ArticleInsights into imaging2023
Radiomic signatures from T2W and DWI MRI are predictive of tumour hypoxia in colorectal liver metastases.
Article in Insights into imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Imaging of cancer of unknown primary: a systematic literature review of the past, present, and future.The British journal of radiology · 2025Pooled it
- Quality over quantity: biopsy-anchored CT radiogenomics models outperform all-lesion training in a multi-tumour cohort despite a smaller sample size.European radiology · 2026Article
- Liver metastases beyond classical imaging findings.Abdominal radiology (New York) · 2026Review
- T2* mapping in magnetic resonance imaging for stratifying the hypoxic microenvironment in pancreatic ductal adenocarcinoma: a preliminary study.Quantitative imaging in medicine and surgery · 2026Article
- Tumor morphology on CT radiomics is largely driven by the local anatomical environment, not the primary tumor type.European radiology experimental · 2026Article
- Multi-sequence MRI deep learning and habitat radiomics for predicting mismatch repair status and prognosis in colorectal liver metastasis: a multicenter study.La Radiologia medica · 2026Article
- Prognostic Factors in Colorectal Liver Metastases: An Exhaustive Review of the Literature and Future Prospectives.Cancers · 2025Review
- Use of Radiomics in Characterizing Tumor Hypoxia.International journal of molecular sciences · 2025Review
- Predictive value of combined DCE-MRI perfusion parameters and clinical features nomogram for microsatellite instability in colorectal cancer.Discover oncology · 2025Article
- ChatGPT as an effective tool for quality evaluation of radiomics research.European radiology · 2025Article
- Imaging features and correlation with short-term prognosis in laparoscopic radical resection of colorectal cancer.World journal of gastrointestinal surgery · 2025Article
- Exploratory high b value diffusion-weighted MR for quantitative differentiation of ileocecal inflammatory conditions and tumors.Insights into imaging · 2025Article
- Magnetic Resonance-Guided Cancer Therapy Radiomics and Machine Learning Models for Response Prediction.Tomography (Ann Arbor, Mich.) · 2024Review
- Non-invasive CT radiomic biomarkers predict microsatellite stability status in colorectal cancer: a multicenter validation study.European radiology experimental · 2024Article
- Machine Learning and Radiomics Analysis for Tumor Budding Prediction in Colorectal Liver Metastases Magnetic Resonance Imaging Assessment.Diagnostics (Basel, Switzerland) · 2024Article
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Authors and funding
15 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTumour hypoxia is a negative predictive and prognostic biomarker in colorectal cancer typically assessed by invasive sampling methods, which suffer from many shortcomings. This retrospective proof-of-principle study explores the potential of MRI-derived imaging markers in predicting tumour hypoxia non-invasively in patients with colorectal liver metastases (CLM).
methodsA single-centre cohort of 146 CLMs from 112 patients were segmented on preoperative T2-weighted (T2W) images and diffusion-weighted imaging (DWI). HIF-1 alpha immunohistochemical staining index (high/low) was used as a reference standard. Radiomic features were extracted, and machine learning approaches were implemented to predict the degree of histopathological tumour hypoxia.
resultsRadiomic signatures from DWI b200 (AUC = 0.79, 95% CI 0.61-0.93, p = 0.002) and ADC (AUC = 0.72, 95% CI 0.50-0.90, p = 0.019) were significantly predictive of tumour hypoxia. Morphological T2W TE75 (AUC = 0.64, 95% CI 0.42-0.82, p = 0.092) and functional DWI b0 (AUC = 0.66, 95% CI 0.46-0.84, p = 0.069) and b800 (AUC = 0.64, 95% CI 0.44-0.82, p = 0.071) images also provided predictive information. T2W TE300 (AUC = 0.57, 95% CI 0.33-0.78, p = 0.312) and b = 10 (AUC = 0.53, 95% CI 0.33-0.74, p = 0.415) images were not predictive of tumour hypoxia.
conclusionsT2W and DWI sequences encode information predictive of tumour hypoxia. Prospective multicentre studies could help develop and validate robust non-invasive hypoxia-detection algorithms. CRITICAL RELEVANCE STATEMENT: Hypoxia is a negative prognostic biomarker in colorectal cancer. Hypoxia is usually assessed by invasive sampling methods. This proof-of-principle retrospective study explores the role of AI-based MRI-derived imaging biomarkers in non-invasively predicting tumour hypoxia in patients with colorectal liver metastases (CLM).
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