ArticleFrontiers in oncology2021
Development of a Nomogram Combining Clinical Risk Factors and Dual-Energy Spectral CT Parameters for the Preoperative Prediction of Lymph Node Metastasis in Patients With Colorectal Cancer.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 21 citations in OpenAlex.
- Quantitative dual-energy computed tomography parameters as imaging biomarkers for assessing the histopathologic grade of colorectal cancer.Quantitative imaging in medicine and surgery · 2026Article
- A nomogram based on dual-layer spectral detector CT-derived 40-KeV virtual monoenergetic images and iodine maps for preoperative prediction of regional lymph node metastasis in colorectal cancer.BMC medical imaging · 2026Article
- Spectral CT imaging in colorectal cancer: current applications, limitations, and future perspectives.Insights into imaging · 2026Review
- Differentiating pulmonary embolism from contrast accumulation-induced beam hardening artifacts using dual-energy CT quantitative parameters.Quantitative imaging in medicine and surgery · 2025Article
- Dual-energy CT combined with histogram parameters in the assessment of perineural invasion in colorectal cancer.International journal of colorectal disease · 2025Article
- The preoperative prediction of lymph node metastasis of resectable pancreatic ductal adenocarcinoma using dual-layer spectral computed tomography.European radiology · 2025Article
- Spectral computed tomography parameters of primary tumors and lymph nodes for predicting tumor deposits in colorectal cancer.World journal of radiology · 2025Article
- Construction of a postoperative liver metastasis prediction model for colorectal cancer based on spectral CT imaging, CEA, and CA19-9.Translational cancer research · 2025Article
- Radiomics analysis of dual-layer spectral-detector CT-derived iodine maps for predicting tumor deposits in colorectal cancer.European radiology · 2025Article
- Prediction of lymph node metastasis in T1 colorectal cancer based on combination of body composition and vascular invasion.International journal of colorectal disease · 2024Article
- Dual-energy computed tomography in a multiparametric regression model for diagnosing lymph node metastases in pancreatic ductal adenocarcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Overexpression of circulating CD38+ NK cells in colorectal cancer was associated with lymph node metastasis and poor prognosis.Frontiers in oncology · 2024Article
- Article
- Predictive modeling based on tumor spectral CT parameters and clinical features for postoperative complications in patients undergoing colon resection for cancer.Insights into imaging · 2023Article
- Preoperative prediction of the lymphovascular tumor thrombus of colorectal cancer with the iodine concentrations from dual-energy spectral CT.BMC medical imaging · 2023Article
- Application of spectral CT in diagnosis, classification and prognostic monitoring of gastrointestinal cancers: progress, limitations and prospects.Frontiers in molecular biosciences · 2023Review
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Authors and funding
10 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aimed to develop a dual-energy spectral computed tomography (DESCT) nomogram that incorporated both clinical factors and DESCT parameters for individual preoperative prediction of lymph node metastasis (LNM) in patients with colorectal cancer (CRC). MATERIAL AND
methodsWe retrospectively reviewed 167 pathologically confirmed patients with CRC who underwent enhanced DESCT preoperatively, and these patients were categorized into training (
resultsThe logistic regression analysis showed that carcinoembryonic antigen, carbohydrate antigen 199, pericolorectal fat invasion, ICAP, ICVP, and Eff-ZVP were independent predictors in the predictive model. Based on these predictors, a quantitative nomogram was developed to predict individual LNM probability. The area under the curve (AUC) values of the nomogram were 0.876 in the training cohort and 0.852 in the validation cohort, respectively. DCA showed that our nomogram has outstanding clinical utility.
conclusionsThis study presents a clinical nomogram that incorporates clinical factors and DESCT parameters and can potentially be used as a clinical tool for individual preoperative prediction of LNM in patients with CRC.
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