ArticleFrontiers in oncology2022
A Dual-Energy CT Radiomics of the Regional Largest Short-Axis Lymph Node Can Improve the Prediction of Lymph Node Metastasis in Patients With Rectal Cancer.
Article in Frontiers in oncology, 2022. 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, 33 citations in OpenAlex.
- Quantifying the Long and Short Axes of the External Iliac Lymph Nodes Using Dual-Energy Computed Tomography: A Potential Diagnostic Approach for Periprosthetic Joint Infection - A Prospective Study.Infection and drug resistance · 2024Trial
- Dual-Layer Spectral CT for Locoregional Assessment of Rectal Cancer: A Comparison with MRI in a Pilot Study.Diagnostics (Basel, Switzerland) · 2026Article
- Article
- Radiomics' Role in Predicting Distant Metastases, Recurrence and Survival Outcome in Rectal Cancer: A Systematic Review.Cancers · 2026Review
- Quantitative parameters of dual-layer spectral CT for differentiating metastatic and non-metastatic lymph nodes in colorectal cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Spectral CT imaging in colorectal cancer: current applications, limitations, and future perspectives.Insights into imaging · 2026Review
- Diagnostic efficacy of dual-energy computed tomography-based fractal analysis for assessing extramural venous invasion/tumor deposits and peripheral nerve invasion in rectal cancer.Quantitative imaging in medicine and surgery · 2026Article
- Radiomics analysis of dual-energy CT-derived iodine maps for predicting histopathologic grading of pancreatic ductal adenocarcinoma: a two-center study.Frontiers in medicine · 2026Article
- Comparative accuracy of spectral computed tomography and conventional computed tomography in colorectal cancer staging.Frontiers in oncology · 2026Article
- Deep learning radiomics andTranslational lung cancer research · 2025Article
- Spectral computed tomography parameters of primary tumors and lymph nodes for predicting tumor deposits in colorectal cancer.World journal of radiology · 2025Article
- Development and validation of a CT-based radiomics nomogram for predicting cervical lymph node metastasis in papillary thyroid carcinoma.Cancer biomarkers : section A of Disease markers · 2025Article
- Diagnostic performance of Node-RADS score for mesorectal lymph node metastasis in rectal cancer.Abdominal radiology (New York) · 2025Article
- Radiomics analysis of dual-layer spectral-detector CT-derived iodine maps for predicting tumor deposits in colorectal cancer.European radiology · 2025Article
- Preoperative prediction of lymphovascular invasion and T-staging of rectal cancer via a dual-energy computed tomography iodine map: a feasibility study.Diagnostic and interventional radiology (Ankara, Turkey) · 2025Article
- Molecular Imaging Biomarkers for Early Cancer Detection: A Systematic Review of Emerging Technologies and Clinical Applications.Diagnostics (Basel, Switzerland) · 2024Review
- Magnetic resonance imaging-based lymph node radiomics for predicting the metastasis of evaluable lymph nodes in rectal cancer.World journal of gastrointestinal oncology · 2024Article
- A clinical-radiomics nomogram based on dual-layer spectral detector CT to predict cancer stage in pancreatic ductal adenocarcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2024Review
- Radiomics using CT images for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma: a multi-centric study.European radiology · 2024Article
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Authors and funding
15 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To explore the value of dual-energy computed tomography (DECT) radiomics of the regional largest short-axis lymph nodes for evaluating lymph node metastasis in patients with rectal cancer. Materials and Methods: One hundred forty-one patients with rectal cancer (58 in LNM+ group, 83 in LNM- group) who underwent preoperative total abdominal DECT were divided into a training group and testing group (7:3 ratio). After post-processing DECT venous phase images, 120kVp-like images and iodine (water) images were obtained. The highest-risk lymph nodes were identified, and their long-axis and short-axis diameter and DECT quantitative parameters were measured manually by two experienced radiologists who were blind to the postoperative pathological results. Four DECT parameters were analyzed: arterial phase (AP) normalized iodine concentration, AP normalized effective atomic number, the venous phase (VP) normalized iodine concentration, and the venous phase normalized effective atomic number. The carcinoembryonic antigen (CEA) levels were recorded one week before surgery. Radiomics features of the largest lymph nodes were extracted, standardized, and reduced before modeling. Radomics signatures of 120kVp-like images (Rad-signature Results: Eight hundred thirty-three features were extracted from 120kVp-like and iodine images, respectively. In testing group, the radiomics features based on 120kVp-like images showed the best diagnostic performance (AUC=0.922) compared to other predictors [CT morphological indicators (short-axis diameter (AUC=0.779, IDI=0.262) and long-axis diameter alone (AUC=0.714, IDI=0.329)), CEA alone (AUC=0.540, IDI=0.414), and normalized DECT parameters alone (AUC=0.504-0.718, IDI=0.290-0.476)]( Conclusion: Predictive model based on DECT and the largest short-axis diameter lymph nodes has the highest diagnostic value in predicting lymph node metastasis in patients with rectal cancer.
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