Orthopedics Department, Affiliated Hospital 6 of Nantong University, Yancheng, 224001, China.
College of Pharmacy, Jiangsu Vocational College of Medicine, Yancheng, 224005, China.
Eur J Med Res. 2024 Sep 30;29(1):476. doi: 10.1186/s40001-024-02081-2.
Osteoporosis (OP) is a chronic disease characterized by diminished bone mass and structural deterioration, ultimately leading to compromised bone strength and an increased risk of fractures. Diagnosis primarily relies on medical imaging findings and clinical symptoms. This study aims to explore an adjunctive diagnostic technique for OP based on surface-enhanced Raman scattering (SERS). Serum SERS spectra from the normal, low bone density, and osteoporosis groups were analyzed to discern OP-related expression profiles. This study utilized partial least squares (PLS) and support vector machine (SVM) algorithms to establish an OP diagnostic model. The combination of Raman peak assignments and spectral difference analysis reflected biochemical changes associated with OP, including amino acids, carbohydrates, and collagen. Using the PLS-SVM approach, sensitivity, specificity, and accuracy for screening OP were determined to be 77.78%, 100%, and 88.24%, respectively. This study demonstrates the substantial potential of SERS as an adjunctive diagnostic technology for OP.
骨质疏松症（OP）是一种以骨量减少和结构恶化为特征的慢性疾病，最终导致骨强度受损，骨折风险增加。诊断主要依赖于医学影像学发现和临床症状。本研究旨在探索一种基于表面增强拉曼散射（SERS）的骨质疏松症辅助诊断技术。分析了正常、低骨密度和骨质疏松症组的血清 SERS 光谱，以辨别与 OP 相关的表达谱。本研究利用偏最小二乘（PLS）和支持向量机（SVM）算法建立了 OP 诊断模型。拉曼峰分配和光谱差异分析的结合反映了与 OP 相关的生化变化，包括氨基酸、碳水化合物和胶原蛋白。使用 PLS-SVM 方法，筛选 OP 的灵敏度、特异性和准确性分别为 77.78%、100%和 88.24%。本研究表明 SERS 作为 OP 辅助诊断技术具有很大的潜力。
