Thyroid nodules are common clinical findings in recent years, and the prevalence of thyroid nodules is 20% - 70% in the general population [1] [2] [3]. Autopsy results showed that thyroid nodules are present in about 50% of the population [1] [4] [5]. Recent statistics show that the incidence of thyroid diseases is rising rapidly in many countries, while mortality is relatively constant [2] [3] [6]. Currently, cytology is the gold standard for diagnosing thyroid nodules, but ultrasound-guided fine-needle aspiration (FNA) is invasive, with certain risks and limitations [7] [8]. Although most of the complications of FNA biopsy, including perithyroidal hemorrhage, and parenchyma edema, were reported to be mild and could be recovered within a few hours, the discomfort and the risk of tumor metastasis during aspiration should not be ignored [7] [8]. A non-invasive examination could reduce pain or discomfort or prevent the probability of cancer seeding along the track of the needle. Besides, it may reduce patients’ mental pressure by painlessly recognizing the relatively low probability of having malignant diseases, which may be beneficial to patients’ disease management and clinical results [9].

Conventional gray-scale ultrasonography (US) is widely used to detect thyroid nodules. It can estimate benign and malignant solid thyroid nodules based roughly on morphologic features, such as nodule shape, margin, size, and calcification [10]. However, we could not omit the relatively low interobserver reliability and the lack of convenient lexicon in US to characterize thyroid nodules. And US elastography, a new advance in US, might not be an ideal tool to differentiate the types of thyroid nodules either [11]. Single-energy computed tomography (SECT) can evaluate the size of nodules, but the correlation between the nodules size and the nature of nodules is unclear [12].

With the recent advance in dual-energy CT (DECT), dual-energy imaging is burgeoning in clinical practice. DECT provides information on material decomposition by simultaneously acquiring images at two different energy levels in one scan. It can quantify intrinsic attenuations related to different atomic numbers and tissue density in specific regions of interest (ROI) [13] - [18]. Evaluating thyroid nodules using DECT is a novel non-invasive technique. It can provide a quantitative measurement of iodine concentration, which may be related to the pathophysiological status of thyroid nodules [19] [20].

Several studies have attempted to evaluate this application [21] [22] [23]. However, due to the different techniques used, the value of relevant quantitative iodine parameters and the diagnostic accuracy were not determined, and it is worth exploring. Therefore, we conducted a meta-analysis to evaluate the diagnostic value of the quantitative DECT parameters in distinguishing malignant and benign thyroid nodules.

As far as we know, a few studies have attempted to explore the relationship between thyroid nodules and diverse quantitative parameters [12] [22] [23] [36] [39]. One of the previous effective methods using conventional single-energy CT is to evaluate the size of nodules to distinguish benign from malignant thyroid nodules quantitatively. But, the correlation between the size of nodules and the nature of nodules is not ideal [12]. Also, for non-contrast DECT images, Tomita et al. found that it is unfeasible to differentiate between benign and malignant thyroid nodules using material decomposition and attenuation slopes [39]. Interestingly, our meta-analysis found that quantitative DECT parameters have good diagnostic accuracy in evaluating benign and malignant thyroid nodules, especially using contrast-enhanced images.

The collection of IC, NIC, and λ_HU are relatively sufficient data at present. The diagnostic ability of these three parameters seems similar. The diagnostic efficiency of NIC (AUC = 0.85) is almost the same as that of IC (AUC = 0.84), and both of them are slightly higher than that of the λ_HU (AUC = 0.81). One possible reason might be that all these measurements could reflect specific element concentration in thyroid mass, and the injection of the contrast media increases the difference of iodine concentration between benign and malignant nodules. In addition, the NIC value means the normalizing IC value, which is obtained by taking both the IC of thyroid mass and the IC of ipsilateral common carotid artery into account. This process might reduce the effect of inconsistent scan delay between studies and improve the homogeneity.

Benign and malignant thyroid nodules differ in iodine uptake ability and tissue composition for the cytological and metabolic changes [21] [40] [41] [42]. Li et al. found follicular epithelial cells with abnormal formation in papillary carcinoma, while the follicular structure and iodine-uptake ability was normal in nodular goiters and adenomas [21]. Studies had also demonstrated that the expression of thyrocyte markers like sodium-iodide symporter (NIS) and thyroglobulin (TG) in thyroid cancer were less than those in benign lesions [41] [42] [43]. Among these, the decrease of follicular cells and iodine transporter on the cell membrane might closely correlate with the disfunction of uptake iodine. Based on our estimation, the NIC values of malignant nodules were significantly lower on contrast-enhanced CT images than that of benign nodules (p < 0.01), which may support the disfunction of iodine uptake in malignant thyroid nodules.

When x-ray passing through a material, its photon energy is absorbed proportionally. And the remaining energy is collected by CT detectors and will be converted to a specific signal, which finally represents the X-ray energy attenuation values on this material, the so-called Hounsfield units (HU) [17] [44]. The spectrum curve is, essentially, the plot of HU against various X-ray energy levels (generally within the range of 40 to 140 keV). In some instances, two materials (e.g., calcium and iodine) can exhibit the same HU due to the similar attenuation coefficients at a given energy level. However, the material’s attenuation coefficient depends primarily on the mass density, composition, and the photon energies interacting with the material. After measuring an additional attenuation at a second energy level, the HU’s change helps to differentiate between two materials [17]. The slope of spectrum curve (λ_HU) was used to depict the spectrum curve. Previous ex vivo study reported that the λ_HU measured in benign nodules (nodular goiters and follicular adenomas) was positive, whereas in malignant nodules (papillary carcinoma) λ_HU was negative [21]. But our included studies showed that all of the λ_HU were positive in the venous phase, which was inconsistent with the previous ex vivo findings. And the absolute value of λ_HU was larger in benign nodules than in malignant nodules according to our analysis.

As a previous study stated, different DECT data obtained by different DECT devices might have some heterogeneity, which requires caution when comparing various studies [45]. Our comprehensive study contains three kinds of DECT devices: five dual-energy gemstone spectral CTs, one dual-layer spectral CT, and two second-generation dual-source dual-energy CTs. However, our research found that the heterogeneity of NIC’s specificity was not significant, and the heterogeneity of NIC’s sensitivity was also acceptable, for it could be explained, to some extent, by the threshold effect. This evidence indicates that the measurement of NIC in the venous phase might be comparable between different CT machines.

Moreover, we did not perform the same estimation in the groups of IC and λ_HU due to the uninterpretable heterogeneity. The heterogeneity of IC and λ_HU groups may not mainly originate from the threshold effect but from other factors. For example, different imaging phases may cause considerable heterogeneity shown in the mean difference of diagnostic efficacy (I² = 73%, I² = 95% respectively). By meta-regression analysis of three parameters, however, the known covariates did not show a significant influence on the SDOR. One possibility might be that the heterogeneity is low. But it is more likely that the literature’s insufficiency makes it difficult to use the known variables to explain the heterogeneity in existing studies. Nevertheless, we should not ignore that the present analysis does not consider some important variables, such as ages, type of nodules, size of nodules, the timing of the contrast injection, and the trigger threshold of CT scan.

DECT has a good diagnostic accuracy in thyroid nodule evaluation. The normalized iodine quantification technique is comparable between different dual-energy CT machines in thyroid nodule assessment. Quantitative DECT parameter may be a potential tool to estimate thyroid nodules noninvasively, reducing the need for unnecessary examinations of nodules, the associated patient anxiety, and inconvenience. More extensive prospective design studies are necessary to further optimize the diagnostic efficacy of quantitative DECT parameters.

This study has some limitations. First, it has been pointed out that the incidence of thyroid cancer is increasing while thyroid nodules may be overdiagnosed, which could lead to overtreatment [6] [45]. We did not focus on whether we should add extra diagnostic methods like DECT to the thyroid examination, though it is still a matter of concern. Second, the thyroid is radiation sensitive. Presently, there are still some challenges in terms of radiation safety, though the radiation dose could be reduced by up to 50% in DECT [46]. Third, because the application of DECT is still developing and spreading, available literature data are limited, which leads to a relatively small number of studies meeting our inclusion criteria. And we did not estimate the combined diagnostic thresholds due to the heterogeneity among studies. Fourth, the category of thyroid nodules included in the study might need further subdivisions. Although various pathological types of nodules were collected in the paper, no study proposed to crosslink parameters and the specific types of thyroid nodules (e.g., suspicious malignant nodules in FNA) that might occur progressive events, such as nodules enlargement or tendency for lymph node metastasis. And it is worth noting that it may be challenging to accurately implement iodine value measurement for micro thyroid lesions (maximum diameter < 10 mm), due to the partial volume effect in CT imaging. Of the studies we included, only two studies contained nodules less than 10 mm [36] [37], which implies that the quantitative diagnosis of sub-centimeter nodules still requires further study. Fifth, in terms of data statistics, some data are provided in the form of median and quartile but not mean and stand deviation [36]. So we estimated some data by combining median and quartile with original data size [47] [48], which may bring into errors when estimating the mean and standard deviation.

This research was supported by the National Natural Science Foundation of China: 21317241, 81971672, Key Program of Natural Science Foundation of Guangdong Province of China: 2018B0303110011, Guangzhou Key Laboratory of Molecular and Functional Imaging for Clinical Translation: 201905010003, the Fundamental Research Funds for the Central Universities: 21620308, 21620101, and the Engineering Research Center of Medical Imaging Artificial Intelligence for Precision Diagnosis and Treatment, Guangdong Province.

The authors declare no conflicts of interest regarding the publication of this paper.

Ye, K.L., Kuang, Y.Y., Liang, J.Y., Xu, X., Shi, C.Z., Cheng, Q.Q., Jiang, Z.J., Xiang, Z.Y. and Luo, L.P. (2021) Diagnostic Value of Dual-Energy CT in Differentiating Malignant and Benign Thyroid Nodules: A Systematic Review and Meta-Analysis. Journal of Biosciences and Medicines, 9, 54-76. https://doi.org/10.4236/jbm.2021.94005

The following are available online, Full search strategy, TableS1: diagnostic performance of DECT parameters, TableS2: PRISMA-DTA checklist, TableS3: PRISMA-DTA for Abstracts Checklist.

Full search strategy in PubMed

1# DECT

2# dual-energy CT

3# dual-energy computed tomography

4# thyroid

5# 1# OR 2# OR 3#

6# 4# AND 5#

OR:

(((DECT) OR (dual-energy CT)) OR (dual-energy computed tomography)) AND (thyroid)

Full search strategy in Web of Science

TS = (DECTOR dual-energy CT OR dual-energy computed tomography) AND TS = thyroid

Full search strategy in Embase

(DECT OR (“dual energy” AND CT) OR (“dual energy” AND computed AND tomography)) AND thyroid

Abbreviations: λ_HU, Slope of spectrum curve; NIC, normalized iodine concentration; IC, iodine concentration; TP, true positive; FP, false positive; FN, false negative; TN, true negative.