Trial reportPloS one2013
Gastric cancer staging with dual energy spectral CT imaging.
Trial report in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
52 citing papers in PubMed, 102 citations in OpenAlex.
- Practical applications of photon-counting CT in oncology: an organ-based pictorial review.Insights into imaging · 2026Article
- Stomach and beyond: imaging the linitis plastica phenotype in signet ring cell carcinoma.Abdominal radiology (New York) · 2026Review
- Asian consensus on normothermic intraperitoneal and systemic treatment for gastric cancer with peritoneal metastasis.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2025Article
- A retrospective analysis of Gastric Cancer Lymph Nodes Based on Groups, Regions, and Stages.Surgery in practice and science · 2025Article
- Spectral CT-based nomogram for preoperative prediction of Lauren classification in locally advanced gastric cancer: a prospective study.European radiology · 2025Article
- Spectral CT vs. diffusion-weighted imaging for the quantitative prediction of pathologic response to neoadjuvant chemotherapy in locally advanced gastric cancer.European radiology · 2024Article
- Dual-Energy Computed Tomography in Urological Diseases: A Narrative Review.Journal of clinical medicine · 2024Review
- A nomogram based on dual-layer detector spectral computed tomography quantitative parameters and morphological quantitative indicator for distinguishing metastatic and nonmetastatic regional lymph nodes in pancreatic ductal adenocarcinoma.Quantitative imaging in medicine and surgery · 2024Article
- Nomogram based on dual-energy CT-derived extracellular volume fraction for the prediction of microsatellite instability status in gastric cancer.Frontiers in oncology · 2024Article
- Preoperative diagnosis of metastatic lymph nodes by CT-histopathologic matching analysis in gastric adenocarcinoma using dual-layer spectral detector CT.European radiology · 2023Article
- Preoperative prediction of Lauren classification in gastric cancer: a radiomics model based on dual-energy CT iodine map.Insights into imaging · 2023Article
- Early stage gastric adenocarcinoma: clinical and molecular landscapes.Nature reviews. Clinical oncology · 2023Review
- Spectral CT-based nomogram for preoperative prediction of perineural invasion in locally advanced gastric cancer: a prospective study.European radiology · 2023Article
- DECT Numbers in Upper Abdominal Organs for Differential Diagnosis: A Feasibility Study.Tomography (Ann Arbor, Mich.) · 2022Article
- Dual-layer spectral detector computed tomography parameters can improve diagnostic efficiency of lung adenocarcinoma grading.Quantitative imaging in medicine and surgery · 2022Article
- Development and validation of a dual-energy CT-based model to estimate the malignant probability of distal gastric wall thickening.Journal of gastrointestinal oncology · 2022Article
- Prediction of epithelial-to-mesenchymal transition molecular subtype using CT in gastric cancer.European radiology · 2022Article
- Spectral CT for preoperative prediction of lymphovascular invasion in resectable gastric cancer: With external prospective validation.Frontiers in oncology · 2022Article
- Improving radiation physics, tumor visualisation, and treatment quantification in radiotherapy with spectral or dual-energy CT.Journal of applied clinical medical physics · 2022Review
- A prospective study of dual-energy computed tomography for differentiating metastatic and non-metastatic lymph nodes of colorectal cancer.Quantitative imaging in medicine and surgery · 2021Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo evaluate the clinical utility of dual energy spectral CT (DEsCT) in staging and characterizing gastric cancers. MATERIALS AND
methods96 patients suspected of gastric cancers underwent dual-phasic scans (arterial phase (AP) and portal venous phase (PP)) with DEsCT mode. Three types of images were reconstructed for analysis: conventional polychromatic images, material-decomposition images, and monochromatic image sets with photon energies from 40 to 140 keV. The polychromatic and monochromatic images were compared in TNM staging. The iodine concentrations in the lesions and lymph nodes were measured on the iodine-based material-decomposition images. These values were further normalized against that in aorta and the normalized iodine concentration (nIC) values were statistically compared. Results were correlated with pathological findings.
resultsThe overall accuracies for T, N and M staging were (81.2%, 80.0%, and 98.9%) and (73.9%, 75.0%, and 98.9%) determined with the monochromatic images and the conventional kVp images, respectively. The improvement of the accuracy in N-staging using the keV images was statistically significant (p<0.05). The nIC values between the differentiated and undifferentiated carcinoma and between metastatic and non-metastatic lymph nodes were significantly different both in AP (p = 0.02, respectively) and PP (p = 0.01, respectively). Among metastatic lymph nodes, nIC of the signet-ring cell carcinoma were significantly different from the adenocarcinoma (p = 0.02) and mucinous adenocarcinoma (p = 0.01) in PP.
conclusionThe monochromatic images obtained with DEsCT may be used to improve the N-staging accuracy. Quantitative iodine concentration measurements may be helpful for differentiating between differentiated and undifferentiated gastric carcinoma, and between metastatic and non-metastatic lymph nodes.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.