用MRI影像特征预测胶质母细胞瘤的IDH基因状态
MRI Radiomics for IDH Genotype Prediction in Glioblastoma Diagnosis
- 从MRI影像自动提取特征，识别IDH突变状态
- 可辅助无创诊断，提升胶质瘤分型准确率
- 适合医学影像与肿瘤生物标志物研究者
放射组学是一种利用影像扫描中自动识别特征的新兴领域，在肿瘤学中应用广泛，因许多关键肿瘤生物标志物无法通过人眼直接观察。随着医学影像大数据和新机器学习技术的发展，实现了更快更准确的肿瘤诊断。基于放射组学的标准化数学特征提取可减少放射科医生的主观偏差。本文综述了近年来磁共振成像（MRI）放射组学在肿瘤学中的进展，重点聚焦于异柠檬酸脱氢酶（IDH）突变状态的识别，该状态是胶质母细胞瘤和Ⅳ级星形细胞瘤诊断的重要生物标志物。
原文摘要 · Abstract (English)
Radiomics is a relatively new field which utilises automatically identified features from radiological scans. It has found a widespread application, particularly in oncology because many of the important oncological biomarkers are not visible to the naked eye. The recent advent of big data, including in medical imaging, and the development of new ML techniques brought the possibility of faster and more accurate oncological diagnosis. Furthermore, standardised mathematical feature extraction based on radiomics helps to eliminate possible radiologist bias. This paper reviews the recent development in the oncological use of MRI radiomic features. It focuses on the identification of the isocitrate dehydrogenase (IDH) mutation status, which is an important biomarker for the diagnosis of glioblastoma and grade IV astrocytoma.
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