ArticleGland surgery2021
Dual-source dual-energy thin-section CT combined with small field of view technique for small lymph node in thyroid cancer: a retrospective diagnostic study.
Article in Gland surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Dual-source dual-energy CT and deep learning for equivocal lymph nodes on CT images for thyroid cancer.European radiology · 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
- Dual-Energy Computed Tomography in Detecting and Predicting Lymph Node Metastasis in Malignant Tumor Patients: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2024Review
- The diagnosis and management of small and indeterminate lymph nodes in papillary thyroid cancer: preoperatively and intraoperatively.Frontiers in endocrinology · 2024Review
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Abstract
backgroundTo evaluate the diagnostic performance of quantitative spectral parameters derived from dual-source dual-energy CT at small field of view (FOV) for small lymph node metastasis in thyroid cancer.
methodsThis was a retrospective diagnostic study. From 2016 to 2019, 280 patients with thyroid disease underwent thin-section dual-source dual-energy thyroid CT and thyroid surgery. The data of patients with lymph nodes having a short diameter of 2-6 mm was analyzed. The quantitative dual-energy CT parameters of targeted lymph nodes were measured, and all parameters between metastatic and non-metastatic lymph nodes were compared. These parameters were then fitted to univariable and multivariable binary logistic regression models. The diagnostic role of spectral parameters was analyzed by receiver operating characteristic (ROC) curves and compared with the McNemar test. Small FOV CT images and a mathematical model were used to judge the status of lymph nodes respectively, and then compared with the golden criterion-pathological diagnosis. The cut-off value of the model was 0.4419, with a sensitivity of 90.2% and a specificity of 92.7%.
resultsOf the 216 lymph nodes investigated in this study, 52.3% and 23.6% had a short diameter of 2-3 and 4 mm, respectively. Multiple quantitative CT parameters were significantly different between benign and malignant lymph nodes, and binary regression analysis was performed. The mathematical model was: p=ey/(1+ ey), y=-23.119+0.033× precontrast electron cloud density +0.076× arterial phase normalized iodine concentration +2.156× arterial phase normalized effective atomic number -0.540× venous phase slope of the spectral Hounsfield unit curve +1.676× venous phase iodine concentration. This parameter model had an AUC of 92%, with good discrimination and consistency, and the diagnostic accuracy was 90.3%. The diagnostic accuracy of the CT image model was 43.1%, and for lymph nodes with a short-diameter of 2-3 mm, the diagnostic accuracy was 22.1%.
conclusionsThe parameter model showed higher diagnostic accuracy than the CT image model for diagnosing small lymph node metastasis in thyroid cancer, and quantitative dual-energy CT parameters were very useful for small lymph nodes that were difficult to be diagnosed only on conventional CT images.
trial registrationThis study is retrospectively registered, and we have registered a prospective study (Registration number: ChiCTR2000035195; http://www.chictr.org.cn).
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