Quantitative diagnosis of osteoporosis using lumbar spine signal intensity in magnetic resonance imaging

(2019) Quantitative diagnosis of osteoporosis using lumbar spine signal intensity in magnetic resonance imaging. British Journal of Radiology. ISSN 0007-1285

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Abstract

Objective: Osteoporosis is the most common metabolic bone disease that is not recognized in many elderly people. To determine the cause of low back pain, lumbosacral MRI is done for a large population who may not have gone under dual energy X-ray absorptiometry (DXA). The aim of this study was to predict bone density using lumbar spine signals in lumbosacral MRI in high risk patients for osteoporosis including post-menopausal females and calculate a threshold for a new quantitative MRI-based score to be used in estimation of lumbar spine bone mass density. Methods: 82 menopaused females, who had undergone DXA before, were selected and MRI was done within 6 months after DXA. 69 healthy females aged 20-29 years who had undergone lumbar MRI were selected as reference group. Results were analyzed and threshold and diagnostic performance of MRI-based score (M-score) on the method of T-score was calculated. Results: Negative correlation between M-score and T-score was detected. Cut off point of 2.05 was found for M-score with near sensitivity of 90 and specificity of 87 for detecting osteoporotic patients from non-osteoporotic individuals. Conclusion: M-score is a MRI-based method which can identify patients at risk of osteoporosis. Early diagnosis of osteoporosis can reduce morbidity and mortality caused by it. Advances in knowledge: The research introduced cut of points for M-score as a new MRI quantitative method to be used as an opportunistic technique for detecting osteoporotic patients.

Item Type: Article
Keywords: bone-mineral density marrow adipose-tissue fat-content fracture mri
Subjects: WN Radiology. Diagnostic Imaging
Divisions: Faculty of Medicine > Departments of Clinical Sciences > Department of Radiology
Journal or Publication Title: British Journal of Radiology
Journal Index: ISI
Volume: 92
Number: 1097
Identification Number: ARTN 20180774 10.1259/bjr.20180774
ISSN: 0007-1285
Depositing User: Zahra Otroj
URI: http://eprints.mui.ac.ir/id/eprint/10385

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