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Ultra-low-dose Quantitative CT for Lumbar Bone Mineral Density Assessment: A Prospective Validation of Radiation
Meng Zhang1, Yanxia Chen1, Jianquan Chen1
1Department of Radiology, Guangdong Provincial Hospital of Chinese Medicine, 53 Jingle Road, Zhuhai City, Guangdong Province, China (M.Z., Y.C., J.C., J.C., M.X.).
Abstract:
Accurate assessment of bone mineral density (BMD) is essential for diagnosing osteoporosis, but conventional quantitative CT protocols are associated with relatively high radiation doses. This study aimed to evaluate the feasibility of a novel dual-parameter optimized ultra-low-dose CT (ULD-CT) protocol for quantitative BMD assessment in the lumbar spine, comparing its radiation dose, image quality, and diagnostic performance against standard-dose CT (SD-CT). In this prospective study, 245 patients undergoing lumbar surgery received paired pre- and postoperative CT scans: SD-CT (120kV/250mAs) and ULD-CT (100kV/30mAs). Radiation dose metrics (CTDIvol, DLP, effective dose [ED]), objective image quality (noise, SNR, CNR), and subjective quality (5-point Likert scale) were analyzed. Volumetric BMD (vBMD) was measured using QCT and classified per American College of Radiology criteria (normal, osteopenia, osteoporosis). Diagnostic performance was evaluated via sensitivity/specificity and ROC analysis. ULD-CT reduced radiation dose by 92.5% compared to SD-CT (ED: 0.88 vs. 11.68 mSv; CTDIvol: 1.93 vs. 25.66 mGy, both P < 0.001). While SD-CT demonstrated superior objective (P=0.001-0.01) and subjective image quality (P<0.001), ULD-CT maintained diagnostic acceptability (scores ≥3; interobserver ICC=0.73). ULD-CT showed slight BMD overestimation but no significant differences in gender, age, or osteoporosis subgroups (P>0.05). ROC analysis revealed high diagnostic accuracy for ULD-CT (AUC: 0.986-0.996), with sensitivity/specificity of 94.74-100% and 95.74-98.01%, respectively. The dual-parameter ULD-CT protocol achieves substantial radiation reduction (92.5%) while preserving the image quality and diagnostic accuracy for osteoporosis classification, offering a safer alternative for longitudinal BMD monitoring without compromising clinical utility.
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