Bone marrow segmentation based on a combined consideration of transverse relaxation processes and Dixon oscillations.
NMR Biomed
; 29(5): 553-62, 2016 May.
Article
em En
| MEDLINE
| ID: mdl-26866627
ABSTRACT
The aim of this study was to demonstrate that gradient-echo sampling of single spin echoes can be used to isolate the signal from trabecular bone marrow, with high-quality segmentation and surface reconstructions resulting from the application of simple post-processing strategies. Theoretical expressions of the time-domain single-spin-echo signal were used to simulate signals from bone marrow, non-bone fatty deposits and muscle. These simulations were compared with and used to interpret signals obtained by the application of the gradient-echo sampling of a spin-echo sequence to image the knee and surrounding tissues at 1.5 T. Trabecular bone marrow has a much higher reversible transverse relaxation rate than surrounding non-bone fatty deposits and other musculoskeletal tissues. This observation, combined with a choice of gradient-echo spacing that accentuates Dixon-type oscillations from chemical-shift interference effects, enabled the isolation of bone marrow signal from surrounding tissues through the use of simple image subtraction and thresholding. Three-dimensional renderings of the marrow surface were then readily generated with this approach - renderings that may prove useful for bone morphology assessment, e.g. for the measurement of femoral anteversion. In conclusion, understanding the behavior of signals from bone marrow and surrounding tissue as a function of time through a spin echo facilitates the segmentation and reconstruction of bone marrow surfaces using straightforward post-processing strategies that are typically available on modern radiology workstations.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Medula Óssea
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Processamento de Imagem Assistida por Computador
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Imageamento por Ressonância Magnética
Tipo de estudo:
Prognostic_studies
Limite:
Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article