ArticleThe Journal of clinical endocrinology and metabolism2024
Prognostic Analysis of 131I Efficacy After Papillary Thyroid Carcinoma Surgery Based on CT Radiomics.
Article in The Journal of clinical endocrinology and metabolism, 2024. 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 6 papers.
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Who cites it
6 citing papers in PubMed.
- Article
- Decision-making value of a 1-cm tumor diameter cut-off for postoperativeAmerican journal of translational research · 2026Article
- Ultrasound radiomics for preoperative evaluation of Ki-67 proliferation index in papillary thyroid carcinoma.Frontiers in oncology · 2026Article
- Multifunctional Bismuth Nanoplatforms Augment Radioactive Iodine Therapy in Anaplastic Thyroid Cancer.International journal of nanomedicine · 2026Article
- Texture analysis combined with machine learning in radiographs of the knee joint: potential to identify tibial plateau occult fractures.Quantitative imaging in medicine and surgery · 2025Article
- Comprehensive analysis of the papillary thyroid carcinoma identifies CSGALNACT1 as a proliferation driver and prognostic biomarker.Frontiers in cell and developmental biology · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
Abstract
objectiveTo develop and validate a radiomics-clinical combined model combining preoperative computed tomography (CT) and clinical data from patients with papillary thyroid carcinoma (PTC) to predict the efficacy of initial postoperative 131I treatment.
methodsA total of 181 patients with PTC who received total thyroidectomy and initial 131I treatment were divided into training and testing sets (7:3 ratio). Univariate analysis and multivariate logistic regression were used to screen clinical factors affecting the therapeutic response to 131I treatment and construct a clinical model. Radiomics features extracted from preoperative CT images of PTCs were dimensionally reduced through recursive feature elimination and least absolute shrinkage and selection operator. Logistic regression was used to establish a radiomics model, and a radiomics-clinical combined model was developed by integrating the clinical model. The area under the curve (AUC), sensitivity, and specificity were used to evaluate the prediction performance of each model.
resultsMultivariate analysis revealed that pre-131I treatment serum thyroglobulin was an independent clinical risk factor affecting the efficacy of initial 131I treatment (P = .002), and the AUC, sensitivity, and specificity for predicting the efficacy of initial 131I treatment were 0.895, 0.899, and 0.816, respectively. After dimensionality reduction, 14 key CT radiomics features of PTCs were included. The established radiomics model predicted the efficacy of 131I treatment in the training and testing sets with AUCs of 0.825 and 0.809, sensitivities of 0.828 and 0.636, and specificities of 0.745 and 0.944, respectively. The combined model improved the AUC, sensitivity, and specificity in both sets.
conclusionThe preoperative CT-based radiomics model can effectively predict the efficacy of initial postoperative 131I treatment in patients with intermediate- or high-risk PTC, and the radiomics-clinical combined model exhibits better predictive performance.
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