Predicion of initial recurrence risk in papillary thyroid carcinoma based on the multi-parametric analysis from dual-layer detector spectral CT / 中华放射学杂志

ABSTRACT

Objective:To investigate the value of multi-parametric analysis based on dual-layer detector spectral CT (DLCT) in predicting the initial recurrence risk for papillary thyroid carcinoma (PTC).Methods:From November 2021 to October 2022, 102 PTC patients confirmed by pathology were retrospectively collected at the First Affiliated Hospital of Nanjing Medical University in this cross-sectional study. There were 25 males and 77 females, with an age of (42±13) years old. The initial recurrence risk assessment for PTC patients was categorized into a low-risk group (75 cases) and an intermediate-high-risk group (27 cases). Clinical data, including age, gender, body mass index, history of nodular goiter, history of Hashimoto thyroiditis, and preoperative thyroid function, were collected. Tumor morphological features, including size, location, shape, aspect ratio, the degree of thyroid capsule contact, calcification, and cystic change, were evaluated. Quantitative DLCT parameters, including iodine concentration (IC), standardized iodine concentration (NIC), effective atomic number (Z eff), standardized effective atomic number (NZ eff), electronic density (ED), CT values under different energy levels (40-200 keV, 30 keV intervals) and slope of energy spectrum curve (λ HU) both in the arterial and venous phase were measured. The differences in clinical, morphological features, and spectral CT quantitative parameters between the two groups were compared using independent sample ttest, Mann-Whitney U test, or χ2 test. Multivariate logistic regression analyses were used to construct three models based on clinical and morphological features, quantitative DLCT parameters and their combination, respectively. The receiver operating characteristic curve was used to evaluate the predictive performance of these models for the initial recurrence risk of PTC patients, and the area under the curve (AUC) was compared using the DeLong test. Results:Significant differences were found in gender, lesion long diameter, lesion short diameter and calcification between the low-risk group and intermediate-high-risk groups ( P<0.05). The arterial phase IC, arterial phase Z eff, arterial phase λ HU, arterial phase CT 40 keV, venous phase NIC and venous phase NZ eff in intermediate-high-risk group were significantly lower than those in the low-risk group ( P<0.05). The logistic regression analysis revealed that the clinical model included gender ( OR=2.895, 95% CI 1.047-8.002, P=0.040) and lesion long diameter ( OR=1.142, 95% CI 1.042-1.251, P=0.004), with an AUC of 0.720, sensitivity of 63.0%, and specificity of 78.7% in predicting the initial recurrence risk of PTC patients. The DLCT quantitative parameter model included arterial phase IC ( OR=0.580, 95% CI 0.370-0.908, P=0.017), venous phase NIC ( OR=0.077, 95% CI 0.011-0.536, P=0.010), and venous phase NZ eff ( OR=0.002, 95% CI 0.001-0.103, P=0.009), with an AUC of 0.774, sensitivity of 71.9%, and specificity of 70.0%. The AUC of the combined model was 0.857, with a sensitivity of 74.1%, and specificity of 88.0%, outperforming the clinical model ( Z=2.92, P=0.004) and the DLCT quantitative parameter model ( Z=2.07, P=0.046). Conclusion:Multi-parametric analysis based on DLCT can help predict the initial recurrence risk for PTC, and combining it with clinical and morphological features, the predictive accuracy can be improved.