Zhang Tingfeng, Zhao Liang, Cui Tingting, Zhou Yi, Li Peifen, Luo Chuqiao, Wei Junkang, Hu Hong
Division of Breast Surgery, Department of General Surgery, The Second Clinical Medical College, The First Affiliated Hospital, Shenzhen People's Hospital, Jinan University, Southern University of Science and Technology), Shenzhen, 518020, Guangdong, China.
Shenzhen Health Development Research and Data Management Center, Shenzhen, 518000, Guangdong, China.
J Transl Med. 2025 Jun 18;23(1):681. doi: 10.1186/s12967-025-06641-w.
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.
放射组学正在经历从单组学向多组学、从单时间点分析向多时间点分析以及从整体分析向亚区域分析的范式转变。这些转变在应对与乳腺癌新辅助化疗(NAC)前后成像变化相关的关键挑战方面显示出巨大潜力。此外,放射组学在探索肿瘤异质性和揭示潜在生物学机制等任务中取得了显著进展。将成像数据与基因数据整合为理解由特定基因改变驱动的成像变化提供了新的视角。然而,目前关于乳腺癌新辅助化疗的放射组学研究尚未实现成像变化与潜在生物学机制的紧密整合。它们在很大程度上局限于模型与基因组数据之间的简单关联,而没有深入解释成像特征中固有的生物学意义,而这对于将这些特征与疾病的动态进展直接联系起来至关重要。本综述旨在探索乳腺癌NAC期间观察到的成像改变的时空异质性,同时使用既定的分析方法评估其生物学意义。它强调了时空放射组学在预测模型开发中的独特优势,并研究了NAC前后成像动态与基因表达谱之间的潜在相关性。此外,我们批判性地审视了以前的放射基因组学研究,为其局限性提供理论见解。最后,本综述提出了在乳腺癌NAC中应用时空放射基因组学的未来方向和创新方法,为该领域的研究人员和临床医生提供了有价值的参考和路线图。