Texture analysis of vertebral bone marrow using chemical shift encoding–based water-fat MRI: a feasibility study

Autor: Muthu Rama Krishnan Mookiah, Thomas Baum, Stefan Ruschke, Dennis M. Hedderich, Michael Dieckmeyer, Claus Zimmer, Alexander Rohrmeier, Karupppasamy Subburaj, Ernst J. Rummeny, Egon Burian, Dimitrios C. Karampinos, Maximilian N. Diefenbach, J. S. Kirschke
Rok vydání: 2019
Předmět:
Zdroj: Osteoporosis International
BASE-Bielefeld Academic Search Engine
ISSN: 1433-2965
0937-941X
DOI: 10.1007/s00198-019-04924-9
Popis: Summary This feasibility study investigated the spatial heterogeneity of the lumbar vertebral bone marrow using chemical shift encoding–based water-fat MRI. Acquired texture features like contrast and dissimilarity allowed for differentiation of pre- and postmenopausal women and may serve as imaging biomarkers in the future. Introduction While the vertebral bone marrow fat using chemical shift encoding water-fat magnetic resonance imaging (MRI) has been extensively studied, its spatial heterogeneity has not been analyzed yet. Therefore, this feasibility study investigated the spatial heterogeneity of the lumbar vertebral bone marrow by using texture analysis in proton density fat fraction (PDFF) maps. Methods Forty-one healthy pre- and postmenopausal women were recruited for this study (premenopausal (n = 15) 30 ± 7 years, postmenopausal (n = 26) 65 ± 7 years). An eight-echo 3D spoiled gradient echo sequence was used for chemical shift encoding–based water-fat separation at the lumbar spine. Vertebral bodies L1 to L5 were manually segmented. Mean PDFF values and texture features were extracted at each vertebral level, namely variance, skewness, and kurtosis, using statistical moments and second-order features (energy, contrast, correlation, homogeneity, dissimilarity, entropy, variance, and sum average). Parameters were compared between pre- and postmenopausal women and vertebral levels. Results PDFF was significantly higher in post- than in premenopausal women (49.37 ± 8.14% versus 27.76 ± 7.30%, p
Databáze: OpenAIRE