Xiongfeng Tang, Cheng Zhang, Meng He, Chi Ma, Deming Guo, Huan Qi, Bo Chen, Kedi Yang, Xianyue Shen, Tak-Man Wong, William Weijia Lu, Yanguo Qin
Department of Orthopaedics, The Second Hospital of Jilin University, Changchun, China.
Department of Orthopaedics and Traumatology, The University of Hong Kong, Hong Kong, Hong Kong SAR, China.
Front Bioeng Biotechnol. 2022 Jun 28;10:856753. doi: 10.3389/fbioe.2022.856753. eCollection 2022.
The diagnosis of osteoporosis is still one of the most critical topics for orthopedic surgeons worldwide. One research direction is to use existing clinical imaging data for accurate measurements of bone mineral density (BMD) without additional radiation. A novel phantom-less quantitative computed tomography (PL-QCT) system was developed to measure BMD and diagnose osteoporosis, as our previous study reported. Compared with traditional phantom-less QCT, this tool can conduct an automatic selection of body tissues and complete the BMD calibration with high efficacy and precision. The function has great advantages in big data screening and thus expands the scope of use of this novel PL-QCT. In this study, we utilized lung cancer or COVID-19 screening low-dose computed tomography (LDCT) of 649 patients for BMD calibration by the novel PL-QCT, and we made the BMD changes with age based on this PL-QCT. The results show that the novel PL-QCT can predict osteoporosis with relatively high accuracy and precision using LDCT, and the AUC values range from 0.68 to 0.88 with DXA results as diagnosis reference. The relationship between PL-QCT BMD with age is close to the real trend population (from ∼160 mg/cc in less than 30 years old to ∼70 mg/cc in greater than 80 years old for both female and male groups). Additionally, the calculation results of Pearson's r-values for correlation between CT values with BMD in different CT devices were 0.85-0.99. To our knowledge, it is the first time for automatic PL-QCT to evaluate the performance against dual-energy X-ray absorptiometry (DXA) in LDCT images. The results indicate that it may be a promising tool for individuals screened for low-dose chest computed tomography.
骨质疏松症的诊断仍然是全球骨科医生最为关注的关键课题之一。一个研究方向是利用现有的临床影像数据,在不增加辐射的情况下准确测量骨密度(BMD)。正如我们之前的研究所报道,一种新型的无体模定量计算机断层扫描(PL-QCT)系统被开发出来用于测量骨密度并诊断骨质疏松症。与传统的无体模QCT相比,该工具能够自动选择身体组织,并高效、精确地完成骨密度校准。该功能在大数据筛查方面具有很大优势,从而扩大了这种新型PL-QCT的应用范围。在本研究中,我们利用649例患者的肺癌或新冠病毒病筛查低剂量计算机断层扫描(LDCT)数据,通过新型PL-QCT进行骨密度校准,并基于此PL-QCT得出骨密度随年龄的变化情况。结果表明,新型PL-QCT使用LDCT能够以较高的准确性和精密度预测骨质疏松症,以双能X线吸收法(DXA)结果作为诊断参考时,AUC值范围为0.68至0.88。PL-QCT骨密度与年龄的关系接近真实人群趋势(女性和男性组中,30岁以下约为160mg/cc,80岁以上约为70mg/cc)。此外,不同CT设备中CT值与骨密度之间相关性的Pearson's r值计算结果为0.85 - 0.99。据我们所知,这是首次在LDCT图像中使用自动PL-QCT评估其与双能X线吸收法(DXA)相比的性能。结果表明,它可能是一种用于低剂量胸部计算机断层扫描筛查人群的有前景的工具。