In vivo quantification of bone mineral density of lumbar vertebrae using fast kVp switching dual-energy CT: correlation with quantitative computed tomography

摘要

Background: Osteoporosis is a common, progressive disease related to low bone mineral density (BMD). If it can be diagnosed at an early stage, osteoporosis is treatable. Quantitative computed tomography (QCT) is one of the current reference standards of BMD measurement, but dual-energy computed tomography (DECT) is considered to be a potential alternative. This study aimed to evaluate the feasibility and accuracy of phantomless in vivo DECT-based BMD quantification in comparison with QCT. Methods: A total of 128 consecutive participants who underwent DECT lumbar examinations between July 2018 and February 2019 were retrospectively analyzed. The density of calcium (water), hydroxyapatite (water), calcium (fat), and hydroxyapatite (fat) [D Ca(Wa) , D HAP(Wa) , D Ca(Fat) and D HAP(Fat) , respectively] were measured along with BMD in the trabecular bone of lumbar level 1–2 by DECT and QCT. Linear regression analysis was performed to assess the relationship between DECT- and QCT-derived BMD at both the participant level and the vertebral level. Linear regression models were quantitatively evaluated with adjusted R -square, normalized mean squared error (NMSE) and relative error (RE). Bland-Altman analysis was conducted to assess agreement between measurements. P0.05 was considered statistically significant. Results: Strong correlations were observed between DECT- and QCT-derived BMD at both the participant level and the vertebral level (adjusted R 2 =0.983–0.987; NMSE = 1.6–2.1%; RE linear =0.6–0.9%). Bland-Altman plots indicated high agreement between both measurements. D Ca(Fat) and D HAP(Fat) showed relatively similar and optimal predictive capability for QCT-derived BMD (both: adjusted R 2 =0.987, NMSE =1.6%, RE linear =0.6%). Conclusions: Fast kVp switching DECT enabled accurate phantomless in vivo BMD quantification of the lumbar spine. D Ca(Fat) and D HAP(Fat) had relatively similar and optimal predictive capability.