ArticleAnnals of gastroenterological surgery2025
Texture analysis of CT colonography to develop a novel imaging biomarker for the management of colorectal cancer.
Article in Annals of gastroenterological surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Clinical-Radiomics Signature Predicts Pathologic Complete Response After Neoadjuvant Therapy in Oesophageal Squamous Cell Carcinoma.Interdisciplinary cardiovascular and thoracic surgery · 2026Article
- Texture analysis of CT colonography to develop a novel imaging biomarker for the management of colorectal cancer.Annals of gastroenterological surgery · 2025Article
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Authors and funding
10 authors.
Funding
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Abstract
Background: Recent studies have focused on evaluating the biomarker value of textural features in radiological images. Our study investigated whether or not a texture analysis of computed tomographic colonography (CTC) images could be a novel biomarker for colorectal cancer (CRC). Methods: This retrospective study investigated 263 patients with CRC who underwent contrast-enhanced CTC (CE-CTC) before curative surgery between January 2014 and December 2017. Multiple texture analyses (fractal, histogram, and gray-level co-occurrence matrix [GLCM] texture analyses) were applied to CE-CTC (portal-venous phase), and fractal dimension (FD), skewness, kurtosis, entropy, and GLCM texture parameters, including GLCM-correlation, GLCM-autocorrelation, GLCM-entropy, and GLCM-homogeneity, of the tumor were calculated. These texture parameters were compared with pathological factors (tumor depth, lymph node metastasis, vascular invasion, and lymphatic invasion) and overall survival (OS). Results: Tumor depth was significantly associated with FD, kurtosis, entropy, GLCM-correlation, GLCM-autocorrelation, GLCM-entropy, and GLCM-homogeneity ( Conclusion: CE-CTC-derived texture parameters may be clinically useful biomarkers for managing CRC patients.
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