presumably due to iron accumulation with age. These iron deposits may in turn influence DTI metrics, especially of deep gray matter structures. The combined imaging modality approach has not been previously used in the study of normal aging. The present study used legacy DTI data collected in 10 younger (22-37 years) and 10 older (65-79 years) men and women at 3.0T and fast spin-echo (FSE) data collected at 1.5T and 3.0T to derive an estimate of the field-dependent relaxation rate increase (the "FDRI estimate") in the putamen, caudate nucleus, globus pallidus, thalamus, and a frontal white matter sample comparison region. The effect of age on the diffusion measures in the deep gray matter structures was distinctly different from that reported in white matter. In contrast to lower anisotropy and higher diffusivity typical in white matter of older relative to younger adults observed with DTI, both anisotropy and diffusivity were higher in the older than younger group in the caudate nucleus and putamen; the thalamus showed little effect of age on anisotropy or diffusivity. Signal intensity measured with DWI was lower in the putamen of elderly than young adults, whereas the opposite was observed for the white matter region and thalamus. As a retrospective study based on legacy data, the FDRI estimates were based on FSE sequences, which underestimated the classical FDRI index of brain iron. Nonetheless, the differential effects of age on DTI metrics in subcortical gray matter structures compared with white matter tracts appears to be related, at least in part, to local iron content, which in the elderly of the present study was prominent in the FDRI estimate of the putamen and visibly striking in the diffusion-weighted image of the basal ganglia structures. Copyright 2008 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18513834      PMCID: PMC2815127          DOI: 10.1016/j.neurobiolaging.2008.04.013

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


  72 in total

Review 1.  Imaging iron stores in the brain using magnetic resonance imaging.

Authors:  E Mark Haacke; Norman Y C Cheng; Michael J House; Qiang Liu; Jaladhar Neelavalli; Robert J Ogg; Asadullah Khan; Muhammad Ayaz; Wolff Kirsch; Andre Obenaus
Journal:  Magn Reson Imaging       Date:  2005-01       Impact factor: 2.546

2.  Voxel based versus region of interest analysis in diffusion tensor imaging of neurodevelopment.

Authors:  Lindsay Snook; Chris Plewes; Christian Beaulieu
Journal:  Neuroimage       Date:  2006-10-27       Impact factor: 6.556

3.  A simplified method to measure the diffusion tensor from seven MR images.

Authors:  P J Basser; C Pierpaoli
Journal:  Magn Reson Med       Date:  1998-06       Impact factor: 4.668

4.  Method for image-based measurement of the reversible and irreversible contribution to the transverse-relaxation rate.

Authors:  J Ma; F W Wehrli
Journal:  J Magn Reson B       Date:  1996-04

5.  Diffusion-weighted MR imaging of anisotropic water diffusion in cat central nervous system.

Authors:  M E Moseley; Y Cohen; J Kucharczyk; J Mintorovitch; H S Asgari; M F Wendland; J Tsuruda; D Norman
Journal:  Radiology       Date:  1990-08       Impact factor: 11.105

6.  Assessment of relative brain iron concentrations using T2-weighted and T2*-weighted MRI at 3 Tesla.

Authors:  R J Ordidge; J M Gorell; J C Deniau; R A Knight; J A Helpern
Journal:  Magn Reson Med       Date:  1994-09       Impact factor: 4.668

7.  Health and infarcted brain tissues studied at short diffusion times: the origins of apparent restriction and the reduction in apparent diffusion coefficient.

Authors:  D G Norris; T Niendorf; D Leibfritz
Journal:  NMR Biomed       Date:  1994-11       Impact factor: 4.044

8.  Differential vulnerability of anterior white matter in nondemented aging with minimal acceleration in dementia of the Alzheimer type: evidence from diffusion tensor imaging.

Authors:  Denise Head; Randy L Buckner; Joshua S Shimony; Laura E Williams; Erbil Akbudak; Thomas E Conturo; Mark McAvoy; John C Morris; Abraham Z Snyder
Journal:  Cereb Cortex       Date:  2004-04       Impact factor: 5.357

9.  Diffusion tensor trace mapping in normal adult brain using single-shot EPI technique. A methodological study of the aging brain.

Authors:  Z G Chen; T Q Li; T Hindmarsh
Journal:  Acta Radiol       Date:  2001-09       Impact factor: 1.701

Review 10.  Clinical review: Imaging in ischaemic stroke--implications for acute management.

Authors:  Ramez Reda Moustafa; Jean-Claude Baron
Journal:  Crit Care       Date:  2007       Impact factor: 9.097

View more
  83 in total

1.  Combining atlas-based parcellation of regional brain data acquired across scanners at 1.5 T and 3.0 T field strengths.

Authors:  Adolf Pfefferbaum; Torsten Rohlfing; Margaret J Rosenbloom; Edith V Sullivan
Journal:  Neuroimage       Date:  2012-01-26       Impact factor: 6.556

2.  Simple linear regression model is misleading when used to analyze quantitative diffusion tensor imaging data that include young and old adults.

Authors:  K M Hasan
Journal:  AJNR Am J Neuroradiol       Date:  2010-06-10       Impact factor: 3.825

3.  Diffusion tensor-based regional gray matter tissue segmentation using the international consortium for brain mapping atlases.

Authors:  Khader M Hasan; Richard E Frye
Journal:  Hum Brain Mapp       Date:  2011-01       Impact factor: 5.038

4.  Rapid generation of biexponential and diffusional kurtosis maps using multi-layer perceptrons: a preliminary experience.

Authors:  Ludovico Minati
Journal:  MAGMA       Date:  2008-07-29       Impact factor: 2.310

5.  Volume and iron content in basal ganglia and thalamus.

Authors:  Patrice Péran; Andrea Cherubini; Giacomo Luccichenti; Gisela Hagberg; Jean-François Démonet; Olivier Rascol; Pierre Celsis; Carlo Caltagirone; Gianfranco Spalletta; Umberto Sabatini
Journal:  Hum Brain Mapp       Date:  2009-08       Impact factor: 5.038

6.  Gray matter alterations in early aging: a diffusion magnetic resonance imaging study.

Authors:  Y Rathi; O Pasternak; P Savadjiev; O Michailovich; S Bouix; M Kubicki; C-F Westin; N Makris; M E Shenton
Journal:  Hum Brain Mapp       Date:  2013-12-31       Impact factor: 5.038

7.  Brain white matter structural properties predict transition to chronic pain.

Authors:  Ali R Mansour; Marwan N Baliki; Lejian Huang; Souraya Torbey; Kristi M Herrmann; Thomas J Schnitzer; A Vania Apkarian
Journal:  Pain       Date:  2013-10       Impact factor: 6.961

8.  The SRI24 multichannel atlas of normal adult human brain structure.

Authors:  Torsten Rohlfing; Natalie M Zahr; Edith V Sullivan; Adolf Pfefferbaum
Journal:  Hum Brain Mapp       Date:  2010-05       Impact factor: 5.038

9.  Compensatory role of the cortico-rubro-spinal tract in motor recovery after stroke.

Authors:  Theodor Rüber; Gottfried Schlaug; Robert Lindenberg
Journal:  Neurology       Date:  2012-07-25       Impact factor: 9.910

10.  MRI estimates of brain iron concentration in normal aging: comparison of field-dependent (FDRI) and phase (SWI) methods.

Authors:  Adolf Pfefferbaum; Elfar Adalsteinsson; Torsten Rohlfing; Edith V Sullivan
Journal:  Neuroimage       Date:  2009-05-12       Impact factor: 6.556

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.