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Unenhanced magnetic resonance imaging of papillary thyroid carcinoma with emphasis on diffusion kurtosis imaging
BACKGROUND: The aim of this study was to investigate the value of unenhanced magnetic resonance imaging (MRI) with diffusion kurtosis imaging (DKI) in diagnosing papillary thyroid carcinoma (PTC). METHODS: In all, 77 consecutive patients comprising a total of 77 thyroid nodules were enrolled in this...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102801/ https://www.ncbi.nlm.nih.gov/pubmed/37064397 http://dx.doi.org/10.21037/qims-22-172 |
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author | Tang, Qiying Liu, Xinyou Jiang, Qiuli Zhu, Liuhong Zhang, Jinhui Wu, Pu-Yeh Jiang, Ying Zhou, Jianjun |
author_facet | Tang, Qiying Liu, Xinyou Jiang, Qiuli Zhu, Liuhong Zhang, Jinhui Wu, Pu-Yeh Jiang, Ying Zhou, Jianjun |
author_sort | Tang, Qiying |
collection | PubMed |
description | BACKGROUND: The aim of this study was to investigate the value of unenhanced magnetic resonance imaging (MRI) with diffusion kurtosis imaging (DKI) in diagnosing papillary thyroid carcinoma (PTC). METHODS: In all, 77 consecutive patients comprising a total of 77 thyroid nodules were enrolled in this study. Of these nodules, 41 were histopathologically confirmed PTCs and 36 were benign nodules. All patients underwent thyroid MRI including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and DKI. All the images were assessed by 2 radiologists. The signal intensity ratio (SIR) of these nodules on T1WI and T2WI, the apparent diffusion coefficient (ADC) from DWI, and mean diffusivity (MD) and mean kurtosis (MK) from DKI were measured. Morphological features on these images were also evaluated. Univariate and multivariate logistic regression analyses were used to evaluate the value of these parameters as potential predictors of PTC. RESULTS: In the univariate analyses, the features that significantly indicated PTC were decreased ADC value (P<0.001), decreased MD value (P<0.001), increased MK value (P<0.001), younger age (P=0.001), female tendency (P=0.049), smaller tumor diameter (P<0.001), solid component (P<0.001), and irregular margin (P<0.001). In the multivariate analysis, decreased MD value (odds ratio =25.321; P=0.001), smaller diameter (odds ratio =13.751; P=0.006), and irregular margin (odds ratio =16.003; P=0.003) were independent risk factors for PTC. The combined predictor of MD, diameter, and margin showed an area under the receiver operating characteristic (ROC) curve of 0.996 in diagnosing PTC, with an optimal cutoff value of 0.69 (95.1% sensitivity, 100.0% specificity). CONCLUSIONS: Lower MD value from DKI, smaller diameter, and irregular margin are useful predictive biomarkers for PTC. |
format | Online Article Text |
id | pubmed-10102801 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-101028012023-04-15 Unenhanced magnetic resonance imaging of papillary thyroid carcinoma with emphasis on diffusion kurtosis imaging Tang, Qiying Liu, Xinyou Jiang, Qiuli Zhu, Liuhong Zhang, Jinhui Wu, Pu-Yeh Jiang, Ying Zhou, Jianjun Quant Imaging Med Surg Original Article BACKGROUND: The aim of this study was to investigate the value of unenhanced magnetic resonance imaging (MRI) with diffusion kurtosis imaging (DKI) in diagnosing papillary thyroid carcinoma (PTC). METHODS: In all, 77 consecutive patients comprising a total of 77 thyroid nodules were enrolled in this study. Of these nodules, 41 were histopathologically confirmed PTCs and 36 were benign nodules. All patients underwent thyroid MRI including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and DKI. All the images were assessed by 2 radiologists. The signal intensity ratio (SIR) of these nodules on T1WI and T2WI, the apparent diffusion coefficient (ADC) from DWI, and mean diffusivity (MD) and mean kurtosis (MK) from DKI were measured. Morphological features on these images were also evaluated. Univariate and multivariate logistic regression analyses were used to evaluate the value of these parameters as potential predictors of PTC. RESULTS: In the univariate analyses, the features that significantly indicated PTC were decreased ADC value (P<0.001), decreased MD value (P<0.001), increased MK value (P<0.001), younger age (P=0.001), female tendency (P=0.049), smaller tumor diameter (P<0.001), solid component (P<0.001), and irregular margin (P<0.001). In the multivariate analysis, decreased MD value (odds ratio =25.321; P=0.001), smaller diameter (odds ratio =13.751; P=0.006), and irregular margin (odds ratio =16.003; P=0.003) were independent risk factors for PTC. The combined predictor of MD, diameter, and margin showed an area under the receiver operating characteristic (ROC) curve of 0.996 in diagnosing PTC, with an optimal cutoff value of 0.69 (95.1% sensitivity, 100.0% specificity). CONCLUSIONS: Lower MD value from DKI, smaller diameter, and irregular margin are useful predictive biomarkers for PTC. AME Publishing Company 2022-08-18 2023-04-01 /pmc/articles/PMC10102801/ /pubmed/37064397 http://dx.doi.org/10.21037/qims-22-172 Text en 2023 Quantitative Imaging in Medicine and Surgery. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Tang, Qiying Liu, Xinyou Jiang, Qiuli Zhu, Liuhong Zhang, Jinhui Wu, Pu-Yeh Jiang, Ying Zhou, Jianjun Unenhanced magnetic resonance imaging of papillary thyroid carcinoma with emphasis on diffusion kurtosis imaging |
title | Unenhanced magnetic resonance imaging of papillary thyroid carcinoma with emphasis on diffusion kurtosis imaging |
title_full | Unenhanced magnetic resonance imaging of papillary thyroid carcinoma with emphasis on diffusion kurtosis imaging |
title_fullStr | Unenhanced magnetic resonance imaging of papillary thyroid carcinoma with emphasis on diffusion kurtosis imaging |
title_full_unstemmed | Unenhanced magnetic resonance imaging of papillary thyroid carcinoma with emphasis on diffusion kurtosis imaging |
title_short | Unenhanced magnetic resonance imaging of papillary thyroid carcinoma with emphasis on diffusion kurtosis imaging |
title_sort | unenhanced magnetic resonance imaging of papillary thyroid carcinoma with emphasis on diffusion kurtosis imaging |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102801/ https://www.ncbi.nlm.nih.gov/pubmed/37064397 http://dx.doi.org/10.21037/qims-22-172 |
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