Observational studyWorld journal of gastroenterology2020
Prediction of different stages of rectal cancer: Texture analysis based on diffusion-weighted images and apparent diffusion coefficient maps.
Observational study in World journal of gastroenterology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Response prediction of neoadjuvant chemoradiation therapy in locally advanced rectal cancer using CT-based fractal dimension analysis.European radiology · 2022Trial
- Preoperative prediction of KRAS mutation in rectal cancer using a combined T2-weighted imaging radiomics and volumetric apparent diffusion coefficient histogram model.Abdominal radiology (New York) · 2026Article
- Fusion of MRI-radiomics and clinical features to improve pathological T-stage prediction of rectal cancer: a multicenter study.BMC cancer · 2026Article
- The clinical value of applying diffusion-weighted imaging combined with T2-weighted imaging to assess diagnostic performance of muscularis propria invasion in mid-to-high rectal cancer.Abdominal radiology (New York) · 2025Review
- The apparent diffusion coefficient as a biomarker in the diagnosis of cervical cancer and the assessment of therapeutic response to chemoradiation therapy.Frontiers in oncology · 2025Article
- The Role of Predictive and Prognostic MRI-Based Biomarkers in the Era of Total Neoadjuvant Treatment in Rectal Cancer.Cancers · 2024Review
- Exploring the value of multiple preprocessors and classifiers in constructing models for predicting microsatellite instability status in colorectal cancer.Scientific reports · 2024Article
- Multiparametric MRI-based radiomic model for predicting lymph node metastasis after neoadjuvant chemoradiotherapy in locally advanced rectal cancer.Insights into imaging · 2024Article
- A nomogram based on MRI radiomics features of mesorectal fat for diagnosing T2- and T3-stage rectal cancer.Abdominal radiology (New York) · 2024Article
- A nomogram based on MRI radiomics features of mesorectal fat for diagnosing T2- and T3-stage rectal cancer.Abdominal radiology (New York) · 2024Article
- Assessment of chemotherapy resistance changes in human colorectal cancer xenografts in rats based on MRI histogram features.Frontiers in oncology · 2024Article
- Significance of apparent diffusion coefficient in diagnosis of rectal carcinoma.Frontiers in oncology · 2024Article
- Investigating the Feasibility of Predicting KRAS Status, Tumor Staging, and Extramural Venous Invasion in Colorectal Cancer Using Inter-Platform Magnetic Resonance Imaging Radiomic Features.Diagnostics (Basel, Switzerland) · 2023Article
- Diagnostic performance of texture analysis in the differential diagnosis of perianal fistulising Crohn's disease and glandular anal fistula.World journal of gastrointestinal surgery · 2023Article
- Texture analysis of SPECT myocardial perfusion provides prognostic value for dilated cardiomyopathy.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Article
- Artificial intelligence and radiomics in magnetic resonance imaging of rectal cancer: a review.Exploration of targeted anti-tumor therapy · 2023Review
- Machine learning based gray-level co-occurrence matrix early warning system enables accurate detection of colorectal cancer pelvic bone metastases on MRI.Frontiers in oncology · 2023Article
- 2'-Fucosyllactose Suppresses Angiogenesis and Alleviates Toxic Effects of 5-Fu in a HCT116 Colon Tumor-Bearing Model.Molecules (Basel, Switzerland) · 2022Article
- Article
- Lymph Nodes Evaluation in Rectal Cancer: Where Do We Stand and Future Perspective.Journal of clinical medicine · 2022Review
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
backgroundIt is evident that an accurate evaluation of T and N stage rectal cancer is essential for treatment planning. It has not been extensively investigated whether texture features derived from diffusion-weighted imaging (DWI) images and apparent diffusion coefficient (ADC) maps are associated with the extent of local invasion (pathological stage T1-2
aimTo predict different stages of rectal cancer using texture analysis based on DWI images and ADC maps.
methodsOne hundred and fifteen patients with pathologically proven rectal cancer, who underwent preoperative magnetic resonance imaging, including DWI, were enrolled, retrospectively. The ADC measurements (ADC
resultsDissimilarity, sum average, information correlation and run-length nonuniformity from DWI
conclusionTexture features extracted from DWI images and ADC maps are useful clues for predicting pathological T and N stages in rectal cancer.
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