Application of CT energy spectrum imaging in the determination of bone marrow fat content in auxiliary diagnosis of osteoporosis

doi:10.3877/cma.j.issn.2095-8757.2020.01.007

Abstract

Abstract:

Objective

To compare the measurement of bone marrow fat content by energy spectrum CT imaging and MRI IDEAL-IQ sequence technology, and to explore the application of energy spectrum CT imaging in the auxiliary diagnosis of osteoporosis.

Methods

GSI scan and IDEAL-IQ scan were performed on the spine of 8-year-old female goats. The content of fat-hydroxyapatite (fat-HAP) in the cancellous bone of the vertebral body was measured by CT energy spectrum imaging, and the fat fraction of the cancellous bone of the vertebral body was measured by magnetic resonance IDEAL-IQ technology. The number of adipose cells in cancellous bone was calculated at high magnification. The correlation among fat HAP content, fat fraction and the number of adipocyte were analyzed by Pearson correlation analysis.

Results

The content of fat-HAP was 951.10~984.78 (967.45±9.84), the value of fat fraction was 0.35~0.55 (0.45±0.05), and the number of adipocyte was 13~30.33 (21.38±4.30). The results of correlation analysis showed that the content of fat-Hap and the fat fraction were significantly correlated with the number of adipocyte (r=0.560、0.580, P < 0.05), but there was no significant correlation between fat-HAP and fat fraction (r=0.300, P > 0.05).

Conclusion

The content of fat HAP based substance pair detected by CT energy spectrum imaging can reflect the number of fat cells in the vertebral body to a certain extent, and indirectly reflect the degree of osteoporosis, which may be used in clinical as a new imaging diagnosis idea.

Key words: Tomography, spectral imaging, Fat, Bone, marrow, MRI, Osteoporosis

Feipeng Song, Jin Zhang, Yi Xu, Minghui Ding, Xinwen Wang, Xu Liu, Kai Sun. Application of CT energy spectrum imaging in the determination of bone marrow fat content in auxiliary diagnosis of osteoporosis[J]. Chinese Journal of Geriatrics Research(Electronic Edition), 2020, 07(01): 27-30.

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