Ruppin Academic Center, Department of Electrical and Computer Engineering, Emek-Hefer, Israel.
Gynecologic Oncology Division, Department of Obstetrics and Gynecology, Hillel Yaffe Medical Center, Hadera, Israel.
J Biophotonics. 2020 Sep;13(9):e202000114. doi: 10.1002/jbio.202000114. Epub 2020 Jun 23.
A rapid and reliable intraoperative diagnostic technique to support clinical decisions was developed using Fourier-transform infrared (FTIR) spectroscopy. Twenty-six fresh tissue samples were collected intraoperatively from patients undergoing gynecological surgeries. Frozen section (FS) histopathology aimed to discriminate between malignant and benign tumors was performed, and attenuated total reflection (ATR) FTIR spectra were collected from these samples. Digital dehydration and principal component analysis and linear discriminant analysis (PCA-LDA) models were developed to classify samples into malignant and benign groups. Two validation schemes were employed: k-fold and "leave one out." FTIR absorption spectrum of a fresh tissue sample was obtained in less than 5 minutes. The fingerprint spectral region of malignant tumors was consistently different from that of benign tumors. The PCA-LDA discrimination model correctly classified the samples into malignant and benign groups with accuracies of 96% and 93% for the k-fold and "leave one out" validation schemes, respectively. We showed that a simple tissue preparation followed by ATR-FTIR spectroscopy provides accurate means for very rapid tumor classification into malignant and benign gynecological tumors. With further development, the proposed method has high potential to be used as an adjunct to the intraoperative FS histopathology technique.
一种使用傅里叶变换红外（FTIR）光谱学开发的快速可靠的术中诊断技术，用于支持临床决策。从接受妇科手术的患者术中采集了 26 个新鲜组织样本。进行冷冻切片（FS）组织病理学检查以区分恶性和良性肿瘤，并从这些样本中采集衰减全反射（ATR）FTIR 光谱。开发了数字脱水和主成分分析和线性判别分析（PCA-LDA）模型，将样本分类为恶性和良性组。采用了两种验证方案：k 折和“留一法”。新鲜组织样本的 FTIR 吸收光谱在不到 5 分钟内获得。恶性肿瘤的指纹谱区始终与良性肿瘤不同。PCA-LDA 判别模型分别以 k 折和“留一法”验证方案的 96%和 93%的准确率将样本正确分类为恶性和良性组。我们表明，简单的组织制备后进行 ATR-FTIR 光谱学分析为快速准确地将肿瘤分为恶性和良性妇科肿瘤提供了一种手段。随着进一步的发展，该方法具有作为术中 FS 组织病理学技术的辅助手段的巨大潜力。
