Department of Radiological Sciences, Oncology and Pathology, I.C.O.T. Hospital, Sapienza University of Rome, Via Franco Faggiana 1668, 04100 Latina, Italy.
Department of Medical Surgical Sciences and Biotechnologies, Sapienza University of Rome, C.so della Repubblica 79, 04100 Latina, Italy.
Int J Mol Sci. 2023 Apr 13;24(8):7214. doi: 10.3390/ijms24087214.
Radiological imaging is currently employed as the most effective technique for screening, diagnosis, and follow up of patients with breast cancer (BC), the most common type of tumor in women worldwide. However, the introduction of the omics sciences such as metabolomics, proteomics, and molecular genomics, have optimized the therapeutic path for patients and implementing novel information parallel to the mutational asset targetable by specific clinical treatments. Parallel to the "omics" clusters, radiological imaging has been gradually employed to generate a specific omics cluster termed "radiomics". Radiomics is a novel advanced approach to imaging, extracting quantitative, and ideally, reproducible data from radiological images using sophisticated mathematical analysis, including disease-specific patterns, that could not be detected by the human eye. Along with radiomics, radiogenomics, defined as the integration of "radiology" and "genomics", is an emerging field exploring the relationship between specific features extracted from radiological images and genetic or molecular traits of a particular disease to construct adequate predictive models. Accordingly, radiological characteristics of the tissue are supposed to mimic a defined genotype and phenotype and to better explore the heterogeneity and the dynamic evolution of the tumor over the time. Despite such improvements, we are still far from achieving approved and standardized protocols in clinical practice. Nevertheless, what can we learn by this emerging multidisciplinary clinical approach? This minireview provides a focused overview on the significance of radiomics integrated by RNA sequencing in BC. We will also discuss advances and future challenges of such radiomics-based approach.
放射影像学目前被用作筛查、诊断和随访乳腺癌(BC)患者的最有效技术,BC 是全球女性最常见的肿瘤类型。然而,代谢组学、蛋白质组学和分子基因组学等组学科学的引入,优化了患者的治疗路径,并实施了与特定临床治疗可靶向的突变资产平行的新信息。与“组学”集群平行,放射影像学已逐渐被用于生成一个特定的“放射组学”组学。放射组学是一种新颖的先进成像方法,使用复杂的数学分析从放射图像中提取定量且理想的可重复数据,包括人类肉眼无法检测到的疾病特异性模式。与放射组学一样,放射基因组学定义为“放射学”和“基因组学”的整合,是一个新兴领域,探索从放射图像中提取的特定特征与特定疾病的遗传或分子特征之间的关系,以构建适当的预测模型。因此,组织的放射学特征应该模拟特定的基因型和表型,并更好地探索肿瘤随时间的异质性和动态演变。尽管有了这些改进,我们在临床实践中仍远未实现经过批准和标准化的方案。然而,通过这种新兴的多学科临床方法,我们可以学到什么呢?这篇小型综述提供了一个关于将 RNA 测序整合到 BC 中的放射组学的意义的重点概述。我们还将讨论这种基于放射组学的方法的进展和未来挑战。