Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China.
Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China; College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China.
Spectrochim Acta A Mol Biomol Spectrosc. 2024 Jun 5;314:124193. doi: 10.1016/j.saa.2024.124193. Epub 2024 Mar 29.
Osteoporosis is a significant health concern. While multiple techniques have been utilized to diagnose this condition, certain limitations still persist. Raman spectroscopy has shown promise in predicting bone strength in animal models, but its application to humans requires further investigation. In this study, we present an in vitro approach for predicting osteoporosis in 10 patients with hip fractures using Raman spectroscopy. Raman spectra were acquired from exposed femoral heads collected during surgery. Employing a leave-one-out cross-validated linear discriminant analysis (LOOCV-LDA), we achieved accurate classification (90 %) between osteoporotic and osteopenia groups. Additionally, a LOOCV partial least squares regression (PLSR) analysis based on the complete Raman spectra demonstrated a significant prediction (r = 0.84, p < 0.05) of bone mineral density as measured by dual X-ray absorptiometry (DXA). To the best of our knowledge, this study represents the first successful demonstration of Raman spectroscopy correlating with osteoporotic status in humans.
骨质疏松症是一个严重的健康问题。虽然已经有多种技术被用于诊断这种疾病，但仍存在某些局限性。拉曼光谱在预测动物模型中的骨强度方面显示出了前景，但将其应用于人类还需要进一步研究。在这项研究中，我们提出了一种使用拉曼光谱对 10 名髋部骨折患者进行骨质疏松症预测的体外方法。拉曼光谱是从手术中采集的暴露的股骨头中获得的。采用留一法交叉验证线性判别分析（LOOCV-LDA），我们在骨质疏松症和骨量减少组之间实现了准确的分类（90%）。此外，基于完整拉曼光谱的 LOOCV 偏最小二乘回归（PLSR）分析表明，与双能 X 线吸收法（DXA）测量的骨密度具有显著的预测关系（r=0.84，p<0.05）。据我们所知，这项研究首次成功地证明了拉曼光谱与人的骨质疏松症状态之间存在相关性。
