Abstract

Objectives: Utilizing artificial intelligence (AI)-assisted chest computed tomography (CT) to assess bone mineral density (BMD) in patients requiring long-term glucocorticoid (GC) therapy.
Materials and methods: In this retrospective study, dual-energy X-ray absorptiometry (DXA) was used as the gold standard for BMD assessment. The area under the receiver operating characteristic curve (AUC) was used to test diagnostic accuracy. We combined opportunistic chest CT and AI to measure vertebral BMD.
Results: We analyzed results of 249 chest CT-DXA pairs from 235 patients requiring GC therapy. Prevalence of osteopenia and osteoporosis was 28.51% and 22.13%, respectively. The average of thoracic 11 (T11) and T12 vertebral BMD measured by AI (AI-BMD) was 154.83 mg/cm³ and 147.56 mg/cm³, respectively. AUC of AI-BMD for osteopenia/osteoporosis was 0.867 (95% confidence interval (CI): 0.823, 0.911) at T11 and 0.844 (95% CI: 0.795, 0.893) at T12. No significant differences in AUC between T11 and T12 were found in the cohort. 80 pairs of chest CT-DXA scans were performed among patients with long-term GC therapy. AUC of AI-BMD for osteopenia/osteoporosis were excellent in patients with long-term and initiating GC therapy. There were no significant differences in AUC among the two subgroups.
Conclusion: We found that AI-assisted chest CT is a convenient diagnostic tool for BMD assessment. AUC of AI-BMD for osteopenia/osteoporosis at T11 and T12 is excellent in patients requiring long-term GC therapy. By using AI-assisted opportunistic chest CT, patients can receive BMD assessments without the extra burden.

Author Details

Authors

• Ruigang Huang¹
• Xian Wang²
• Yanhua Qiu¹
• Weihua Lin¹
• Lihao Wei¹
• Jiguang Zhou³
• Chunhong Huang²
• Shanying Chen²

Departments

• ¹ Department of Radiology,
• ² Department of Nephrology, and
• ³ Statistical Office, Zhangzhou Affiliated Hospital of Fujian Medical University

Address

Shanying Chen, MD
Department of Nephrology
Zhangzhou Affiliated Hospital of Fujian Medical University
59 # Shengli Xi Road
Zhangzhou, P. R. China 363000
Email: [email protected]

Citation