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在胰腺活检中使用红外成像进行快速癌症成像,使用红外成像

Paulina Koziol-Bohatkiewicz^1,2, Danuta Liberda-Matyja^1,3, Tomasz P Wrobel¹

¹Solaris National Synchrotron Radiation Centre, Jagiellonian University, Czerwone Maki 98, 30-392, Krakow, Poland. tomek.wrobel@uj.edu.pl.

|February 22, 2024

概括

量子级联激光 (QCL) 显微镜与机器学习相结合,有效检测胰腺癌. 这项技术还可以快速评估外科手术边缘,提高诊断速度和临床环境中的准确性.

科学领域:

生物医学光学生物医学光学
频谱学是一种光谱学.
机器学习应用机器学习应用

背景情况:

胰腺管道腺癌是一种致命的癌症,诊断和治疗选择有限.
红外 (IR) 光谱和机器学习显示出癌症检测的前景.
量子级联激光 (QCL) 显微镜为临床应用提供更快,频率特定的测量.

研究的目的:

为胰腺癌分类建立基于QCL显微镜的模型.
开发一种使用减少光谱信息的快速外科边缘检测模型.
将现有的福里埃变换红外诊断模型转换为QCL显微镜.

主要方法:

预处理QCL光谱数据.
培训随机森林 (RF) 分类器用于组织分类.
对诊断模型的光谱特征选择的优化.

主要成果:

成功地将诊断模型转化为高预测能力 (AUC = 98%) 的QCL显微镜,用于癌细胞组织.
开发使用有限频谱的快速外科边缘识别模型.
使用QCL显微镜对良性和癌症组织进行有前途的区分.

结论:

QCL显微镜是有效的胰腺癌诊断的可行工具.
开发的模型显示了快速,手术内外科手术边缘评估的潜力.
QCL显微镜可以在几分钟内获得诊断结果,与临床时间框架保持一致.

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