Spatial-temporal radiogenomics in predicting neoadjuvant chemotherapy efficacy for breast cancer: a comprehensive review

时空放射基因组学在预测乳腺癌新辅助化疗疗效中的应用:一项综合综述

阅读:1

Abstract

Radiomics is undergoing a paradigm shift from single-omics to multi-omics, from single-temporal to multi-temporal analysis, and from global to subregional analysis. These transformations have shown great potential in addressing key challenges related to imaging changes before and after neoadjuvant chemotherapy (NAC) in breast cancer. Furthermore, radiomics has achieved remarkable progress in tasks such as exploring tumor heterogeneity and uncovering underlying biological mechanisms. Integrating imaging data with gene data offers novel perspectives for understanding imaging changes driven by specific genetic alterations. However, current radiomics studies on neoadjuvant chemotherapy for breast cancer have not yet achieved a close integration of imaging changes with underlying biological mechanisms. They are largely limited to simple associations between models and genomic data, without in-depth interpretation of the biological significance inherent in imaging features, which is essential to directly link these features with the dynamic progression of the disease. This review seeks to explore the spatial-temporal heterogeneity of imaging alterations observed during NAC for breast cancer, while assessing their biological implications using established analytical approaches. It highlights the distinct advantages of spatial-temporal radiomics in predictive model development and examines potential correlations between imaging dynamics and gene expression profiles before and after NAC. Additionally, we critically examines previous radiogenomics studies, providing theoretical insights into their limitations. Finally, the review proposes future directions and innovative approaches for applying spatial-temporal radiogenomics in NAC for breast cancer, serving as a valuable reference and roadmap for researchers and clinical practitioners in this field.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。