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| The value of dual energy CT-based nomogram in predicting extraglandular invasion of papillary thyroid carcinoma |
| XIA Shuiwei, LIN Guihan, CHEN Weiyue, CHEN Chunmiao, YING Haifeng, JI Jiansong. |
| Department of Radiology, Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui 323000, China |
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| Cite this article: |
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XIA Shuiwei,LIN Guihan,CHEN Weiyue, et al. The value of dual energy CT-based nomogram in predicting extraglandular invasion of papillary thyroid carcinoma[J]. JOURNAL OF WEZHOU MEDICAL UNIVERSITY, 2023, 53(3): 221-226.
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Abstract Objective: To investigate the value of nomograms based on dual-energy CT in predicting extraglandular invasion (ETE) of papillary thyroid carcinoma (PTC) before surgery. Methods: A total of 252 patients with PTC confirmed by surgery and pathology in the Fifth Affiliated Hospital of Wenzhou Medical University from March 2017 to December 2021 were retrospectively collected, and were divided into ETE group (n=150) and non-ETE group (n=102) according to the results of pathological diagnosis. All patients were randomly divided into training group (n=176) and validation group (n=76) using a ratio of 7:3. All patients underwent preoperative dual-energy CT neck enhanced scan, and the standardized iodine concentration (NIC), slope of the spectral curve (λHU), and effective atomic number (Zeff) of the lesion in the arterial and venous phases were measured and calculated; conventional CT features including lesion location, longest diameter, presence or absence of calcification, and presence or absence of breakthrough capsule were analyzed. Independent risk factors for ETE were screened by univariate analysis and multivariate logistic regression analysis, and a joint model was constructed and a nomogram was drawn. Model performance and clinical value were assessed using area under receiver operating characteristic (ROC) curve (AUC), calibration curve, and decision curve analysis (DCA). Results: In the training set, there’s significant difference between the two groups (all P<0.05) in the tumor location and whether or not the capsule had broken through the capsule. The NIC, λHU and Zeff in the arterial phase and the Zeff in the venous phase of PTC in the ETE group were significantly higher than those in the non-ETE group (all P<0.05). Multivariate logistic regression analysis showed that ventral location of the lesion, breakthrough of the capsule under CT, NIC in the arterial phase, Zeff in the arterial phase, and Zeff in the venous phase were independent risk factors for predicting ETE in PTC. The AUCs of the constructed nomogram prediction model in the training and validation sets were 0.902 (0.859-0.946) and 0.892 (0.810-0.964), respectively. The calibration curve showed a good agreement between the actual value of the sample and the predicted probability of the model, and the DCA indicated that the clinical application value of the model was high. Conclusion: The nomogram based on dual-energy CT can provide a certain guiding value for non-invasive preoperative prediction of ETE in patients with PTC.
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Received: 06 November 2022
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