| Abstrakt: |
Colorectal cancer (CRC) is a global health challenge with high morbidity and mortality. Radiomics, an emerging field, utilizes quantitative imaging features extracted from medical images for CRC diagnosis, staging, treatment response assessment, and prognostication. This review highlights the potential of radiomics for personalized CRC management. Radiomics enables noninvasive tumor characterization, aiding in early detection and accurate diagnosis, and it can be used to predict tumor stage, lymph node involvement, and prognosis. Furthermore, radiomics guides personalized therapies by assessing the treatment response and identifying patients who could benefit. Challenges include standardizing imaging protocols and analysis techniques. Robust validation frameworks and user‐friendly software are needed for the integration of radiomics into clinical practice. Despite challenges, radiomics offers valuable insights into tumor biology, treatment response, and prognosis in CRC. Overcoming technical and clinical hurdles will unlock its full potential in CRC management. This review covers the role of radiomics in CRC diagnosis, staging, treatment response assessment, and prediction of treatment outcomes, and also discusses the challenges associated with implementing radiomics in clinical practice and highlighted the need for standardization and validation in this field. Furthermore, the review explores future directions, such as the integration of artificial intelligence and machine learning algorithms, which can further enhance the capabilities of radiomics in CRC. |
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