近红外光谱在子宫癌和子宫肌瘤检测中的应用。

Danyang Cheng, Haiqiu Yang, Arielle S Joasil, Xiaowei Chen, Hanina Hibshoosh, Christine P Hendon
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引用次数: 0

摘要

子宫内膜癌和子宫平滑肌瘤(肌瘤)是常见的子宫疾病,需要早期诊断以改善患者的症状并提高介入手术的成功率。在这项工作中,我们报告了24例子宫切除术后69例子宫癌和肌瘤的近红外光谱特征。根据光谱形态的差异,采用近红外光谱对比参数对正常子宫、癌组织和肌瘤组织进行鉴别。利用显著的光学特征和光谱主成分,该分类模型对子宫组织的分类预测准确率高于70%,对癌症标本的识别灵敏度为70%,特异性为93%,对肌瘤标本的识别灵敏度为86%,特异性为83%。这些结果表明,近红外成像有希望作为妇科成像的补充方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Near-Infrared Spectroscopy Mapping for Uterine Cancer and Fibroid Detection.

Endometrial cancer and uterine leiomyomas (fibroid) are common uterine pathologies that require early diagnosis to improve a patient's symptoms and increase the success rate of interventional procedures. In this work, we report on near-infrared spectroscopy (NIRS) spectral features of uterine cancer and fibroids from 69 surgical specimens obtained from 24 patients following hysterectomies. Normal uterus, cancer, and fibroid tissue were identified by NIR spectral contrast parameters based on the differences in spectrum morphology. Using the significant optical features and spectral principal components, a classification model was able to classify uterus tissue with a prediction accuracy higher than 70%, identifying cancer specimens with 70% sensitivity and 93% specificity, and fibroid samples with 86% sensitivity and 83% specificity. These results demonstrated NIRS mapping has promise as a complementary method for gynecologic imaging.

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