ArticleEuropean radiology2023
MRI-based multiregional radiomics for preoperative prediction of tumor deposit and prognosis in resectable rectal cancer: a bicenter study.
Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.
- The accuracy of radiomics in diagnosing tumor deposits and perineural invasion in rectal cancer: a systematic review and meta-analysis.Frontiers in oncology · 2024Pooled it
- Prognostic prediction model for rectal cancer based on CMS subtype indicators and SHAP-based interpretable analysis.Abdominal radiology (New York) · 2026Article
- Preoperative identification of tumor deposits in rectal cancer using a transformer-based multimodal fusion model: a multicenter retrospective study.BMC medical imaging · 2026Article
- MRI-based multiregional radiomics for pretreatment prediction of pathologic complete response to neoadjuvant chemoradiation therapy in locally advanced rectal cancer: a bicenter study.Abdominal radiology (New York) · 2026Article
- Multicenter peritumoral radiomics in oncology: advances, challenges, and future directions.Radiation oncology (London, England) · 2026Review
- MRI-derived radiomics for risk stratification of tumor deposits in rectal cancer: a dual-center study.Insights into imaging · 2026Article
- Interpretable habitat radiomics model based on multi-sequence MRI for risk prediction of metachronous liver metastasis in rectal cancer: a multicenter study.Japanese journal of radiology · 2026Article
- MRI-Based Morphological Features as Predictors of Clinical Outcomes in Locally Advanced Rectal Cancer Treated with Neoadjuvant Chemoradiotherapy: Insights from a Single-Institution Experience.Journal of clinical medicine · 2026Article
- Research Progress of MRI-based Radiomics in Rectal CancerCurrent medical imaging · 2026Review
- Prognostic value of tumor deposits and their different response to neoadjuvant therapy in locally advanced rectal cancer.PloS one · 2026Article
- Research progress in multimodal radiomics of rectal cancer tumors and peritumoral regions in MRI.Abdominal radiology (New York) · 2025Review
- A novel pN stage prediction model for resectable rectal adenocarcinoma based on preoperative MRI features and multiregional apparent diffusion coefficients.European radiology · 2025Article
- Enhancing the role of MRI in rectal cancer: advances from staging to prognosis prediction.European radiology · 2025Review
- A novel MRI-based habitat analysis and deep learning for predicting perineural invasion in prostate cancer: a two-center study.BMC cancer · 2025Article
- Dual-energy CT quantitative parameters for prediction of prognosis in patients with resectable rectal cancer.European radiology · 2025Article
- Peritumoral and intratumoral magnetic resonance imaging-based radiomics of brain metastases for predicting the response to EGFR-tyrosine kinase inhibitors in metastatic non-small cell lung cancer.Quantitative imaging in medicine and surgery · 2025Article
- Preoperative MRI-based radiomics analysis of intra- and peritumoral regions for predicting CD3 expression in early cervical cancer.Scientific reports · 2025Article
- Predictive value of models based on MRI radiomics and clinical indicators for lymphovascular space invasion in endometrial cancer.BMC cancer · 2025Article
- Spectral computed tomography parameters of primary tumors and lymph nodes for predicting tumor deposits in colorectal cancer.World journal of radiology · 2025Article
- DCE-MRI quantitative analysis and MRI-based radiomics for predicting the early efficacy of microwave ablation in lung cancers.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
objectiveTo build T2WI-based multiregional radiomics for predicting tumor deposit (TD) and prognosis in patients with resectable rectal cancer. MATERIALS AND
methodsA total of 208 patients with pathologically confirmed rectal cancer from two hospitals were prospectively enrolled. Intra- and peritumoral features were extracted separately from T2WI images and the least absolute shrinkage and selection operator was used to screen the most valuable radiomics features. Clinical-radiomics nomogram was developed by radiomics signatures and the most predictive clinical parameters. Prognostic model for 3-year recurrence-free survival (RFS) was constructed using univariate and multivariate Cox analysis.
resultsFor TD, the area under the receiver operating characteristic curve (AUC) for intratumoral radiomics model was 0.956, 0.823, and 0.860 in the training cohort, test cohort, and external validation cohort, respectively. AUC for the peritumoral radiomics model was 0.929, 0.906, and 0.773 in the training cohort, test cohort, and external validation cohort, respectively. The AUC for combined intra- and peritumoral radiomics model was 0.976, 0.918, and 0.874 in the training cohort, test cohort, and external validation cohort, respectively. The AUC for clinical-radiomics nomogram was 0.989, 0.777, and 0.870 in the training cohort, test cohort, and external validation cohort, respectively. The prognostic model constructed by combining intra- and peritumoral radiomics signature score (radscore)-based TD and MRI-reported lymph nodes metastasis (LNM) indicated good performance for predicting 3-year RFS, with AUC of 0.824, 0.865, and 0.738 in the training cohort, test cohort and external validation cohort, respectively.
conclusionCombined intra- and peritumoral radiomics model showed good performance for predicting TD. Combining intra- and peritumoral radscore-based TD and MRI-reported LNM indicated the recurrence risk. CLINICAL RELEVANCE STATEMENT: Combined intra- and peritumoral radiomics model could help accurately predict tumor deposits. Combining this predictive model-based tumor deposits with MRI-reported lymph node metastasis was associated with relapse risk of rectal cancer after surgery. KEY POINTS: • Combined intra- and peritumoral radiomics model provided better diagnostic performance than that of intratumoral and peritumoral radiomics model alone for predicting TD in rectal cancer. • The predictive performance of the clinical-radiomics nomogram was not improved compared with the combined intra- and peritumoral radiomics model for predicting TD. • The prognostic model constructed by combining intra- and peritumoral radscore-based TD and MRI-reported LNM showed good performance for assessing 3-year RFS.
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