- ISSN: 1573-4056
- E-ISSN: 1875-6603
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oa Initial Recurrence Risk Stratification of Papillary Thyroid Cancer based on Intratumoral and Peritumoral Dual Energy CT Radiomics
- Source: Current Medical Imaging, Volume 21, Issue 1, Jan 2025, E15734056402179
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- 23 Apr 2025
- 27 May 2025
- 21 Aug 2025
Abstract
This study aims to evaluate the potential of Dual-Energy Computed Tomography (DECT)-based radiomics in preoperative risk stratification for the prediction of initial recurrence in Papillary Thyroid Carcinoma (PTC).
The retrospective analysis included 236 PTC cases (165 in the training cohort, 71 in the validation cohort) collected between July 2020 and June 2021. Tumor segmentation was carried out in both intratumoral and peritumoral areas (1 mm inner and outer to the tumor boundary). Three region-specific rad-scores were developed (rad-score [VOIwhole], rad-score [VOIouter layer], and rad-score [VOIinner layer]), respectively. Three radiomics models incorporating these rad-scores and additional risk factors were compared to a clinical model alone. The optimal radiomics model was presented as a nomogram.
Rad-scores from peritumoral regions (VOIouter layer and VOIinner layer) outperformed the intratumoral rad-score (VOIwhole). All radiomics models surpassed the clinical model, with peritumoral-based models (radiomics models 2 and 3) outperforming the intratumoral-based model (radiomics model 1). The top-performing nomogram, which included tumor size, tumor site, and rad-score (VOIinner layer), achieved an Area Under the Curve (AUC) of 0.877 in the training cohort and 0.876 in the validation cohort. The nomogram demonstrated good calibration, clinical utility, and stability.
DECT-based intratumoral and peritumoral radiomics advance PTC initial recurrence risk prediction, providing clinical radiology with precise predictive tools. Further work is needed to refine the model and enhance its clinical application.
Radiomics analysis of DECT, particularly in peritumoral regions, offers valuable predictive information for assessing the risk of initial recurrence in PTC.
