About this Research Topic
Tumor microenvironment (TME), which contains a complex mixture of malignant and non-malignant cells, plays an essential role in malignancies initiation and progression and provides plentiful targets for personalized therapy. Understanding TME can facilitate therapeutic decision-making and response prediction. The heterogeneity of malignancies can be mirrored in TME. Therefore, non-invasive investigations of TME would contribute to the personalized therapy of malignancies. Imaging modalities, including ultrasound, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET), are indispensable in the diagnosis of solid malignancies and assessment of treatment response. Radiomics, which harnesses computers to extract large numbers of quantitative features from medical imaging (especially those beyond human visual perception), has made it a promising biomarker for predicting the prognosis and therapeutic response assessment of various malignancies.
This Research Topic aims to collect articles highlighting the use of radiomics to probe TME to facilitate diagnosis and treatment assessment of solid malignancies. We are interested in collecting original articles and reviews describing the potential of radiomics derived from multiple imaging modalities for the TME, especially its application in therapeutic decision-making, and the possible limitations of radiomics and artificial medicine.
● Radiomics derived from multimodality imaging (including ultrasound, CT, MRI and PET) for TME of various solid malignancies
● TME radiomics models for predicting treatment response, especially about targeted therapy and immunotherapy
● Methods of medical imaging data preparation and algorithms for machine learning and deep learning of TME
● Role of TME radiomics biomarkers integrating other molecular features of tumors, such as tumor mutation burden and PD-L1 expression, in delivering precision medicine
This Research Topic aims to collect articles highlighting the use of radiomics to probe TME to facilitate diagnosis and treatment assessment of solid malignancies. We are interested in collecting original articles and reviews describing the potential of radiomics derived from multiple imaging modalities for the TME, especially its application in therapeutic decision-making, and the possible limitations of radiomics and artificial medicine.
● Radiomics derived from multimodality imaging (including ultrasound, CT, MRI and PET) for TME of various solid malignancies
● TME radiomics models for predicting treatment response, especially about targeted therapy and immunotherapy
● Methods of medical imaging data preparation and algorithms for machine learning and deep learning of TME
● Role of TME radiomics biomarkers integrating other molecular features of tumors, such as tumor mutation burden and PD-L1 expression, in delivering precision medicine
Keywords: tumor microenvironment, radiomics, artificial intelligence, personalized medicine, treatment response
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
