Automated Opportunistic Trabecular Volumetric Bone Mineral Density Extraction Outperforms Manual Measurements for the Prediction of Vertebral Fractures in Routine CT

DIAGNOSTICS(2023)

引用 0|浏览16
暂无评分
摘要
Opportunistic osteoporosis screening using multidetector CT-scans (MDCT) and convolutional neural network (CNN)-derived segmentations of the spine to generate volumetric bone mineral density (vBMD) bears the potential to improve incidental osteoporotic vertebral fracture (VF) prediction. However, the performance compared to the established manual opportunistic vBMD measures remains unclear. Hence, we investigated patients with a routine MDCT of the spine who had developed a new osteoporotic incidental VF and frequency matched to patients without incidental VFs as assessed on follow-up MDCT images after 1.5 years. Automated vBMD was generated using CNN-generated segmentation masks and asynchronous calibration. Additionally, manual vBMD was sampled by two radiologists. Automated vBMD measurements in patients with incidental VFs at 1.5-years follow-up (n = 53) were significantly lower compared to patients without incidental VFs (n = 104) (83.6 & PLUSMN; 29.4 mg/cm(3) vs. 102.1 & PLUSMN; 27.7 mg/cm(3), p < 0.001). This comparison was not significant for manually assessed vBMD (99.2 & PLUSMN; 37.6 mg/cm(3) vs. 107.9 & PLUSMN; 33.9 mg/cm(3), p = 0.30). When adjusting for age and sex, both automated and manual vBMD measurements were significantly associated with incidental VFs at 1.5-year follow-up, however, the associations were stronger for automated measurements (& beta; = -0.32; 95% confidence interval (CI): -20.10, 4.35; p < 0.001) compared to manual measurements (& beta; = -0.15; 95% CI: -11.16, 5.16; p < 0.03). In conclusion, automated opportunistic measurements are feasible and can be useful for bone mineral density assessment in clinical routine.
更多
查看译文
关键词
osteoporosis,opportunistic screening,computed tomography,bone mineral density,osteoporotic fractures,computational neural networks
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要