Prediction of osteoporosis and osteopenia by routine computed tomography of the lumbar spine in different regions of interest.

J Orthop Surg Res

Shi's Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Institute of Traumatology & Orthopedics, Shanghai Academy of Traditional Chinese Medicine, No. 528, Zhangheng Road, Shanghai, Pudong New Area, 201203, China.

Published: October 2022

Background: We aimed to investigate the utility of Hounsfield units (HU) obtained from different regions of interest in opportunistic lumbar computed tomography (CT) to predict osteoporosis coupling with data of dual-energy X-ray absorptiometry (DXA).

Methods: A total of 100 patients who attended a university hospital in Shanghai, China, and had undergone CT and DXA tests of the lumbar spine within 3 months were included in this retrospective review. Images were reviewed on axial sections, and regions of interest (ROI) markers were placed on the round, oval, anterior, left, and right of the L1-L4 vertebra to measure the HU. The mean values of CT HU were then compared to the bone mineral density (BMD) measured by DXA. Receiver operator characteristic curves were generated to determine the threshold for diagnosis and its sensitivity and specificity values.

Results: The differences in CT HU of different ROI based on DXA definitions of osteoporosis, osteopenia, and normal individuals were statistically significant (p < 0.01). The HU values of the different ROI correlated well with the BMD values (Spearman coefficient all > 0.75, p < 0.01). The threshold for diagnosing osteoporosis varies from 87 to 111 HU in different ROIs, and the threshold for excluding osteoporosis or osteopenia is 99-125 HU.

Conclusion: This is the first study on osteoporosis diagnosis of different ROI with routine CT lumbar scans. There is a strong correlation between CT HU of different ROI in the lumbar spine and BMD, and HU measurements can be used to predict osteoporosis.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9571421PMC
http://dx.doi.org/10.1186/s13018-022-03348-2DOI Listing

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