Non-invasive Amide Proton Transfer Imaging and ZOOM Diffusion-Weighted Imaging in Differentiating Benign and Malignant Thyroid Micronodules.
Front Endocrinol (Lausanne)
; 9: 747, 2018.
Article
em En
| MEDLINE
| ID: mdl-30631303
Background: Pre-operative non-invasive differentiation of benign and malignant thyroid nodules is difficult for doctors. This study aims to determine whether amide proton transfer (APT) imaging and zonally oblique multi-slice (ZOOM) diffusion-weighted imaging (DWI) can provide increased accuracy in differentiating benign and malignant thyroid nodules. Methods: This retrospective study was approved by the institutional review board and included 60 thyroid nodules in 50 patients. All of the nodules were classified as malignant (n = 21) or benign (n = 39) based on pathology. It was meaningful to analyze the APT and apparent diffusion coefficient (ADC) values of the two groups by independent t-test to identify the benign and malignant thyroid nodules. The relationship between APT and ZOOM DWI was explored through Pearson correlation analysis. The diagnostic efficacy of APT and ZOOM DWI in determining if thyroid nodules were benign or malignant was compared using receiver operating characteristic (ROC) curve analysis. Results: The mean APTw value of the benign nodules was 2.99 ± 0.79, while that of the malignant nodules was 2.14 ± 0.73. Additionally, there was a significant difference in the APTw values of the two groups (P < 0.05). The mean ADC value of the benign nodules was 1.84 ± 0.41, and was significantly different from that of the malignant nodules, which was 1.21 ± 0.19 (P < 0.05). Scatter point and Pearson test showed a moderate positive correlation between the APT and ADC values (P < 0.05). The ROC curve showed that the area under the curve (AUC) value of ZOOM DWI (AUC = 0.937) was greater than that of APT (AUC = 0.783) (P = 0.028). Conclusion: APT and ZOOM DWI imaging improved the accuracy of distinguishing between benign and malignant thyroid nodules. ZOOM DWI is superior to APTw imaging (Z = 2.198, P < 0.05).
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Base de dados:
MEDLINE
Tipo de estudo:
Observational_studies
/
Prognostic_studies
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article