ArticleEuropean radiology2023
Preoperative diagnosis of metastatic lymph nodes by CT-histopathologic matching analysis in gastric adenocarcinoma using dual-layer spectral detector CT.
Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.
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14 citing papers in PubMed, 17 citations in OpenAlex.
- Spectral CT-based habitat analysis for predicting pathologic response to neoadjuvant therapy in gastric cancer.European radiology · 2026Article
- Parameters of dual-layer spectral detector CT for differentiating pathological types of colorectal adenocarcinoma.Insights into imaging · 2026Article
- 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
- Research progress of the clinical application of dual-layer spectral computed tomography in gastrointestinal malignancies.World journal of radiology · 2026Review
- Dual-layer spectral detector computed tomography multiparameter machine learning model for prediction of lymph node metastases in esophageal squamous cell carcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- The significance of small lymph nodes on CT for advanced poorly cohesive gastric carcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Predictive value of multivariate models combining CT-based extracellular volume fraction with clinicopathological parameters for preoperative detection of occult lymph node metastasis in gastric cancer.Insights into imaging · 2025Article
- A comparative study of dual-layer spectral CT and 18F-FDG-PET/CT multi-quantitative parameters in the diagnosis of sentinel lymph nodes in breast cancer.Annals of nuclear medicine · 2025Article
- The clinical applications of dual-layer spectral detector CT in digestive system diseases.European radiology · 2025Review
- Electron density derived from dual-energy CT for predicting thrombolytic therapeutic efficacy in patients with pulmonary embolism.Japanese 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
- A quantitative model using multi-parameters in dual-energy CT to preoperatively predict serosal invasion in locally advanced gastric cancer.Insights into imaging · 2024Article
- Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2024Review
- Differentiating gastric schwannoma from gastric stromal tumor (≤5 cm) by histogram analysis based on iodine-based material decomposition images: a preliminary study.Frontiers in oncology · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
objectivesThere still remain challenges to accurate diagnosis of lymph node (LN) involvement in gastric cancer (GC) on conventional CT. This study evaluated the quantitative data derived from dual-layer spectral detector CT (DLCT) for preoperative diagnosis of metastatic LNs compared to conventional CT images.
methodsPatients with adenocarcinoma scheduled for gastrectomy were enrolled in this prospective study from July, 2021, to February, 2022. Regional LNs were labeled on preoperative DLCT. The LNs were located and matched using carbon nanoparticle solution during surgery according to their locations and anatomic landmarks on preoperative images. The matched LNs were randomly split into training and validation cohorts in a ratio of 2:1. The DLCT quantitative parameters in the training cohort were investigated using logistic regression models to identify independent predictors of metastatic LNs, and these predictors were subsequently applied to the validation cohort. Receiver operating characteristic curves were compared between the DLCT parameters and conventional CT images.
resultsFifty-five patients were included in the study, with 267 successfully matched LNs (90 metastatic, 177 nonmetastatic). Independent predictors included arterial phase CT attenuation on 70-keV images, venous phase electron density, and clustered feature. These combination predictors had areas under the curve (AUC) of 0.855 and 0.907 in the training and validation cohorts, respectively. Compared to conventional CT criteria alone, the model had higher AUC and accuracy (0.741 vs. 0.907, 75.28% vs. 87.64%; p < 0.01) for LN diagnosis.
conclusionIncorporating DLCT parameters improved preoperative diagnosis of LN metastasis in GC, increasing the accuracy of clinical N stage. CLINICAL RELEVANCE STATEMENT: Compared to conventional CT criteria, quantitative parameters from dual-layer spectral detector CT showed higher diagnostic efficacy for the preoperative diagnosis of lymph node metastases in gastric cancer, increasing the accuracy of clinical N stage. KEY POINTS: • Quantitative parameters from dual-layer spectral detector CT are useful for the preoperative diagnosis of lymph node metastases in gastric adenocarcinoma, increasing the accuracy of clinical N stage. • The values for metastatic lymph nodes are higher than those of nonmetastatic ones. The arterial phase of CT attenuation on 70-keV images, venous phase of electron density, and clustered feature independently predicted lymph node metastases. • Prediction model had area under the curve of 0.907, sensitivity of 81.82%, specificity of 91.07%, and accuracy of 87.64% for the preoperative diagnosis of lymph node metastasis.
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