Brain morphometry: Difference between revisions

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==Methodologies==
==Methodologies==
Technically, several approaches exist for neuroimaging-based brain morphometric analyses: [[Voxel-based morphometry]], [[deformation-based morphometry]], [[surface-based morphometry]] and [[tract-based morphometry]]. All four are usually performed based on [[Magnetic resonance imaging]] data, the former three using T1-weighted [[pulse sequence (NMR)|pulse sequences]], the latter diffusion-weighted ones.
Technically, several approaches exist for neuroimaging-based brain morphometric analyses: [[Voxel-based morphometry]], [[deformation-based morphometry]], [[surface-based morphometry]] and [[tract-based morphometry]]. All four are usually performed based on [[Magnetic resonance imaging|Magnetic Resonance Imaging]] data, the former three using T1-weighted [[pulse sequence (NMR)|pulse sequences]], the latter diffusion-weighted ones.


==Applications==
==Applications==
Currently, most applications of brain morphometry have a clinical focus, i.e. they serve to diagnose and monitor neuropsychiatric disorders, in particular [[neurodevelopmental disorder]]s (like [[schizophrenia]]) or [[neurodegenerative disease]]s (like [[Alzheimer's disease|Alzheimer]]), but brain [[brain development|development]] and [[brain aging|aging]] as well as [[brain evolution]] can also be studied this way.
Currently, most applications of brain morphometry have a clinical focus, i.e. they serve to diagnose and monitor neuropsychiatric disorders, in particular [[neurodevelopmental disorder]]s (like [[schizophrenia]]) or [[neurodegenerative disease]]s (like [[Alzheimer's disease|Alzheimer]]), but brain [[brain development|development]] and [[brain aging|aging]] as well as [[brain evolution]] can also be studied this way.

Revision as of 06:57, 23 January 2009

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As a subfield of morphometry, brain morphometry is concerned with the quantification of anatomical patterns in the brain. These include whole-brain parameters like brain mass or brain volume, encephalization quotient, the distribution of grey matter and white matter as well as cerebrospinal fluid but also derived parameters like gyrification and cortical thickness or quantitative aspects of substructures of the brain, e.g. the volume of the hippocampus, or the amount of neurons in the optic tectum. Though the extraction of some morphometric parameters like brain mass or liquor volume may be relatively straightforward in post mortem samples, studies in living subjects normally use an indirect approach: First, a spatial representation of the brain or its components is obtained by some appropriate neuroimaging technique, and from such datasets, the parameters of interest can then be extracted.

Methodologies

Technically, several approaches exist for neuroimaging-based brain morphometric analyses: Voxel-based morphometry, deformation-based morphometry, surface-based morphometry and tract-based morphometry. All four are usually performed based on Magnetic Resonance Imaging data, the former three using T1-weighted pulse sequences, the latter diffusion-weighted ones.

Applications

Currently, most applications of brain morphometry have a clinical focus, i.e. they serve to diagnose and monitor neuropsychiatric disorders, in particular neurodevelopmental disorders (like schizophrenia) or neurodegenerative diseases (like Alzheimer), but brain development and aging as well as brain evolution can also be studied this way.