# Predictive Value of Arterial Enhancement Fraction Derived from Dual-Layer Spectral Computed Tomography for Thyroid Microcarcinoma

## TL;DR

This study shows that a CT-based measure called arterial enhancement fraction (AEFD) can help identify thyroid cancer in small nodules and reduce unnecessary biopsies.

## Contribution

AEFD from dual-layer spectral CT is shown to be a novel and effective tool for diagnosing thyroid microcarcinomas.

## Key findings

- AEFD and AEFS were significantly lower in malignant thyroid nodules compared to benign ones.
- AEFD outperformed other imaging features in diagnosing malignancy with higher sensitivity and specificity.
- Using AEFD reduced the need for unnecessary biopsies by 18.3% in the study cohort.

## Abstract

Background/Objectives: Accurately distinguishing malignancy in thyroid micronodules (≤10 mm) is crucial for clinical management, yet it is challenging due to the limitations of conventional ultrasonography-guided biopsy. This study aims to evaluate the predictive value of dual-layer spectral computed tomography (DSCT)-derived arterial enhancement fraction (AEF) in diagnosing thyroid microcarcinomas. Methods: In the study, 321 pathologically confirmed thyroid micronodules (benign = 131, malignant = 190) from Chongqing General Hospital underwent preoperative DSCT. Quantitative parameters of DSCT, including the normalized iodine concentration (NIC), normalized effective atomic number (NZeff), and slope of the spectral Hounsfield unit curve (λHU(40–100)), were assessed. Both single-energy CT (SECT)-derived AEF (AEFS) and DSCT-derived AEF (AEFD) were calculated. Conventional image features included microcalcifications and enhancement blurring. Correlation between AEFD and AEFS was determined using Spearman’s correlation coefficient. Diagnostic performance was evaluated by calculating the area under the curve (AUC) using receiver operating characteristic (ROC) analysis. Results: Malignant micronodules exhibited significantly lower AEFD (0.958 vs. 1.259, p < 0.001) and AEFS (0.964 vs. 1.436, p < 0.001) versus benign nodules. Arterial phase parameters—APλHU(40–100), APNIC, APNZeff—differed significantly between groups (all p < 0.001), whereas venous phase parameters (VPλHU(40–100), VPNIC, VPNZeff) showed no differences (all p > 0.05). Multivariate analysis revealed that λHU(40–100) as an independent predictor of malignancy, with an odds ratio (OR) of 0.600 (95% confidence interval (CI): 0.437–0.823; p = 0.002) and an AUC of 0.752 (95% CI: 0.698–0.806). A significant positive correlation was identified between AEFD and AEFS (r = 0.710; p < 0.001). For diagnosing malignancy, AEFD demonstrated superior overall performance (AUC: 0.794; sensitivity: 70.5%; specificity: 81.7%; accuracy: 75.1%) to AEFS (0.753; 71.1%; 74.0%; 72.3%), APλHU(40–100) (0.752; 68.9%; 75.6%; 71.7%), and calcification (0.573; 21.6%; 92.4%; 50.5%). Clinically, AEFD reduced the unnecessary biopsy rate to 18.3%, preventing 107 procedures in our cohort. Conclusions: AEFD and AEFS demonstrated strong correlation and comparable diagnostic performance in the evaluation of thyroid micronodules. Furthermore, AEFD showed favorable diagnostic efficacy compared to both spectral parameters and conventional imaging feature. More importantly, the application of AEFD significantly reduced unnecessary biopsy rates, highlighting its clinical value in optimizing patient management.