Kukreti Shwayta, Cerussi Albert, Tromberg Bruce, Gratton Enrico
Beckman Laser Institute, University of California, Irvine CA, USA.
Dis Markers. 2008;25(6):281-90. doi: 10.1155/2008/651308.
We have discovered quantitative optical biomarkers unique to cancer by developing a double-differential spectroscopic analysis method for near-infrared (NIR, 650-1000 nm) spectra acquired non-invasively from breast tumors. These biomarkers are characterized by specific NIR absorption bands. The double-differential method removes patient specific variations in molecular composition which are not related to cancer, and reveals these specific cancer biomarkers. Based on the spectral regions of absorption, we identify these biomarkers with lipids that are present in tumors either in different abundance than in the normal breast or new lipid components that are generated by tumor metabolism. Furthermore, the O-H overtone regions (980-1000 nm) show distinct variations in the tumor as compared to the normal breast. To quantify spectral variation in the absorption bands, we constructed the Specific Tumor Component (STC) index. In a pilot study of 12 cancer patients we found 100% sensitivity and 100% specificity for lesion identification. The STC index, combined with other previously described tissue optical indices, further improves the diagnostic power of NIR for breast cancer detection.
通过开发一种双差分光谱分析方法，用于对从乳腺肿瘤无创获取的近红外（NIR，650 - 1000 nm）光谱进行分析，我们发现了癌症特有的定量光学生物标志物。这些生物标志物以特定的近红外吸收带为特征。双差分方法消除了与癌症无关的患者分子组成的特定差异，并揭示了这些特定的癌症生物标志物。基于吸收的光谱区域，我们将这些生物标志物与肿瘤中存在的脂质进行了识别，这些脂质在肿瘤中的丰度与正常乳腺不同，或者是由肿瘤代谢产生的新脂质成分。此外，与正常乳腺相比，O - H泛音区域（980 - 1000 nm）在肿瘤中显示出明显的变化。为了量化吸收带中的光谱变化，我们构建了特定肿瘤成分（STC）指数。在一项对12名癌症患者的初步研究中，我们发现病变识别的灵敏度和特异性均为100%。STC指数与其他先前描述的组织光学指数相结合，进一步提高了近红外技术对乳腺癌检测的诊断能力。
