a Department of Electronic Engineering , Fudan University , Shanghai , China.
b Key laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai , Shanghai , China.
Comput Assist Surg (Abingdon). 2017 Dec;22(sup1):18-25. doi: 10.1080/24699322.2017.1378722. Epub 2017 Sep 15.
Glioblastoma is the most aggressive malignant brain tumor with poor prognosis. Radiomics is a newly emerging and promising technique to reveal the complex relationships between high-throughput medical image features and deep information of disease including pathology, biomarkers and genomics. An approach was developed to investigate the internal relationship between magnetic resonance imaging (MRI) features and the age-related origins of glioblastomas based on a quantitative radiomics method. A fully automatic image segmentation method was applied to segment the tumor regions from three dimensional MRI images. 555 features were then extracted from the image data. By analyzing large numbers of quantitative image features, some predictive and prognostic information could be obtained by the radiomics approach. 96 patients diagnosed with glioblastoma pathologically have been divided into two age groups (<45 and ≥45 years old). As expected, there are 101 features showing the consistency with the age groups (T test, p < .05), and unsupervised clustering results of those features also show coherence with the age difference (T test, p= .006). In conclusion, glioblastoma in different age groups present different radiomics-feature patterns with statistical significance, which indicates that glioblastoma in different age groups should have different pathologic, protein, or genic origins.
胶质母细胞瘤是最具侵袭性的恶性脑肿瘤，预后不良。放射组学是一种新兴的有前途的技术，可以揭示高通量医学图像特征与疾病的深层信息（包括病理学、生物标志物和基因组学）之间的复杂关系。本研究旨在基于定量放射组学方法，研究磁共振成像（MRI）特征与胶质母细胞瘤的年龄起源之间的内在关系。该方法采用全自动图像分割方法，从三维 MRI 图像中分割肿瘤区域。然后从图像数据中提取 555 个特征。通过分析大量定量图像特征，放射组学方法可以获得一些预测和预后信息。96 名经病理诊断为胶质母细胞瘤的患者被分为两个年龄组（<45 岁和≥45 岁）。正如预期的那样，有 101 个特征与年龄组一致（T 检验，p<.05），这些特征的无监督聚类结果也与年龄差异一致（T 检验，p=0.006）。总之，不同年龄组的胶质母细胞瘤呈现出具有统计学意义的不同放射组学特征模式，这表明不同年龄组的胶质母细胞瘤可能具有不同的病理、蛋白或基因起源。
