ArticleCancer imaging : the official publication of the International Cancer Imaging Society2023
Nomogram based on spectral CT quantitative parameters and typical radiological features for distinguishing benign from malignant thyroid micro-nodules.
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
- The value of dual-layer detector spectral CT multiparameter imaging in distinguishing between benign lesions and carcinomas of the larynx and hypopharynx.Quantitative imaging in medicine and surgery · 2026Article
- The influence of fine-needle aspiration on dual-layer detector spectral CT parameters of papillary thyroid carcinoma: a propensity-match analysis.BMC medical imaging · 2026Article
- Optimized dual-source dual-energy computed tomography nomogram model integrating background normalization improves solid thyroid nodules diagnosis.Gland surgery · 2026Article
- Development and validation of a multimodal predictive model based on clinical, biochemical, and quantitative dual-energy CT parameters: for predicting the benignity and malignancy of thyroid nodules.Frontiers in endocrinology · 2026Article
- Precision imaging biomarkers for gout: artifact-specific spectral CT parameters for personalized differentiation of tophi in a prospective study.Therapeutic advances in musculoskeletal disease · 2026Article
- Prediction of thyroid function based on CT radiomics: a two-center study.Quantitative imaging in medicine and surgery · 2025Article
- Article
- Machine learning model incorporating spectral CT quantitative parameters and clinical characteristics for differentiation of benign and malignant thyroid nodules.BMC medical imaging · 2025Article
- Arterial Enhancement Fraction-Spectral CT-Based Model as Part of Prediction Model in BRAFDiagnostics (Basel, Switzerland) · 2025Article
- Predictive Value of Arterial Enhancement Fraction Derived from Dual-Layer Spectral Computed Tomography for Thyroid Microcarcinoma.Diagnostics (Basel, Switzerland) · 2025Article
- The value of machine learning based on spectral CT quantitative parameters in the distinguishing benign from malignant thyroid micro-nodules.BMC cancer · 2025Article
- Radiomics analysis of dual-layer spectral-detector CT-derived iodine maps for predicting tumor deposits in colorectal cancer.European radiology · 2025Article
- Differentiation of benign and malignant lesions in Bethesda III and IV thyroid nodules via dual-energy computed tomography quantitative parameters and morphologic features.Quantitative imaging in medicine and surgery · 2024Article
- 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
- Detection of malignant lesions in cytologically indeterminate thyroid nodules using a dual-layer spectral detector CT-clinical nomogram.Frontiers in oncology · 2024Article
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10 authors.
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Abstract
purposeTo analyse the predictive effect of a nomogram combining dual-layer spectral computed tomography (DSCT) quantitative parameters with typical radiological features in distinguishing benign micro-nodule from thyroid microcarcinoma (TMC).
methodsData from 342 instances with thyroid micro-nodules (≤1 cm) who underwent DSCT (benign group: n = 170; malignant group: n = 172) were reviewed. Typical radiological features including micro-calcification and enhanced blurring, and DSCT quantitative parameters including attenuation on virtual monoenergetic images (40 keV, 70 keV and 100 keV), the slope of the spectral HU curve (λHU), normalized iodine concentration (NIC), and normalized effective atomic number (NZeff) in the arterial phase (AP) and venous phase (VP), were measured and compared between the benign and malignant groups. The receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of significant quantitative DSCT parameters or the models combining DSCT parameters respectively and typical radiological features based on multivariate logistic regression (LR) analysis. A nomogram was developed using predictors with the highest diagnostic performance in the above model, as determined by multivariate LR analysis.
resultsThe DSCT parameter APλHU showed the greatest diagnostic efficiency in identifying patients with TMC, with an area under the ROC curve (AUC) of 0.829, a sensitivity and specificity of 0.738 and 0.753, respectively. Then, APλHU was combined with the two radiological features to construct the DSCT-Radiological nomogram, which had an AUC of 0.858, a sensitivity of 0.791 and a specificity of 0.800. The calibration curve of the nomogram demonstrated that the prediction result was in good agreement with the actual observation. The decision curve revealed that the nomogram can result in a greater net benefit than the all/none-intervention strategy for all threshold probabilities.
conclusionAs a valid and visual noninvasive prediction tool, the DSCT-Radiological nomogram incorporating DSCT quantitative parameters and radiological features shows favourable predictive efficiency for identifying benign and malignant thyroid micro-nodules.
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