A comparative analysis of diffusion-weighted imaging and ultrasound in thyroid nodules

Role of advanced MRI sequences for thyroid lesions assessment. A narrative review

Despite not being the first imaging modality for thyroid gland assessment, Magnetic Resonance Imaging (MRI), thanks to its optimal tissue contrast and spatial resolution, has provided some advancements in detecting and characterizing thyroid abnormalities. Recent research has been focused on improving MRI sequences and employing advanced techniques for a more comprehensive understanding of thyroid pathology. Although not yet standard practice, advanced MRI sequences have shown high accuracy in preliminary studies, correlating well with histopathological results. They particularly show promise in determining malignancy risk in thyroid lesions, which may reduce the need for invasive procedures like biopsies. In this line, functional MRI sequences like Diffusion Weighted Imaging (DWI), Dynamic Contrast-Enhanced MRI (DCE-MRI), and Arterial Spin Labeling (ASL) have demonstrated their potential usefulness in evaluating both diffuse thyroid conditions and focal lesions. Multicompartmental DWI models, such as Intravoxel Incoherent Motion (IVIM) and Diffusion Kurtosis Imaging (DKI), and novel methods like Amide Proton Transfer (APT) imaging or artificial intelligence (AI)-based analyses are being explored for their potential valuable insights into thyroid diseases. This manuscript reviews the critical physical principles and technical requirements for optimal functional MRI sequences of the thyroid and assesses the clinical utility of each technique. It also considers future prospects in the context of advanced MR thyroid imaging and analyzes the current role of advanced MRI sequences in routine practice.

Comparative analysis of the image quality and diagnostic performance of the zooming technique with diffusion-weighted imaging using different b-values for thyroid papillary carcinomas and benign nodules

Objective

To compare image quality and diagnostic performance using different b-values for the zooming technique with diffusion-weighted imaging (ZOOMit-DWI) in thyroid nodules.

Materials and methods

A total of 51 benign thyroid nodules and 50 thyroid papillary carcinomas were included. ZOOMit-DWI was performed with b-values of 0, 500, 1000, 1500 and 2000 s/mm2. The sharpness was evaluated as subjective index. The signal intensity ratio (SIR), signal-to-noise ratio (SNR) and apparent diffusion coefficient (ADC) were measured as objective indices. Pairwise comparisons were performed among the different b-value groups using the Friedman test. A receiver operating characteristic curve of the ADC value was used to evaluate diagnostic performance. The DeLong test was used to compare diagnostic effectiveness among the different b-value groups.

Results

In both the papillary carcinoma group (P = 0.670) and the benign nodule group (P = 0.185), the sharpness of nodules was similar between b-values of 1000 s/mm2and 1500 s/mm2. In the papillary carcinoma group, the SIRnodule was statistically higher in DWI images with a b-value of 1500 s/mm2than in DWI images with b-values of 500 s/mm2(P = 0.004), 1000 s/mm2(P = 0.002), and 2000 s/mm2(P = 0.003). When the b-values were 1500 s/mm2(P = 0.008) and 2000 s/mm2(P = 0.009), the SIRnodule significantly differed between the papillary carcinoma group and the benign nodule group. When b = 500 s/mm2, the ADC had an AUC of 0.888. When b = 1000 s/mm2, the ADC had an AUC of 0.881. When b = 1500 s/mm2, the ADC had an AUC of 0.896. When b = 2000 s/mm2, the ADC had an AUC of 0.871. The DeLong test showed comparable diagnostic effectiveness among the different b-value groups except for between b-values of 2000 s/mm2and 1500 s/mm2, with a b-value of 2000 s/mm2showing lower effectiveness.

Conclusion

This study suggests that 1500 s/mm2may be a suitable b-value to differentiate benign and malignant thyroid nodules in ZOOMit-DWI images, which yielded better image quality.

Multiplexed sensitivity-encoding versus single-shot echo-planar imaging: a comparative study for diffusion-weighted imaging of the thyroid lesions

PURPOSE

To compare multiplexed sensitivity-encoding diffusion-weighted magnetic resonance imaging (MUSE-DWI) and conventional DWI (cDWI) techniques in thyroid MRI.

MATERIALS AND METHODS

Nineteen patients who underwent thyroid MRI using both MUSE-DWI and cDWI at a 3.0 T MRI system were enrolled. Qualitative parameters (image quality, thyroid contour, and lesion conspicuity) and quantitative parameters (signal-to-noise ratio (SNR), lesion-to-thyroid contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC)) were compared between the two sequences. In addition, ADC values derived from MUSE-DWI and cDWI were separately compared between benign and malignant lesions.

RESULTS

MUSE-DWI outperformed cDWI in terms of image quality, thyroid contour, and lesion conspicuity. Significantly, higher signal-to-noise ratio (SNR) in both the thyroid and its lesion were found in MUSE-DWI than those in cDWI (both P < 0.05). The lesion-to-thyroid contrast-to-noise ratio (CNR) values were also significantly higher in MUSE-DWI than those in cDWI (P < 0.05). The apparent diffusion coefficient (ADC) of the thyroid in MUSE-DWI was significantly lower than that in cDWI (P < 0.05). The ADC of the lesion in MUSE-DWI was also significantly lower than that in cDWI (P < 0.05). In addition, ADC values derived from MUSE-DWI and cDWI were significantly higher in benign lesions than malignant lesions (P < 0.05).

CONCLUSION

Compared with cDWI, MUSE-DWI can improve the image quality, thyroid contour sharpness, lesion conspicuity, SNR in both the thyroid and its lesions, and enhancing the CNR between lesions and thyroid.

Gemstone Spectral CT Virtual Noncontrast Images and Iodine Maps for the Characterization of Thyroid Lesions and Distinguishing Thyroid Papillary Carcinoma from Nodular Goiter

BACKGROUND

Gemstone spectral contrast-enhanced CT with virtual noncontrast (VNC) images and iodine maps can potentially reduce the number of required CT scans for thyroid lesions. However, data regarding the clinical utility of VNC images and iodine maps in characterizing thyroid lesions and distinguishing thyroid papillary carcinoma from nodular goiter are still limited.

PURPOSE

To determine whether VNC images and iodine density could reliably aid in characterizing thyroid lesions and distinguishing thyroid papillary carcinoma from nodular goiter compared with true noncontrast (TNC) images.

METHODS

This retrospective study included patients with thyroid papillary carcinoma or nodular goiter who underwent TNC and contrast-enhanced gemstone spectral CT scans. The consistency of qualitative parameters, including intralesional calcification, necrosis, lesion boundary, thyroid edge interruption, and lymph node metastasis, between TNC and VNC images, was analyzed using the kappa statistic. TNC attenuation, VNC attenuation, absolute attenuation between TNC and VNC, and iodine density were compared between thyroid papillary carcinoma and nodular goiter by using Student's t-test. The diagnostic performance for distinguishing papillary carcinoma from nodular goiter was evaluated by using the area under the receiver operating characteristic curve (AUC) value, sensitivity, and specificity.

RESULTS

VNC and TNC imaging showed comparable performance in delineating calcification, necrosis, lesion boundary, thyroid edge interruption, and lymph node metastasis (all k > 0.75). Papillary carcinoma showed significantly lower absolute attenuation between VNC and TNC than nodular goiter (7.86 ± 6.74 vs. 13.43 ± 10.53, P=0.026), which was similarly observed for iodine density (31.45 ± 8.51 vs. 37.27 ± 10.34, P=0.016). The iodine density showed higher diagnostic performance (AUC = 0.727), accuracy (0.773 vs. 0.667), sensitivity (0.750 vs. 0.708), and specificity (0.786 vs. 0.643) than the absolute attenuation between TNC and VNC images (AUC = 0.683).

CONCLUSIONS

VNC imaging, a promising substitute for TNC imaging, has comparable diagnostic efficacy for reliably characterizing thyroid lesions. Iodine density could be valuable for distinguishing thyroid papillary carcinoma from nodular goiter.

Diagnostic accuracy of S-Detect in distinguishing benign and malignant thyroid nodules: A meta-analysis

Objectives

In this meta-analysis study, the main objective was to determine the accuracy of S-detect in effectively distinguishing malignant thyroid nodules from benign thyroid nodules.

Methods

We searched the PubMed, Cochrane Library, and CBM databases from inception to August 1, 2021. Meta-analysis was conducted using STATA version 14.0 and Meta-Disc version 1.4 softwares. We calculated summary statistics for sensitivity (Sen), specificity (Spe), positive and negative likelihood ratio (LR⁺/LR⁻), diagnostic odds ratio(DOR), and receiver operating characteristic (SROC) curves. Cochran’s Q-statistic and I² test were used to evaluate potential heterogeneity between studies. A sensitivity analysis was performed to evaluate the influence of single studies on the overall estimate. We also performed meta-regression analyses to investigate the potential sources of heterogeneity.

Results

In this study, a total of 17 studies meeting the requirements of the standard were used. The number of benign and malignant nodules analyzed and evaluated in this paper was 1595 and 1118 respectively. This paper mainly completes the required histological confirmation through s-detect. The pooled Sen and pooled Spe were 0.87 and 0.74, respectively, (95%CI = 0.84–0.89) and (95%CI = 0.66–0.81). Furthermore, the pooled LR⁺ and negative LR⁻ were determined to be 3.37 (95%CI = 2.53–4.50) and 0.18 (95%CI = 0.15–0.21), respectively. The experimental results showed that the pooled DOR of thyroid nodules was 18.83 (95% CI = 13.21–26.84). In addition, area under SROC curve was determined to be 0.89 (SE = 0.0124). It should be pointed out that there is no evidence of bias (i.e. t = 0.25, P = 0.80).

Conclusions

Through this meta-analysis, it can be seen that the accuracy of s-detect is relatively high for the effective distinction between malignant thyroid nodules and benign thyroid nodules.

Diagnostic accuracy of B-mode ultrasound, ultrasound elastography and diffusion weighted MRI in differentiation of thyroid nodules (prospective study)

Background

The incidence of the thyroid nodules and its detection is increasing rapidly. The most precise method for diagnosis of the nodules of the thyroid is FNAC. But, about 10–20% of specimens of FNAC are indeterminate and non-diagnostic. Therefore, there is a demand for another diagnostic method for evaluating thyroid nodules. Thyroid ultrasound elastography may improve the ability to differentiate malignant from benign thyroid nodules. Few articles were published about the results of DW MRI in thyroid nodules, with its results confirmed that malignant nodules have lower mean ADC values than benign nodules. This study aims to investigate and compare the accuracy of B-mode ultrasound, ultrasound elastography and diffusion-weighted MRI in characterization of the nodules of the thyroid.

Results

The study included 56 patients with thyroid nodules (36 benign and 20 malignant). Thyroid ultrasound, ultrasound elastography and DWI were done for all patients. Ultrasound-guided FNA Cytological examination (as the gold standard) was done for 48 patients and surgical histopathology was done to 8 patients with non-diagnostic FNAC. The results showed: TIRADS score had sensitivity 90%, specificity 77.8% and accuracy of 82.14%. The elastography score had sensitivity 80%, specificity 88.9% and accuracy 85.7%. The use of the strain ratio had 80% sensitivity, 94.4% specificity and 89.3% accuracy. DWI and ADC value had 100% sensitivity and 94.4% specificity and the accuracy was 96.4% for differentiating malignant from benign thyroid nodules. Multi-parametric analysis by TIRADS and ADC had 100% accuracy.

Conclusion

Ultrasound elastography add valuable data over ultrasound TIRADS. But, diffusion weighted MRI and ADC value has more accuracy in differentiating malignant from benign thyroid nodules. The best performance was achieved by the combination of ACR-TIRADS and ADC value.

Discrimination between malignant and benign thyroid tumors by diffusion-weighted imaging - A systematic review and meta analysis

PURPOSE

Magnetic resonance imaging is used to stage thyroid tumors. Diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) can be used to reflect tumor microstructure. Our aim was to compare ADC values of malignant and benign thyroid lesions based on a large sample.

METHODS

MEDLINE library, EMBASE and SCOPUS databases were screened for the associations between ADC values and thyroid lesions up to August 2021. The primary endpoint of the systematic review were ADC values of benign and malignant thyroid lesions. In total, 29 studies were suitable for the analysis and were included into the present study.

RESULTS

The included studies comprised a total of 2137 lesions, 1118 (52.3%) benign and 1019 (47.7%) malignant lesions. The pooled mean ADC value of the benign thyroid lesions was 1.88 × 10^-3 mm²/s [95% CI 1.77-2.0] and the pooled mean ADC value of malignant thyroid lesions was 1.15 × 10^-3 mm²/s [95% CI 1.04-1.25].

CONCLUSIONS

ADC can well discriminate benign and malignant thyroid tumors. Therefore, DWI should be implemented into the presurgical diagnostic work-up in clinical routine.

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.