ArticleUnited European gastroenterology journal2014
Whole-liver CT texture analysis in colorectal cancer: Does the presence of liver metastases affect the texture of the remaining liver?
Article in United European gastroenterology journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
- Predicting Mismatch-Repair Status in Rectal Cancer Using Multiparametric MRI-Based Radiomics Models: A Preliminary Study.BioMed research international · 2022Trial
- Trial
- Predicting intrahepatic recurrence of colorectal cancer liver metastases after curative hepatectomy using a machine learning model with data integration of ultrasound radiomics and clinicopathological parameters.Insights into imaging · 2026Article
- Treatment of oligometastatic disease in colorectal cancer: from molecular biology to multimodal strategies.Oncology reviews · 2026Review
- Explainable multi-modal radiomics for early prediction of liver metastasis in rectal cancer: a multicentric study.Insights into imaging · 2025Article
- Construction of a prognostic survival model for colorectal cancer patients using CT image texture analysis: a prospective cohort study.Frontiers in oncology · 2025Article
- Development and independent validation of explainable radiomics-based machine learning models for prognosis in colorectal liver metastases.Frontiers in digital health · 2025Article
- Organotropic metastasis in colorectal cancer: integrating molecular pathways with therapeutic opportunities.Frontiers in immunology · 2025Review
- Simulated deep CT characterization of liver metastases with high-resolution filtered back projection reconstruction.Visual computing for industry, biomedicine, and art · 2024Article
- The value of computed tomography texture analysis in identifying chronic subdural hematoma patients with a good response to polytherapy.Scientific reports · 2024Article
- Preoperative CT and survival data for patients undergoing resection of colorectal liver metastases.Scientific data · 2024Article
- 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
- Role of radiomics in the diagnosis and treatment of gastrointestinal cancer.World journal of gastroenterology · 2022Review
- 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
- Radiomics in precision medicine for gastric cancer: opportunities and challenges.European radiology · 2022Review
- Association of CT-Based Delta Radiomics Biomarker With Progression-Free Survival in Patients With Colorectal Liver Metastases Undergo Chemotherapy.Frontiers in oncology · 2022Article
- Early Diagnosis of Liver Metastases from Colorectal Cancer through CT Radiomics and Formal Methods: A Pilot Study.Journal of clinical medicine · 2021Article
- Review
- Distinguishing pure histopathological growth patterns of colorectal liver metastases on CT using deep learning and radiomics: a pilot study.Clinical & experimental metastasis · 2021Article
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12 authors.
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Abstract
backgroundLiver metastases limit survival in colorectal cancer. Earlier detection of (occult) metastatic disease may benefit treatment and survival.
objectiveThe objective of this article is to evaluate the potential of whole-liver CT texture analysis of apparently disease-free liver parenchyma for discriminating between colorectal cancer (CRC) patients with and without hepatic metastases.
methodsThe primary staging CT examinations of 29 CRC patients were retrospectively analysed. Patients were divided into three groups: patients without liver metastases (n = 15), with synchronous liver metastases (n = 10) and metachronous liver metastases within 18 months following primary staging (n = 4). Whole-liver texture analysis was performed by delineation of the apparently non-diseased liver parenchyma (excluding metastases or other focal liver lesions) on portal phase images. Mean grey-level intensity (M), entropy (E) and uniformity (U) were derived with no filtration and different filter widths (0.5 = fine, 1.5 = medium, 2.5 = coarse).
resultsMean E1.5 and E2.5 for the whole liver in patients with synchronous metastases were significantly higher compared with the non-metastatic patients (p = 0.02 and p = 0.01). Mean U1.5 and U2.5 were significantly lower in the synchronous metastases group compared with the non-metastatic group (p = 0.04 and p = 0.02). Texture parameters for the metachronous metastases group were not significantly different from the non-metastatic group or synchronous metastases group (p > 0.05), although - similar to the synchronous metastases group - there was a subtle trend towards increased E1.5, E2.5 and decreased U1.5, U2.5 values. Areas under the ROC curve for the diagnosis of synchronous metastatic disease based on the texture parameters E1.5,2.5 and U1.5,2.5 ranged between 0.73 and 0.78.
conclusionTexture analysis of the apparently non-diseased liver holds promise to differentiate between CRC patients with and without metastatic liver disease. Further research is required to determine whether these findings may be used to benefit the prediction of metachronous liver disease.
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