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Tissue Border Enhancement by inversion recovery MRI at 7.0 Tesla.
Neuroradiology ; 56(7): 517-23, 2014 Jul.
Article en En | MEDLINE | ID: mdl-24763967
ABSTRACT

INTRODUCTION:

This contribution presents a magnetic resonance imaging (MRI) acquisition technique named Tissue Border Enhancement (TBE), whose purpose is to produce images with enhanced visualization of borders between two tissues of interest without any post-processing.

METHODS:

The technique is based on an inversion recovery sequence that employs an appropriate inversion time to produce images where the interface between two tissues of interest is hypo-intense; therefore, tissue borders are clearly represented by dark lines. This effect is achieved by setting imaging parameters such that two neighboring tissues of interest have magnetization with equal magnitude but opposite sign; therefore, the voxels containing a mixture of each tissue (that is, the tissue interface) possess minimal net signal. The technique was implemented on a 7.0 T MRI system.

RESULTS:

This approach can assist the definition of tissue borders, such as that between cortical gray matter and white matter; therefore, it could facilitate segmentation procedures, which are often challenging on ultra-high-field systems due to inhomogeneous radiofrequency distribution. TBE allows delineating the contours of structural abnormalities, and its capabilities were demonstrated with patients with focal cortical dysplasia, gray matter heterotopia, and polymicrogyria.

CONCLUSION:

This technique provides a new type of image contrast and has several possible applications in basic neuroscience, neurogenetic research, and clinical practice, as it could improve the detection power of MRI in the characterization of cortical malformations, enhance the contour of small anatomical structures of interest, and facilitate cortical segmentation.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Encéfalo / Encefalopatías / Imagen por Resonancia Magnética / Interpretación de Imagen Asistida por Computador / Aumento de la Imagen Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: Neuroradiology Año: 2014 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Encéfalo / Encefalopatías / Imagen por Resonancia Magnética / Interpretación de Imagen Asistida por Computador / Aumento de la Imagen Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: Neuroradiology Año: 2014 Tipo del documento: Article