Department of Chemistry, University at Albany, SUNY, Albany, NY, 12222, USA.
Division of Otolaryngology Head and Neck Surgery, Albany Medical College, Albany, NY, 12208, USA.
Sci Rep. 2024 May 15;14(1):11135. doi: 10.1038/s41598-024-59850-6.
Sjögren's disease is an autoimmune disorder affecting exocrine glands, causing dry eyes and mouth and other morbidities. Polypharmacy or a history of radiation to the head and neck can also lead to dry mouth. Sjogren's disease is often underdiagnosed due to its non-specific symptoms, limited awareness among healthcare professionals, and the complexity of diagnostic criteria, limiting the ability to provide therapy early. Current diagnostic methods suffer from limitations including the variation in individuals, the absence of a single diagnostic marker, and the low sensitivity and specificity, high cost, complexity, and invasiveness of current procedures. Here we utilized Raman hyperspectroscopy combined with machine learning to develop a novel screening test for Sjögren's disease. The method effectively distinguished Sjögren's disease patients from healthy controls and radiation patients. This technique shows potential for development of a single non-invasive, efficient, rapid, and inexpensive medical screening test for Sjögren's disease using a Raman hyper-spectral signature.
干燥综合征是一种影响外分泌腺的自身免疫性疾病，可导致眼睛和口腔干燥及其他病变。多种药物治疗或头颈部放疗也会导致口干。由于其症状不具特异性、医疗保健专业人员认识有限以及诊断标准复杂，干燥综合征常常被漏诊，这限制了早期提供治疗的能力。目前的诊断方法存在局限性，包括个体差异、缺乏单一诊断标志物以及当前程序的灵敏度和特异性低、成本高、复杂和有创。在这里，我们利用拉曼高光谱结合机器学习来开发一种新的干燥综合征筛查测试。该方法可有效区分干燥综合征患者与健康对照和放疗患者。该技术有望开发出一种单一的无创、高效、快速和廉价的拉曼高光谱特征的干燥综合征医学筛查测试。
