High-Resolution MR Imaging of the Human Brainstem In vivo at 7 Tesla.

Abstract:

:The human brainstem, which comprises a multitude of axonal nerve fibers and nuclei, plays an important functional role in the human brain. Depicting its anatomy non-invasively with high spatial resolution may thus in turn help to better relate normal and pathological anatomical variations to medical conditions as well as neurological and peripheral functions. We explored the potential of high-resolution magnetic resonance imaging (MRI) at 7 T for depicting the intricate anatomy of the human brainstem in vivo by acquiring and generating images with multiple contrasts: T 2-weighted images, quantitative maps of longitudinal relaxation rate (R 1 maps) and effective transverse relaxation rate ([Formula: see text] maps), magnetic susceptibility maps, and direction-encoded track-density images. Images and quantitative maps were compared with histological stains and anatomical atlases to identify nerve nuclei and nerve fibers. Among the investigated contrasts, susceptibility maps displayed the largest number of brainstem structures. Contrary to R 1 maps and T 2-weighted images, which showed rather homogeneous contrast, [Formula: see text] maps, magnetic susceptibility maps, and track-density images clearly displayed a multitude of smaller and larger fiber bundles. Several brainstem nuclei were identifiable in sections covering the pons and medulla oblongata, including the spinal trigeminal nucleus and the reticulotegmental nucleus on magnetic susceptibility maps as well as the inferior olive on R 1, [Formula: see text], and susceptibility maps. The substantia nigra and red nuclei were visible in all contrasts. In conclusion, high-resolution, multi-contrast MR imaging at 7 T is a versatile tool to non-invasively assess the individual anatomy and tissue composition of the human brainstem.

journal_name

Front Hum Neurosci

authors

Deistung A,Schäfer A,Schweser F,Biedermann U,Güllmar D,Trampel R,Turner R,Reichenbach JR

doi

10.3389/fnhum.2013.00710

subject

Has Abstract

pub_date

2013-10-29 00:00:00

pages

710

issn

1662-5161

journal_volume

7

pub_type

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