ArticleEuropean journal of radiology open2022
Using texture analysis in the development of a potential radiomic signature for early identification of hepatic metastasis in colorectal cancer.
Article in European journal of radiology open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence with magnetic resonance imaging for prediction of pathological complete response to neoadjuvant chemoradiotherapy in rectal cancer: A systematic review and meta-analysis.Frontiers in oncology · 2022Pooled it
- CT-Based Radiomics Models with External Validation for Prediction of Recurrence and Disease-Specific Mortality After Radical Surgery of Colorectal Liver Metastases.Annals of surgical oncology · 2025Article
- Review
- Colorectal cancer liver metastases: A radiologic point of view.World journal of gastrointestinal oncology · 2025Article
- Signaling pathways involved in colorectal cancer: pathogenesis and targeted therapy.Signal transduction and targeted therapy · 2024Review
- Artificial Intelligence to Early Predict Liver Metastases in Patients with Colorectal Cancer: Current Status and Future Prospectives.Life (Basel, Switzerland) · 2023Review
- Radiomics in colorectal cancer patients.World journal of gastroenterology · 2023Review
- Colorectal liver metastases patients prognostic assessment: prospects and limits of radiomics and radiogenomics.Infectious agents and cancer · 2023Review
- Review
- Whole-liver enhanced CT radiomics analysis to predict metachronous liver metastases after rectal cancer surgery.Cancer imaging : the official publication of the International Cancer Imaging Society · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Background: Radiomics allows information not readily available to the naked eye to be extracted from high resolution imaging modalities such as CT. Identifying that a cancer has already metastasised at the time of presentation through a radiomic signature will affect the treatment pathway. The ability to recognise the existence of metastases earlier will have a significant impact on the survival outcomes. Aim: To create a novel radiomic signature using textural analysis in the evaluation of synchronous liver metastases in colorectal cancer. Methods: CT images at baseline and subsequent surveillance over a 5-year period of patients with colorectal cancer were processed using textural analysis software. Comparison was made between those patients who developed liver metastases and those that remained disease free to detect differences in the 'texture' of the liver. Results: A total of 24 patients were divided into two matched groups for comparison. Significant differences between the two groups scores when using the textural analysis programme were found on coarse filtration (p = 0.044). Patients that went on to develop metastases an average of 18 months after presentation had higher levels of hepatic heterogeneity on CT. Conclusion: This initial study demonstrates the potential of using a textural analysis programme to build a radiomic signature to predict the development of hepatic metastases in rectal cancer patients otherwise thought to have clear staging CT scans at time of presentation.
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