Qualitative analysis of contrast-enhanced ultrasound in the diagnosis of small, TR3-5 benign and malignant thyroid nodules measuring ≤1 cm

Integrated use of contrast-enhanced and grey-scale ultrasound in assigning American College of Radiology Thyroid Imaging-Reporting and Data System scores for characterisation of thyroid nodules: A prospective observational study

Background

The advent and increased use of high-resolution ultrasonography has resulted in improved detection of thyroid nodules. Even with the use of various Thyroid Imaging-Reporting and Data System, accurate imaging diagnosis of malignant thyroid nodules has been suboptimal, which necessitated use of newer modalities like contrast-enhanced ultrasonography alone and in combination for this purpose. Although the combined use of various Thyroid Imaging-Reporting and Data System and contrast-enhanced ultrasonography has turned out to be accurate in many studies, the ideal way to integrate contrast-enhanced ultrasonography into the Thyroid Imaging-Reporting and Data System algorithm is under-investigated.

Purpose

To estimate and compare the diagnostic accuracy of American College of Radiology Thyroid Imaging-Reporting and Data System and contrast-enhanced ultrasonography in differentiating benign and malignant nodules alone and in combination. To estimate the diagnostic accuracy of contrast-enhanced ultrasonography in re-categorisation of Thyroid Imaging-Reporting and Data System 3 and Thyroid Imaging-Reporting and Data System 4 thyroid nodules.

Materials and methods

This was a prospective cohort study performed in a tertiary care university-based hospital for 3 years. Adult patients with clinical or previous sonographic diagnosis of thyroid nodules were selected. Each of the nodules were assessed using ultrasonography and categorised using American College of Radiology Thyroid Imaging-Reporting and Data System criteria. The lesion was then assessed for contrast-enhanced ultrasonography features. The final diagnosis of the nodules was made using fine needle aspiration cytology. The diagnostic accuracy in diagnosis of malignant thyroid nodules for each of the American College of Radiology Thyroid Imaging-Reporting and Data System and contrast-enhanced ultrasonography alone and in combination was assessed. The diagnostic accuracy of contrast-enhanced ultrasonography in diagnosis of malignant thyroid nodules categorised as Thyroid Imaging-Reporting and Data System 3 and Thyroid Imaging-Reporting and Data System 4 was also assessed.

Results

American College of Radiology Thyroid Imaging-Reporting and Data System had a sensitivity, specificity, negative predictive value, positive predictive value and diagnostic accuracy of 86.6%, 54.5%, 17.4%, 97.3% and 57.7%, respectively, in diagnosis of malignant thyroid nodules. Contrast-enhanced ultrasonography had a sensitivity, specificity, negative predictive value, positive predictive value and diagnostic accuracy of 86.6%, 95.4%, 67.9%, 98.4% and 94.4%, respectively, in diagnosis of malignant thyroid nodules. Contrast-enhanced ultrasonography had sensitivity, specificity, negative predictive value, positive predictive value and diagnostic accuracy of 93.3%, 100.0%, 100.0%, 99.2% and 99.3%, respectively, in re-categorisation of Thyroid Imaging-Reporting and Data System 3 and Thyroid Imaging-Reporting and Data System 4 nodules.

Conclusion

Contrast-enhanced ultrasonography can play a key role in diagnosis of malignant thyroid nodules which are categorised as indeterminate on grey-scale ultrasound.

Ultrasound-Based Micro-/Nanosystems for Biomedical Applications

Due to the intrinsic non-invasive nature, cost-effectiveness, high safety, and real-time capabilities, besides diagnostic imaging, ultrasound as a typical mechanical wave has been extensively developed as a physical tool for versatile biomedical applications. Especially, the prosperity of nanotechnology and nanomedicine invigorates the landscape of ultrasound-based medicine. The unprecedented surge in research enthusiasm and dedicated efforts have led to a mass of multifunctional micro-/nanosystems being applied in ultrasound biomedicine, facilitating precise diagnosis, effective treatment, and personalized theranostics. The effective deployment of versatile ultrasound-based micro-/nanosystems in biomedical applications is rooted in a profound understanding of the relationship among composition, structure, property, bioactivity, application, and performance. In this comprehensive review, we elaborate on the general principles regarding the design, synthesis, functionalization, and optimization of ultrasound-based micro-/nanosystems for abundant biomedical applications. In particular, recent advancements in ultrasound-based micro-/nanosystems for diagnostic imaging are meticulously summarized. Furthermore, we systematically elucidate state-of-the-art studies concerning recent progress in ultrasound-based micro-/nanosystems for therapeutic applications targeting various pathological abnormalities including cancer, bacterial infection, brain diseases, cardiovascular diseases, and metabolic diseases. Finally, we conclude and provide an outlook on this research field with an in-depth discussion of the challenges faced and future developments for further extensive clinical translation and application.

Differentiation of benign and malignant lesions in Bethesda III and IV thyroid nodules via dual-energy computed tomography quantitative parameters and morphologic features

Background

Thyroid nodules (TNs) cytologically defined as category Bethesda III and IV pose a major diagnostic challenge before surgery, demanding new methods to reduce unnecessary diagnostic thyroid lobectomies for patients with benign TNs. This study aimed to assess whether a model combining dual-energy computed tomography (DECT) quantitative parameters with morphologic features could reliably differentiate between benign and malignant lesions in Bethesda III and IV TNs.

Methods

Data from 77 patients scheduled for thyroid surgery for Bethesda III and IV TNs (malignant =48; benign =29) who underwent DECT scans were reviewed. DECT quantitative parameters including normalized iodine concentration (NIC), attenuation on the slope of spectral Hounsfield unit (HU) curve, and normalized effective atomic number (Zeff) were measured in the arterial phase (AP) and venous phase (VP). DECT quantitative parameters and morphologic features were compared between the malignant and benign cohorts. The receiver operating characteristic curve was performed to compare the performances of significant DECT quantitative parameters, morphologic features, or the models combining the DECT parameters, respectively, with morphologic features. A nomogram was constructed from the optimal performance model, and the performance was evaluated via the calibration curve and decision curve analysis.

Results

The areas under the receiver operating characteristic curve with 95% confidence interval (CI) of the NIC in the AP (AP-NIC), slope of spectral HU curve in the AP, and NZeff in the AP were 0.749 (95% CI: 0.641-0.857), 0.654 (95% CI: 0.530-0.778), and 0.722 (95% CI: 0.602-0.842), respectively. The model combining AP-NIC with enhanced blurring showed the highest diagnostic performance, with an area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of 0.808, 0.854, and 0.655, respectively; it was then used to construct a nomogram. The calibration curve showed that the discrepancy between the prediction of the nomogram and actual observations was less than 5%. The decision curve analysis indicated the nomogram had a positive net benefit in threshold risk ranges of 14% to 58% or 60% to 91% for malignant Bethesda III and IV TNs.

Conclusions

The model combining AP-NIC with enhanced blurring could reliably differentiate between benign and malignant lesions in Bethesda III and IV TNs.

Thyroid ultrasound and its ancillary techniques

Ultrasound (US) of the thyroid has been used as a diagnostic tool since the late 1960s. US is the most important imaging tool for diagnosing thyroid disease. In the majority of cases a correct diagnosis can already be made in synopsis of the sonographic together with clinical findings and basal thyroid hormone parameters. However, the characterization of thyroid nodules by US remains challenging. The introduction of Thyroid Imaging Reporting and Data Systems (TIRADSs) has improved diagnostic accuracy of thyroid cancer significantly. Newer techniques such as elastography, superb microvascular imaging (SMI), contrast enhanced ultrasound (CEUS) and multiparametric ultrasound (MPUS) expand diagnostic options and tools further. In addition, the use of artificial intelligence (AI) is a promising tool to improve and simplify diagnostics of thyroid nodules and there is evidence that AI can exceed the performance of humans. Combining different US techniques with the introduction of new software, the use of AI, FNB as well as molecular markers might pave the way for a completely new area of diagnostic accuracy in thyroid disease. Finally, interventional ultrasound using US-guided thermal ablation (TA) procedures are increasingly proposed as therapy options for benign as well as malignant thyroid diseases.

The value of quantitative and a new qualitative color pattern shear wave elastography for the differentiation of ACR TI-RADS 4 or 5 category thyroid nodules measuring ≤10 mm

Objective

This study aims to evaluate the diagnostic performance of quantitative shear wave elastography (SWE) and a new qualitative color pattern SWE for the differentiation of benign and malignant American College of Radiology Thyroid Imaging, Reporting, and Data System (ACR TI-RADS) 4 or 5 category thyroid nodules measuring ≤10 mm.

Materials and methods

From May 2020 to July 2022, a total of 237 patients with 270 thyroid nodules were enrolled, and conventional ultrasound and SWE examinations were performed for each patient. Each ACR TI-RADS 4 or 5 category thyroid nodule measuring ≤10 mm was evaluated by quantitative SWE and a new qualitative color pattern SWE. The diagnostic performance of quantitative SWE parameters, the new qualitative color pattern SWE, and the combination of SWE with ACR TI-RADS, respectively, for the differentiation of benign and malignant ACR TI-RADS 4 or 5 category thyroid nodules measuring ≤10 mm was evaluated and compared.

Results

Among 270 thyroid nodules in 237 patients, 72 (26.67%) thyroid nodules were benign and 198 (73.33%) thyroid nodules were malignant. The qualitative color pattern SWE showed better diagnostic performance than the quantitative SWE parameters. When combining the qualitative color pattern SWE with ACR TI-RADS scores, with the optimal cutoff value of the total points ≥8, the thyroid nodules were considered malignant. The sensitivity, specificity, accuracy, and AUC were 89.90%, 56.94%, 81.11%, and 0.820 (95% CI: 0.768-0.864), respectively. Compared with using qualitative color pattern SWE alone, the combination of qualitative color pattern SWE and ACR TI-RADS had better diagnostic performance, which was significantly different (p < 0.05).

Conclusion

The combination of qualitative SWE color patterns and ACR TI-RADS had high sensitivity and accuracy, which might be a convenient and useful method to differentiate benign and malignant ACR TI-RADS 4 or 5 category thyroid nodules measuring ≤10 mm. It would be helpful for the management of thyroid nodules and improving prognosis.

Diagnostic value of qualitative and quantitative parameters of contrast-enhanced ultrasound for differentiating differentiated thyroid carcinomas from benign nodules

Objective

To explore the diagnostic value of contrast-enhanced ultrasound (CEUS) of qualitative and quantitative parameters for differentiating differentiated thyroid cancers from benign nodules.

Method

A total of 290 thyroid nodules that were pathologically confirmed were enrolled in this study. The univariate analysis was performed for the clinical characteristics and CEUS qualitative and quantitative parameters of the inside and peripheral zone of nodules, including age, gender, nodule size, intensity of enhancement, homogeneity, wash-in and wash-out patterns, margin after CEUS, ring enhancement, peak intensity, sharpness, time to peak(TP), and area under the curve(AUC), and the meaningful indicators in the single-factor analysis were further included in multivariate logistic regression analysis.

Results

Multivariate analysis showed that there were significant differences in age (p=0.031), nodule size (p<0.001), heterogeneous enhancement (p<0.001), hypo-enhancement (p=0.001), unclear margin after CEUS(p=0.007), inside peak (p<0.001), and outside sharpness(p<0.001) between benign and malignant nodules. However, there were no significant differences in gender, ring enhancement, wash-in, wash-out, outside TP, outside AUC between benign and malignant thyroid nodules (P>0.05, for all).

Conclusion

CEUS might be useful in the differential diagnosis of differentiated thyroid cancers and benign nodules, which could provide a certain basis for clinical treatment.

Predicting Malignancy of Thyroid Micronodules: Radiomics Analysis Based on Two Types of Ultrasound Elastography Images

RATIONALE AND OBJECTIVES

To develop a multimodal ultrasound radiomics nomogram for accurate classification of thyroid micronodules.

MATERIALS AND METHODS

A retrospective study including 181 thyroid micronodules within 179 patients was conducted. Radiomics features were extracted from strain elastography (SE), shear wave elastography (SWE) and B-mode ultrasound (BMUS) images. Minimum redundancy maximum relevance and least absolute shrinkage and selection operator algorithms were used to select malignancy-related features. BMUS, SE, and SWE radiomics scores (Rad-scores) were then constructed. Multivariable logistic regression was conducted using radiomics signatures along with clinical data, and a nomogram was ultimately established. The calibration, discriminative, and clinical usefulness were considered to evaluate its performance. A clinical prediction model was also built using independent clinical risk factors for comparison.

RESULTS

An aspect ratio ≥ 1, mean elasticity index, BMUS Rad-score, SE Rad-score, and SWE Rad-score were identified as the independent predictors for predicting malignancy of thyroid micronodules by multivariable logistic regression. The radiomics nomogram based on these characteristics showed favorable calibration and discriminative capabilities (AUCs: 0.903 and 0.881 for training and validation cohorts, respectively), all outperforming clinical prediction model (AUCs: 0.791 and 0.626, respectively). The decision curve analysis also confirmed clinical usefulness of the nomogram. The significant improvement of net reclassification index and integrated discriminatory improvement indicated that multimodal ultrasound radiomics signatures might work as new imaging markers for classifying thyroid micronodules.

CONCLUSION

The nomogram combining multimodal ultrasound radiomics features and clinical factors has the potential to be used for accurate diagnosis of thyroid micronodules in the clinic.

Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis

Background

The performance in evaluating thyroid nodules on ultrasound varies across different risk stratification systems, leading to inconsistency and uncertainty regarding diagnostic sensitivity, specificity, and accuracy.

Objective

Comparing diagnostic performance of detecting thyroid cancer among distinct ultrasound risk stratification systems proposed in the last five years.

Evidence acquisition

Systematic search was conducted on PubMed, EMBASE, and Web of Science databases to find relevant research up to December 8, 2022, whose study contents contained elucidation of diagnostic performance of any one of the above ultrasound risk stratification systems (European Thyroid Imaging Reporting and Data System[Eu-TIRADS]; American College of Radiology TIRADS [ACR TIRADS]; Chinese version of TIRADS [C-TIRADS]; Computer-aided diagnosis system based on deep learning [S-Detect]). Based on golden diagnostic standard in histopathology and cytology, single meta-analysis was performed to obtain the optimal cut-off value for each system, and then network meta-analysis was conducted on the best risk stratification category in each system.

Evidence synthesis

This network meta-analysis included 88 studies with a total of 59,304 nodules. The most accurate risk category thresholds were TR5 for Eu-TIRADS, TR5 for ACR TIRADS, TR4b and above for C-TIRADS, and possible malignancy for S-Detect. At the best thresholds, sensitivity of these systems ranged from 68% to 82% and specificity ranged from 71% to 81%. It identified the highest sensitivity for C-TIRADS TR4b and the highest specificity for ACR TIRADS TR5. However, sensitivity for ACR TIRADS TR5 was the lowest. The diagnostic odds ratio (DOR) and area under curve (AUC) were ranked first in C-TIRADS.

Conclusion

Among four ultrasound risk stratification options, this systemic review preliminarily proved that C-TIRADS possessed favorable diagnostic performance for thyroid nodules.

Systematic review registration

https://www.crd.york.ac.uk/prospero, CRD42022382818.

Assessment of the statistical optimization strategies and clinical evaluation of an artificial intelligence-based automated diagnostic system for thyroid nodule screening

Background

Thyroid cancer is the most common endocrine cancer in the world. Accurately distinguishing between benign and malignant thyroid nodules is particularly important for the early diagnosis and treatment of thyroid cancer. This study aimed to investigate the best possible optimization strategies for an already-trained artificial intelligence (AI)-based automated diagnostic system for thyroid nodule screening and, in addition, to scrutinize the clinically relevant limitations using stratified analysis to better standardize the application in clinical workflows.

Methods

We retrospectively reviewed a total of 1,092 ultrasound images associated with 397 thyroid nodules collected from 287 patients between April 2019 and January 2021, applying postoperative pathology as the gold standard. We applied different statistical approaches, including averages, maximums, and percentiles, to estimate per-nodule-based malignancy scores from the malignancy scores per image predicted by AI-SONIC Thyroid v. 5.3.0.2 (Demetics Medical Technology Ltd., Hangzhou, China) system, and we assessed its diagnostic efficacy on nodules of different sizes or tumor types with per-nodule analysis using performance metrics.

Results

Of the 397 thyroid nodules, 272 thyroid nodules were overrepresented by malignant nodules according to the results of the surgical pathological examinations. Taking the median of the malignancy scores per image to estimate the nodule-based score with a cutoff value of 0.56 optimized for the means of sensitivity and specificity, the AI-based automated detection system demonstrated slightly lower sensitivity, significantly higher specificity (almost independent of nodule size), and similar accuracy to that of the senior radiologist. Both the AI system and the senior radiologist demonstrated higher sensitivity in diagnosing smaller nodules (≤25 mm) and comparable diagnostic performances for larger nodules. The mean diagnostic time per nodule of the AI system was 0.146 s, which was in sharp contrast to the 2.8 to 4.5 min of the radiologists.

Conclusions

Using our optimization strategy to achieve nodule-based diagnosis, the AI-SONIC Thyroid automated diagnostic system demonstrated an overall diagnostic accuracy equivalent to that of senior radiologists. Thus, it is expected that it can be used as a reliable auxiliary diagnostic method by radiologists for the screening and preoperative evaluation of malignant thyroid nodules.

Nomogram based on spectral CT quantitative parameters and typical radiological features for distinguishing benign from malignant thyroid micro-nodules

PURPOSE

To analyse the predictive effect of a nomogram combining dual-layer spectral computed tomography (DSCT) quantitative parameters with typical radiological features in distinguishing benign micro-nodule from thyroid microcarcinoma (TMC).

METHODS

Data from 342 instances with thyroid micro-nodules (≤1 cm) who underwent DSCT (benign group: n = 170; malignant group: n = 172) were reviewed. Typical radiological features including micro-calcification and enhanced blurring, and DSCT quantitative parameters including attenuation on virtual monoenergetic images (40 keV, 70 keV and 100 keV), the slope of the spectral HU curve (λHU), normalized iodine concentration (NIC), and normalized effective atomic number (NZeff) in the arterial phase (AP) and venous phase (VP), were measured and compared between the benign and malignant groups. The receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of significant quantitative DSCT parameters or the models combining DSCT parameters respectively and typical radiological features based on multivariate logistic regression (LR) analysis. A nomogram was developed using predictors with the highest diagnostic performance in the above model, as determined by multivariate LR analysis.

RESULTS

The DSCT parameter APλHU showed the greatest diagnostic efficiency in identifying patients with TMC, with an area under the ROC curve (AUC) of 0.829, a sensitivity and specificity of 0.738 and 0.753, respectively. Then, APλHU was combined with the two radiological features to construct the DSCT-Radiological nomogram, which had an AUC of 0.858, a sensitivity of 0.791 and a specificity of 0.800. The calibration curve of the nomogram demonstrated that the prediction result was in good agreement with the actual observation. The decision curve revealed that the nomogram can result in a greater net benefit than the all/none-intervention strategy for all threshold probabilities.

CONCLUSION

As a valid and visual noninvasive prediction tool, the DSCT-Radiological nomogram incorporating DSCT quantitative parameters and radiological features shows favourable predictive efficiency for identifying benign and malignant thyroid micro-nodules.

Contrast-enhanced ultrasound improves the potency of fine-needle aspiration in thyroid nodules with high inadequate risk

Background

This study aims to determine the clinical value of contrast enhanced ultrasound (CEUS) for fine-needle aspiration (FNA) of high inadequate risky thyroid nodules.

Methods

During April 2018 and April 2021, consecutive 3748 thyroid nodules underwent FNA were retrospectively analyzed. CEUS guided FNA (CEUS-FNA) was applied in 115 nodules with high inadequate risk in Lingnan Campus. Ten nodules underwent CEUS-FNA presented non-enhancing, and would be further analyzed independently. Other 105 partial or total enhancing nodules were included as CEUS-FNA group, and 210 nodules with high inadequate risk in Tianhe Campus were match as the US-FNA control group. FNA specimens were collected for liquid-based preparation. Cytological results were classified following the Bethesda System for Reporting Thyroid Cytopathology.

Results

The overall FNA specimen inadequate rate in our center was 6.6%. All of the ten non-enhancing nodules under CEUS have an inadequate result in cytopathological analyzes. The subsequent postoperative pathology and follow-up ultrasonography showed the non-enhancing nodules were benign or stable without further malignant features. Total specimen inadequate rate of high inadequate risk thyroid nodules in CEUS-FNA group was significantly lower than US-FNA group (6.7% vs. 16.7%, P = 0.014). Further stratified analyzed shown that FNA under US guidance, the inadequate rates in cystic, predominantly cystic, predominantly solid and solid sub-groups were 28.1%, 17.1%, 10.0% and 9.2% (P = 0.019). In contrast, the inadequate rates in cystic, predominantly cystic, predominantly solid and solid sub-groups were 7.4%, 6.7%, 5.6% and 6.7% (P = 0.996) in CEUS-FNA group.

Conclusions

CEUS can improve the specimen adequacy of FNA in high inadequate risk thyroid nodules by avoiding unnecessary FNAs of the non-enhancing nodules, and accurately locating the viable tissue and precise guidance in real-time. CEUS is a recommend modality for FNA guidance of high inadequate risk thyroid nodules.

Contrast-Enhanced Ultrasound: An Effective Method for Noninvasive Diagnosis of Mummified Thyroid Nodules

Mummified thyroid nodules are a special type of thyroid nodule, which is benign, but is often diagnosed as malignant by ultrasound. This study investigated the usefulness of contrast-enhanced ultrasound (CEUS) in the diagnosis of mummified nodules. 66 patients with mummified nodules were divided into two groups: a no-enhancement group and a low-enhancement group. 32 patients with papillary thyroid carcinoma (PTC) were recruited in control group. In the no-enhancement group, CEUS showed that there was no contrast agent entering the nodules, with or without a little dot enhancement or regular ring enhancement around the nodules. The low-enhancement group showed low enhancement inside nodules, which was similar to that in the PTC group. In semiquantitative time-intensity curve analyses, intensity maximum of the central area of nodules in the low-enhancement group was lower than that in the PTC group (P < 0.05) and time to peak of the central area of nodules in the low-enhancement group was lower than that in the PTC group (P < 0.05). The results demonstrate that CEUS could be used to effectively diagnose mummified nodules, obviating the need for patients to undergo invasive examination such as biopsy or even surgery.

Performance of Contrast-Enhanced Ultrasound in Thyroid Nodules: Review of Current State and Future Perspectives

Ultrasound has been established as a baseline imaging technique for thyroid nodules. The main advantage of adding CEUS is the ability to assess the sequence and intensity of vascular perfusion and hemodynamics in the thyroid nodule, thus providing real-time characterization of nodule features, considered a valuable new approach in the determination of benign vs. malignant nodules. Original studies, reviews and six meta-analyses were included in this article. A total of 624 studies were retrieved, and 107 were included in the study. As recognized for thyroid nodule malignancy risk stratification by US, for acceptable accuracy in malignancy a combination of several CEUS parameters should be applied: hypo-enhancement, heterogeneous, peripheral irregular enhancement in combination with internal enhancement patterns, and slow wash-in and wash-out curve lower than in normal thyroid tissue. In contrast, homogeneous, intense enhancement with smooth rim enhancement and "fast-in and slow-out" are indicative of the benignity of the thyroid nodule. Even though overlapping features require standardization, with further research, CEUS may achieve reliable performance in detecting or excluding thyroid cancer. It can also play an operative role in guiding ablation procedures of benign and malignant thyroid nodules and metastatic lymph nodes, and providing accurate follow-up imaging to assess treatment efficacy.

Diagnostic value of thyroid micronodules with high b-value diffusion weighted imaging: Comparative study with high-resolution ultrasound

PURPOSE

This study aims to compare the diagnostic performance of two imaging methods for thyroid nodules ≤1.0 cm and reduce unnecessary overdiagnosis.

METHODS

A retrospective study was conducted on 80 patients with pathologically confirmed solitary thyroid micronodules underwent both high-resolution ultrasound (HRUS) and High b-value (2000 s/mm²) diffusion weighted imaging (DWI). Intra- and interobserver agreement (Intraclass correlation coefficient) was followed by Kruskal-Wallis test to detect whether the quantitative apparent diffusion coefficient (ADC) and thyroid nodule subgroups were related. Cohen's kappa analysis was applied to assess the interobserver consistency of DWI and HRUS characteristics. The receiver operating characteristic curves were adopted for evaluating the diagnostic performance of thyroid malignancy. The sensitivity, specificity, and accuracy of the two imaging methods were compared using the McNemar's test and Kappa test.

RESULTS

A total of 80 patients were included, consisting of 43 malignant and 37 benign micronodules. The sensitivity, specificity and accuracy of DWI combined with rADC (ADCmin to ADCn ratio) for the diagnosis of thyroid micronodules were 83.7%, 89.2% and 86.3%, respectively. The area under the curve (AUC) was 0.91 (95% confidence interval [CI]: 0.84-0.97). The sensitivity, specificity and accuracy of HRUS diagnosis were 100%, 62.16% and 82.5%, respectively.

CONCLUSION

High b-value DWI is superior to HRUS for evaluating the diagnostic performance of solid thyroid micronodules. DWI and its ADC quantitative analysis could be added to the evaluation of thyroid micronodules to improve the specificity of diagnosis, reduce overdiagnosis and avoid unnecessary biopsies or surgeries.