Literature DB >> 14527311

Temporal dynamics of brain anatomy.

Arthur W Toga1, Paul M Thompson.   

Abstract

The brain changes profoundly in structure and function during development and as a result of diseases such as the dementias, schizophrenia, multiple sclerosis, and tumor growth. Strategies to measure, map, and visualize these brain changes are of immense value in basic and clinical neuroscience. Algorithms that map brain change with sufficient spatial and temporal sensitivity can also assess drugs that aim to decelerate or arrest these changes. In neuroscience studies, these tools can reveal subtle brain changes in adolescence and old age and link these changes with measurable differences in brain function and cognition. Early detection of brain change in patients at risk for dementia; tumor recurrence; or relapsing-remitting conditions, such as multiple sclerosis, is also vital for optimizing therapy. We review a variety of mathematical and computational approaches to detect structural brain change with unprecedented sensitivity, both spatially and temporally. The resulting four-dimensional (4-D) maps of brain anatomy are warehoused in population-based brain atlases. Here, statistical tools compare brain changes across subjects and across populations, adjusting for complex differences in brain structure. Brain changes in an individual can be compared with a normative database comprised of subjects matched for age, gender, and other demographic factors. These dynamic brain maps offer key biological markers for understanding disease progression and testing therapeutic response. The early detection of disease-related brain changes is also critical for possible pre-emptive intervention before the ravages of disease have set in.

Entities:  

Mesh:

Year:  2003        PMID: 14527311     DOI: 10.1146/annurev.bioeng.5.040202.121611

Source DB:  PubMed          Journal:  Annu Rev Biomed Eng        ISSN: 1523-9829            Impact factor:   9.590


  20 in total

1.  Discriminant analysis of longitudinal cortical thickness changes in Alzheimer's disease using dynamic and network features.

Authors:  Yang Li; Yaping Wang; Guorong Wu; Feng Shi; Luping Zhou; Weili Lin; Dinggang Shen
Journal:  Neurobiol Aging       Date:  2011-01-26       Impact factor: 4.673

2.  Direct cortical mapping via solving partial differential equations on implicit surfaces.

Authors:  Yonggang Shi; Paul M Thompson; Ivo Dinov; Stanley Osher; Arthur W Toga
Journal:  Med Image Anal       Date:  2007-02-16       Impact factor: 8.545

3.  Registration of longitudinal image sequences with implicit template and spatial-temporal heuristics.

Authors:  Guorong Wu; Qian Wang; Hongjun Jia; Dinggang Shen
Journal:  Med Image Comput Comput Assist Interv       Date:  2010

4.  Evaluation of automated brain MR image segmentation and volumetry methods.

Authors:  Frederick Klauschen; Aaron Goldman; Vincent Barra; Andreas Meyer-Lindenberg; Arvid Lundervold
Journal:  Hum Brain Mapp       Date:  2009-04       Impact factor: 5.038

Review 5.  Transitions into underage and problem drinking: developmental processes and mechanisms between 10 and 15 years of age.

Authors:  Michael Windle; Linda P Spear; Andrew J Fuligni; Adrian Angold; Jane D Brown; Daniel Pine; Greg T Smith; Jay Giedd; Ronald E Dahl
Journal:  Pediatrics       Date:  2008-04       Impact factor: 7.124

6.  Registration of longitudinal brain image sequences with implicit template and spatial-temporal heuristics.

Authors:  Guorong Wu; Qian Wang; Dinggang Shen
Journal:  Neuroimage       Date:  2011-07-23       Impact factor: 6.556

Review 7.  Mapping fetal brain development in utero using magnetic resonance imaging: the Big Bang of brain mapping.

Authors:  Colin Studholme
Journal:  Annu Rev Biomed Eng       Date:  2011-08-15       Impact factor: 9.590

8.  Spatiotemporal mapping of brain atrophy in mouse models of Huntington's disease using longitudinal in vivo magnetic resonance imaging.

Authors:  Manisha Aggarwal; Wenzhen Duan; Zhipeng Hou; Neal Rakesh; Qi Peng; Christopher A Ross; Michael I Miller; Susumu Mori; Jiangyang Zhang
Journal:  Neuroimage       Date:  2012-02-09       Impact factor: 6.556

9.  In vivo high-resolution diffusion tensor imaging of the mouse brain.

Authors:  Dan Wu; Jiadi Xu; Michael T McMahon; Peter C M van Zijl; Susumu Mori; Frances J Northington; Jiangyang Zhang
Journal:  Neuroimage       Date:  2013-06-12       Impact factor: 6.556

10.  Computational morphometry for detecting changes in brain structure due to development, aging, learning, disease and evolution.

Authors:  Daniel Mietchen; Christian Gaser
Journal:  Front Neuroinform       Date:  2009-08-11       Impact factor: 4.081

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