Department of Physics, Lund University, Lund, Sweden.
Division of Surgery, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden.
J Biophotonics. 2022 Oct;15(10):e202200140. doi: 10.1002/jbio.202200140. Epub 2022 Aug 4.
The aim of this work was to evaluate the capability of diffuse reflectance spectroscopy to distinguish malignant liver tissues from surrounding tissues and to determine whether an extended wavelength range (450-1550 nm) offers any advantages over using the conventional wavelength range. Furthermore, multivariate analysis combined with a machine learning algorithm, either linear discriminant analysis or the more advanced support vector machine, was used to discriminate between and classify freshly excised human liver specimens from 18 patients. Tumors were distinguished from surrounding liver tissues with a sensitivity of 99%, specificity of 100%, classification rate of 100% and a Matthews correlation coefficient of 100% using the extended wavelength range and a combination of principal component analysis and support vector techniques. The results indicate that this technology may be useful in clinical applications for real-time tissue diagnostics of tumor margins where rapid classification is important.
本研究旨在评估漫反射光谱技术鉴别肝恶性组织与周围组织的能力，并确定扩展波长范围（450-1550nm）是否优于传统波长范围。此外，采用多元分析结合机器学习算法（线性判别分析或更先进的支持向量机）对 18 例新鲜切除的人类肝脏标本进行鉴别和分类。使用扩展波长范围以及主成分分析和支持向量技术相结合的方法，肿瘤与周围肝组织的灵敏度为 99%、特异性为 100%、分类率为 100%，马氏相关系数为 100%。结果表明，该技术在实时肿瘤边界组织诊断的临床应用中可能具有重要意义，因为它需要快速分类。
