1 Department of Radiology, University of California, Irvine Medical Center, Douglas Hospital, Rte 140, Rm 0115, Orange, CA 92868.
2 Department of Radiology, University of California, San Francisco, San Francisco, CA.
AJR Am J Roentgenol. 2018 Jan;210(1):30-38. doi: 10.2214/AJR.17.18754. Epub 2017 Oct 5.
The purpose of this review is to summarize advances in the molecular analysis of gliomas, the role genetics plays in MRI features, and how machine-learning approaches can be used to survey the tumoral environment.
The genetic profile of gliomas influences the course of treatment and clinical outcomes. Though biopsy is the reference standard for determining tumor genetics, it can suffer diagnostic delays due to surgical planning and pathologic assessment. Radiogenomics may allow rapid, low-risk characterization of genetic heterogeneity.
本综述旨在总结神经胶质瘤的分子分析进展、遗传学在 MRI 特征中的作用，以及机器学习方法如何用于调查肿瘤环境。
神经胶质瘤的遗传特征影响治疗过程和临床结果。尽管活检是确定肿瘤遗传学的参考标准，但由于手术计划和病理评估，活检可能会导致诊断延迟。放射基因组学可能允许快速、低风险地描述遗传异质性。
