Utility of high b-value (2000 sec/mm2) DWI with RESOLVE in differentiating papillary thyroid carcinomas and papillary thyroid microcarcinomas from benign thyroid nodules

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.

Characterization of high-grade pineal region lesions: the usefulness of apparent diffusion coefficient volumetric values

BACKGROUND

High-grade pineal region tumors are rare and heterogeneous types of primary central nervous system neoplasms; radiological differential diagnosis is challenging but it is important because it has a therapeutic relevance.

PURPOSE

To discriminate among high-grade pineal region tumors by combining apparent diffusion coefficient (ADC) volumetric values and qualitative features in order to predict their histology.

MATERIAL AND METHODS

Twenty-two patients with high-grade pineal region tumors were assessed by qualitative and quantitative analysis. Margins, T2-weighted signal intensity, contrast enhancement, hemorrhage, calcifications, different volumetric ADC fractions (ADC_mean, ADC_max, ADC_min) were evaluated and were compared to the histopathologic findings (cell count and proliferation index).

RESULTS

Our qualitative imaging data showed that only margins were different among different tumors and each tumor type showed peculiar age onset. ADC_mean was found the best quantitative value to discriminate high-grade tumors of the pineal region. ADC_mean correlated with proliferation index but not with cell count. ADC_mean values were lower in tumors with higher proliferation rate and a significant difference in ADC_mean values were found between germinomas and pineoblastomas, between germinomas and papillary tumors and between papillary tumors and pineoblastomas. Moreover, the cut-off value of 0.865 × 10^-3 mm²/s for ADC_mean (ADC mean threshold value) could differentiate germinoma from pineoblastomas with the best combination of sensitivity and specificity.

CONCLUSION

The ADC_mean value measured on the whole tumor, reflecting tumor proliferative activity, may be a practical and non-invasive marker for predicting tumor histology in high-grade pineal region lesions and might be useful in preoperative assessment.

Single shot zonal oblique multislice SE-EPI diffusion-weighted imaging with low to ultra-high b-values for the differentiation of benign and malignant vertebral spinal fractures

Purpose

To investigate the diagnostic yield of low to ultra-high b-values for the differentiation of benign from malignant vertebral fractures using a state-of-the-art single-shot zonal-oblique-multislice spin-echo echo-planar diffusion-weighted imaging sequence (SShot ZOOM SE-EPI DWI).

Materials and Methods

66 patients (34 malignant, 32 benign) were examined on 1.5 T MR scanners. ADC maps were generated from b-values of 0,400; 0,1000 and 0,2000s/mm². ROIs were placed into the fracture of interest on ADC maps and trace images and into adjacent normal vertebral bodies on trace images. The ADC of fractures and the Signal-Intensity-Ratio (SIR) of fractures relative to normal vertebral bodies on trace images were considered quantitative metrics. The appearance of the fracture of interest was graded qualitatively as iso-, hypo-, or hyperintense relative to normal vertebrae.

Results

ADC achieved an area under the curve (AUC) of 0.785/0.698/0.592 for b = 0,400/0,1000/0,2000s/mm² ADC maps respectively. SIR achieved an AUC of 0.841/0.919/0.917 for b = 400/1000/2000s/mm² trace images respectively. In qualitative analyses, only b = 2000s/mm² trace images were diagnostically valuable (sensitivity:1, specificity:0.794). Machine learning models incorporating all qualitative and quantitative metrics achieved an AUC of 0.95/0.98/0.98 for b-values of 400/1000/2000s/mm² respectively. The model incorporating only qualitative metrics from b = 2000s/mm² achieved an AUC of 0.97.

Conclusion

By using quantitative and qualitative metrics from SShot ZOOM SE-EPI DWI, benign and malignant vertebral fractures can be differentiated with high diagnostic accuracy. Importantly qualitative analysis of ultra-high b-value images may suffice for differentiation as well.

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.

Diffusion-Weighted Imaging of the Head and Neck (Including Temporal Bone)

Diffusion techniques provide valuable information when performing head and neck imaging. This information can be used to detect the presence or absence of pathology, refine differential diagnosis, determine the location for biopsy, assess response to treatment, and prognosticate outcomes. For example, when certain technical factors are taken into consideration, diffusion techniques prove indispensable in assessing for residual cholesteatoma following middle ear surgery. In other scenarios, pretreatment apparent diffusion coefficient values may assist in prognosticating outcomes in laryngeal cancer and likelihood of response to radiation therapy. As diffusion techniques continue to advance, so too will its clinical utility.

Applying Amide Proton Transfer-Weighted Imaging (APTWI) to Distinguish Papillary Thyroid Carcinomas and Predominantly Solid Adenomatous Nodules: Comparison With Diffusion-Weighted Imaging

Background: Amide proton transfer-weighted (ATPw) imaging is a novel MRI technique that has been used to identify benign and malignant tumors. The present study evaluated the role of APTw imaging in differentiating papillary thyroid carcinoma from predominantly solid adenomatous nodule.

Methods: This study included 24 cases of solitary papillary thyroid carcinoma, and 20 cases of solid adenomatous nodules. Normal thyroid tissues were examined in 12 healthy subjects. The healthy subjects, eight cases of adenomatous nodule with cystic degeneration, and 12 cases of thyroid goiter, were only considered in the descriptive analysis, not included in our statistical analysis. The mean APTw value and the apparent diffusion coefficients (ADCs) of papillary thyroid carcinoma and solid adenomatous nodule were compared via a Mann-Whitney U test and receiver operating characteristic (ROC)-curve analyses.

Results: The adenomatous nodule (3.3 ± 1.3%) exhibited significantly higher APTw value (p < 0.05) than that of the papillary thyroid carcinoma (1.8 ± 0.7%). The optimal cut-off value of the mean APTw value in differentiating papillary thyroid carcinoma from adenomatous nodule was 3.15%, with a sensitivity of 60% and a specificity of 100%. The mean ADC of papillary thyroid carcinoma (1.2 ± 0.2 × 10⁻³ mm²/s) was significantly lower than that of adenomatous nodule (2.0 ± 0.4 × 10⁻³ mm²/s). The optimal cut-off value of the mean ADC was 1.35 × 10⁻³ mm²/s, with a sensitivity of 100% and a specificity of 75%. Based on the ROC-curve analysis of APT and ADC, the ADC showed a higher area under the curve (AUC) than that of APT (AUC_APT = 0.84, AUC_ADC = 0.95).

Conclusion: APTw imaging may be as useful as DWI for the differentiation of papillary thyroid carcinoma from predominantly solid adenomatous nodule. Although the sensitivity of ADC was greater than that of APT, APT had greater specificity.

Intravoxel incoherent motion and ADC measurements for differentiating benign from malignant thyroid nodules: utilizing the most repeatable region of interest delineation at 3.0 T

Background

There is a growing need for a reproducible and effective imaging method for the quantitative differentiation of benign from malignant thyroid nodules. This study aimed to investigate the performances of intravoxel incoherent motion (IVIM) parameters and the apparent diffusion coefficient (ADC) in differentiating malignant from benign thyroid nodules derived from the most repeatable region of interest (ROI) delineation.

Methods

Forty-three patients with 46 pathologically confirmed thyroid nodules underwent diffusion-weighted imaging (DWI) with 8 b values. Two observers measured the intravoxel incoherent motion (IVIM) parameters (D, f and D*) and the apparent diffusion coefficient (ADC), ADC₆₀₀ and ADC₉₉₀ values using whole-lesion (W-L) ROI and IVIM parameters using single-section (S-S) ROI delineation. The intraclass correlation coefficients (ICCs) and Bland-Altman plots were used to evaluate the intra- and interobserver variability. The diagnostic performance of these parameters was evaluated by generating receiver operating characteristic (ROC) curves.

Results

The ICC values of all IVIM with W-L ROI delineation were higher than those with S-S ROI delineation, and excellent intra- and interobserver reproducibility was obtained. According to the Bland-Altman plots, the 95% limits of agreement of the IVIM parameters determined by the W-L ROIs revealed smaller absolute intra- and interobserver variability than those determined by S-S ROIs. The D and ADC₆₀₀ values obtained from the W-L ROIs were the most powerful parameters in differentiating benign from the malignant nodules [area under the ROC curve = 0.962 and 0.970, P = 0.771].

Conclusions

The W-L ROI of the thyroid was considered an effective method for obtaining IVIM measurements with excellent reproducibility for differentiating benign from malignant nodules.

Texture Analysis of High b-Value Diffusion-Weighted Imaging for Evaluating Consistency of Pituitary Macroadenomas

BACKGROUND

Preoperative evaluation of the consistency of pituitary macroadenomas is important for neurosurgeons to prepare the surgical plan.

PURPOSE

To evaluate the diagnostic performance of texture analysis (TA) of diffusion-weighted imaging (DWI) at a standard b-value (b = 1000 s/mm² ) and a high b-value (b = 2000 s/mm² ) for their ability to assess the tumor consistency of pituitary macroadenomas.

STUDY TYPE

Retrospective.

POPULATION/SUBJECTS

Fifty patients with histologically confirmed pituitary macroadenomas were classified as soft (n = 37) or hard (n = 13) types.

FIELD STRENGTH/SEQUENCE

Coronal T₂ -weighted imaging (T₂ WI), Readout Segmentation of Long Variable Echo-trains (RESOLVE) DWI at b = 1000 s/mm² and b = 2000 s/mm² were acquired with 3.0T MRI.

ASSESSMENT

The corresponding apparent diffusion coefficient (ADC) maps (ADC₁₀₀₀ and ADC₂₀₀₀ ) were registered to T₂ WI. Regions of interest (ROIs) were manually drawn along the solid part of the tumor from the coregistered T₂ WI-ADC images. The texture parameters from T₂ WI, ADC₁₀₀₀ , and ADC₂₀₀₀ were acquired.

STATISTICAL TESTS

The texture parameters were compared between the two types by using unpaired Student's t-test. Receiver operating characteristic (ROC) curves and logistic regression analyses were used to assess their diagnostic performance.

RESULTS

Significant differences in TA parameters of ADC₁₀₀₀ and ADC₂₀₀₀ were observed between soft and hard types (P &lt; 0.05 for all), whereas the TA of T₂ WI resulted in no significant difference (P &gt; 0.05 for all). TA of ADC₂₀₀₀ provided a superior diagnostic performance compared with that of ADC₁₀₀₀ (P = 0.038). A combination of mean value and entropy of ADC₂₀₀₀ yielded an AUC, a sensitivity, and a specificity of 0.911, 78.4% and 92.3%, respectively.

DATA CONCLUSION

TA of ADC values were useful for assessing the tumor consistency of pituitary macroadenomas. ADC₂₀₀₀ may facilitate better type discrimination.

LEVEL OF EVIDENCE

3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1507-1513.

Predictive Factors of Recurrence in Patients with Differentiated Thyroid Carcinoma: A Retrospective Analysis on 579 Patients

Differentiated thyroid carcinoma (DTC) is usually associated with a favorable prognosis. Nevertheless, up to 30% of patients present a local or distant recurrence. The aim of this study was to assess the incidence of recurrence after surgery for DTC and to identify predictive factors of recurrence. We included in this retrospective study 579 consecutive patients who underwent thyroidectomy for DTC from 2011 to 2016 at our institution. We observed biochemical or structural recurrent disease in 36 (6.2%) patients; five-year disease-free survival was 94.1%. On univariate analysis, male sex, histotype, lymph node yield, lymph node metastasis, extrathyroidal invasion and multicentricity were associated with significantly higher risk of recurrence, while microcarcinoma was correlated with significantly lower risk of recurrence. On multivariate analysis, only lymph node metastases (OR 4.724, p = 0.012) and microcarcinoma (OR 0.328, p = 0.034) were detected as independent predictive factors of recurrence. Postoperative management should be individualized and commensurate with the risk of recurrence: Patients with high-risk carcinoma should undergo strict follow-up and aggressive treatment. Furthermore, assessment of the risk should be repeated over time, considering individual response to therapy.

Comparative analysis of the value of diffusion kurtosis imaging and diffusion-weighted imaging in evaluating the histological features of endometrial cancer

Purpose

This study evaluated and compared the performances of diffusion kurtosis imaging (DKI) and diffusion-weighted imaging (DWI) for diagnosing and histologically grading endometrial cancer.

Materials and methods

In this retrospective study, DKI and DWI data for 61 patients with endometrial cancer and 30 patients with a normal endometrium were analyzed, and the mean kurtosis (MK), mean diffusion coefficient (MD) and apparent diffusion coefficient (ADC) values for the endometrial cancer tissue and normal endometrial tissue were acquired. The parameters for the normal endometrium group (G0) and the endometrial cancer groups (G1, G2 and G3) were compared and analyzed. The receiver operating characteristic (ROC) curve was used to evaluate each parameter’s diagnostic accuracy and threshold. Spearman correlation analysis was used to analyze the correlations between all parameters and histological grades.

Results

The MK values for the G0, G1, G2 and G3 groups increased gradually, while the MD and ADC values decreased gradually. Except for the differences in the ADC values between G0 and G1, the differences among the groups were statistically significant (P < 0.05). The MK values had the highest diagnostic accuracy in differentiating G0 and (G1 + G2 + G3), G0 and G1, G1 and G2, and G2 and G3 (AUC = 0.93, 0.76, 0.91, 0.91, P < 0.05). MK was maximally correlated with histological grade, followed by MD and ADC (MK > MD > ADC; r = − 0.85, + 0.82, + 0.76, P < 0.01).

Conclusion

Both DKI and DWI can be used to evaluate the diagnosis and histological grading of endometrial cancer. Compared with DWI, the DKI model is a more complete mathematical model with more sensitive parameters, which can more effectively evaluate the pathological and physiological characteristics of endometrial cancer.