Literature DB >> 29908978

Feasibility of Intravoxel Incoherent Motion for Differentiating Benign and Malignant Thyroid Nodules.

Hui Tan1, Jun Chen2, Yi Ling Zhao3, Jin Huan Liu3, Liang Zhang3, Chang Sheng Liu3, Dongjie Huang3.   

Abstract

RATIONALE AND
OBJECTIVES: This study aimed to preliminarily investigate the feasibility of intravoxel incoherent motion (IVIM) theory in the differential diagnosis of benign and malignant thyroid nodules.
MATERIALS AND METHODS: Forty-five patients with 56 confirmed thyroid nodules underwent preoperative routine magnetic resonance imaging and IVIM diffusion-weighted imaging. The histopathologic diagnosis was confirmed by surgery. Apparent diffusion coefficient (ADC), perfusion fraction f, diffusivity D, and pseudo-diffusivity D* were quantified. Independent samples t test of IVIM-derived metrics were conducted between benign and malignant nodules. Receiver-operating characteristic analyses were performed to determine the optimal thresholds as well as the sensitivity and specificity for differentiating.
RESULTS: Significant intergroup difference was observed in ADC, D, D*, and f (p < 0.001). Malignant tumors featured significantly lower ADC, D and D* values and a higher f value than that of benign nodules. The ADC, D, and D* could distinguish the benign from malignant thyroid nodules, and parameter f differentiate the malignant tumors from benign nodules. The values of the area under the curve for parameter ADC, D, and D* were 0.784 (p = 0.001), 0.795 (p = 0.001), and 0.850 (p < 0.001), separately, of which the area under the curve of f value was the maximum for identifying the malignant from benign nodules, which was 0.841 (p < 0.001).
CONCLUSION: This study suggested that ADC and IVIM-derived metrics, including D, D*, and f, could potentially serve as noninvasive predictors for the preoperative differentiating of thyroid nodules, and f value performed best in identifying the malignant from benign nodules among these parameters.
Copyright © 2018 Academic Radiology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Benign and malignant thyroid nodules; Differential diagnosis; Intravoxel incoherent motion; Magnetic resonance imaging; Multiple b value

Year:  2018        PMID: 29908978     DOI: 10.1016/j.acra.2018.05.011

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  5 in total

1.  Distinguishing early-stage nasopharyngeal carcinoma from benign hyperplasia using intravoxel incoherent motion diffusion-weighted MRI.

Authors:  Qi-Yong Ai; Ann D King; Janet S M Chan; Weitian Chen; K C Allen Chan; John K S Woo; Benny C Y Zee; Anthony T C Chan; Darren M C Poon; Brigette B Y Ma; Edwin P Hui; Anil T Ahuja; Alexander C Vlantis; Jing Yuan
Journal:  Eur Radiol       Date:  2019-03-22       Impact factor: 5.315

2.  Predicting Grade of Esophageal Squamous Carcinoma: Can Stretched Exponential Model-Based DWI Perform Better Than Bi-Exponential and Mono-Exponential Model?

Authors:  Hui Yang; Xubo Ge; Xiuzhu Zheng; Xiaoqian Li; Jiang Li; Min Liu; Jianzhong Zhu; Jian Qin
Journal:  Front Oncol       Date:  2022-07-14       Impact factor: 5.738

3.  Comparison of the Differential Diagnostic Performance of Intravoxel Incoherent Motion Imaging and Diffusion Kurtosis Imaging in Malignant and Benign Thyroid Nodules.

Authors:  Liling Jiang; Jiao Chen; Haiping Huang; Jian Wu; Junbin Zhang; Xiaosong Lan; Daihong Liu; Jiuquan Zhang
Journal:  Front Oncol       Date:  2022-07-22       Impact factor: 5.738

4.  Quantitative differentiation of malignant and benign thyroid nodules with multi-parameter diffusion-weighted imaging.

Authors:  Xiang Zhu; Jia Wang; Yan-Chun Wang; Ze-Feng Zhu; Jian Tang; Xiao-Wei Wen; Ying Fang; Jun Han
Journal:  World J Clin Cases       Date:  2022-08-26       Impact factor: 1.534

5.  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.

Authors:  Minghui Song; Yunlong Yue; Yanfang Jin; Jinsong Guo; Lili Zuo; Hong Peng; Queenie Chan
Journal:  Cancer Imaging       Date:  2020-01-22       Impact factor: 3.909

  5 in total

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