Image-based omics applications in rectal cancer: State of the art and future directions

Image-based omics sciences, such as radiomics and digital pathology, are transforming rectal cancer management, offering new dimensions in precision medicine. Radiomics extracts quantitative features from imaging modalities like MRI, CT, and PET, revealing tumor characteristics undetectable by the human eye. By applying machine learning and AI, radiomics can predict tumor behavior and treatment response, facilitating personalized treatment plans. Digital pathology digitizes histopathological slides for AI analysis, identifying cellular features and biomarkers relevant to rectal cancer. The synergy between radiomics and digital pathology enables noninvasive predictions and biological validations, enhancing clinical decision-making. This chapter reviews the current state of image-based omics in rectal cancer, highlighting their potential to revolutionize precision oncology. Through advanced AI techniques and integrated multiomics approaches, these innovations promise to optimize therapeutic efficacy, improve patient outcomes, and pave the way for personalized cancer care.