Literature DB >> 28616727

Preliminary study of diffusion kurtosis imaging in thyroid nodules and its histopathologic correlation.

Ruo-Yang Shi1, Qiu-Ying Yao1, Qin-Yi Zhou2, Qing Lu1, Shi-Teng Suo1, Jun Chen2, Wen-Jie Zheng2, Yong-Ming Dai3, Lian-Ming Wu4, Jian-Rong Xu5.   

Abstract

OBJECTIVES: To evaluate the utility of diffusion kurtosis imaging (DKI) of patients with thyroid nodules and to assess the probable correlation with histopathological factors.
METHODS: The study included 58 consecutive patients with thyroid nodules who underwent magnetic resonance imaging (MRI) examination, including DKI and diffusion-weighted imaging (DWI). Histopathological analysis of paraffin sections included cell density and immunohistochemical analysis of Ki-67 and vascular endothelial growth factor (VEGF). Statistical analyses were performed using Student's t-test, receiver operating characteristic (ROC) curves and Spearman's correlation.
RESULTS: The diffusion parameters, cell density and immunohistochemistry analysis between malignant and benign lesions showed significant differences. The largest area under the ROC curve was acquired for the D value (AUC = 0.797). The highest sensitivity was shown with the use of K (threshold = 0.832, sensitivity = 0.917). The Ki-67 expression generally stayed low. A moderate correlation was found between ADC, D and cell density (r = -0.536, P = 0.000; r = -0.570, P = 0.000) and ADC, D and VEGF expression (r = -0.451, P = 0.000; r = -0.522, P = 0.000).
CONCLUSION: The DKI-derived parameters D and K demonstrated an advantage compared to conventional DWI for thyroid lesion diagnosis. While the histopathological study indicated that the D value correlated better with extracellular change than the ADC value, the K value probably changed relative to the intracellular structure. KEY POINTS: • DWI and DKI parameters can identify PTC from benign thyroid nodules. • Correlations were found between diffusion parameters and histopathological analysis. • DKI obtains better diagnostic accuracy than conventional DWI.

Entities:  

Keywords:  DKI; DWI; Thyroid; Thyroid nodule; VEGF

Mesh:

Substances:

Year:  2017        PMID: 28616727     DOI: 10.1007/s00330-017-4874-0

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  37 in total

1.  Diffusion-weighted imaging of prostate cancer: effect of b-value distribution on repeatability and cancer characterization.

Authors:  Harri Merisaari; Jussi Toivonen; Marko Pesola; Pekka Taimen; Peter J Boström; Tapio Pahikkala; Hannu J Aronen; Ivan Jambor
Journal:  Magn Reson Imaging       Date:  2015-07-26       Impact factor: 2.546

2.  Role of apparent diffusion coefficient values in differentiation between malignant and benign solitary thyroid nodules.

Authors:  A A K Abdel Razek; A G Sadek; O R Kombar; T E Elmahdy; N Nada
Journal:  AJNR Am J Neuroradiol       Date:  2007-11-26       Impact factor: 3.825

3.  Breast Cancer: Diffusion Kurtosis MR Imaging-Diagnostic Accuracy and Correlation with Clinical-Pathologic Factors.

Authors:  Kun Sun; Xiaosong Chen; Weimin Chai; Xiaochun Fei; Caixia Fu; Xu Yan; Ying Zhan; Kemin Chen; Kunwei Shen; Fuhua Yan
Journal:  Radiology       Date:  2015-05-04       Impact factor: 11.105

4.  Diffusion-weighted images differentiate benign from malignant thyroid nodules.

Authors:  Gulnur Erdem; Tamer Erdem; Hakki Muammer; Deniz Yakar Mutlu; Ahmet Kemal Firat; Ibrahim Sahin; Alpay Alkan
Journal:  J Magn Reson Imaging       Date:  2010-01       Impact factor: 4.813

5.  Initial experience of 3 tesla apparent diffusion coefficient values in differentiating benign and malignant thyroid nodules.

Authors:  A Turan Ilica; Hakan Artaş; Asli Ayan; Armağan Günal; Ozdes Emer; Zafer Kilbas; Coskun Meric; Mehmet Mahir Atasoy; Ovsev Uzuner
Journal:  J Magn Reson Imaging       Date:  2012-11-12       Impact factor: 4.813

6.  Multiparametric MR imaging for differentiating between benign and malignant thyroid nodules: initial experience in 23 patients.

Authors:  Miho Sasaki; Misa Sumi; Ken-ichi Kaneko; Kotaro Ishimaru; Haruo Takahashi; Takashi Nakamura
Journal:  J Magn Reson Imaging       Date:  2012-11-27       Impact factor: 4.813

7.  Magnetic resonance imaging with diffusion-weighted imaging in the evaluation of thyroid-associated orbitopathy: getting below the tip of the iceberg.

Authors:  Letterio Salvatore Politi; Claudia Godi; Gabriella Cammarata; Alessandro Ambrosi; Antonella Iadanza; Roberto Lanzi; Andrea Falini; Stefania Bianchi Marzoli
Journal:  Eur Radiol       Date:  2014-02-12       Impact factor: 5.315

8.  On the utility of quantitative diffusion-weighted MR imaging as a tool in differentiation between malignant and benign thyroid nodules.

Authors:  Lian-Ming Wu; Xiao-Xi Chen; Yu-Lai Li; Jia Hua; Jie Chen; Jiani Hu; Jian-Rong Xu
Journal:  Acad Radiol       Date:  2013-12-12       Impact factor: 3.173

9.  Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors.

Authors:  Gene Young Cho; Linda Moy; Sungheon G Kim; Steven H Baete; Melanie Moccaldi; James S Babb; Daniel K Sodickson; Eric E Sigmund
Journal:  Eur Radiol       Date:  2015-11-28       Impact factor: 5.315

10.  Diagnostic value of diffusion-weighted MR imaging in thyroid disease: application in differentiating benign from malignant disease.

Authors:  Yingwei Wu; Xiuhui Yue; Weiwen Shen; Yushan Du; Ying Yuan; Xiaofeng Tao; Cheuk Ying Tang
Journal:  BMC Med Imaging       Date:  2013-07-30       Impact factor: 1.930

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  12 in total

1.  Development and validation of an ultrasound-based nomogram to improve the diagnostic accuracy for malignant thyroid nodules.

Authors:  Bao-Liang Guo; Fu-Sheng Ouyang; Li-Zhu Ouyang; Zi-Wei Liu; Shao-Jia Lin; Wei Meng; Xi-Yi Huang; Hai-Xiong Chen; Shao-Ming Yang; Qiu-Gen Hu
Journal:  Eur Radiol       Date:  2018-09-12       Impact factor: 5.315

2.  Diffusion kurtosis imaging provides quantitative assessment of the microstructure changes of disc degeneration: an in vivo experimental study.

Authors:  Li Li; Zhiguo Zhou; Jing Li; Jicheng Fang; Yuanyuan Qing; Tian Tian; Shun Zhang; Gang Wu; Alessandro Scotti; Kejia Cai; WenZhen Zhu
Journal:  Eur Spine J       Date:  2019-02-18       Impact factor: 3.134

3.  Efficacy of apparent diffusion coefficient in predicting aggressive histological features of papillary thyroid carcinoma.

Authors:  Bin Song; Hao Wang; Yongqi Chen; Weiyan Liu; Ran Wei; Yi Ding
Journal:  Diagn Interv Radiol       Date:  2018-11       Impact factor: 2.630

4.  Dual-source dual-energy computed tomography-derived quantitative parameters combined with machine learning for the differential diagnosis of benign and malignant thyroid nodules.

Authors:  Liling Jiang; Daihong Liu; Ling Long; Jiao Chen; Xiaosong Lan; Jiuquan Zhang
Journal:  Quant Imaging Med Surg       Date:  2022-02

Review 5.  Preclinical Imaging for the Study of Mouse Models of Thyroid Cancer.

Authors:  Adelaide Greco; Luigi Auletta; Francesca Maria Orlandella; Paola Lucia Chiara Iervolino; Michele Klain; Giuliana Salvatore; Marcello Mancini
Journal:  Int J Mol Sci       Date:  2017-12-16       Impact factor: 5.923

6.  Whole-lesion ADC histogram analysis is not able to reflect microvessel density in HNSCC.

Authors:  Hans-Jonas Meyer; Gordian Hamerla; Leonard Leifels; Anne Kathrin Höhn; Alexey Surov
Journal:  Medicine (Baltimore)       Date:  2019-05       Impact factor: 1.817

Review 7.  Magnetic Resonance Imaging for Translational Research in Oncology.

Authors:  Maria Felicia Fiordelisi; Carlo Cavaliere; Luigi Auletta; Luca Basso; Marco Salvatore
Journal:  J Clin Med       Date:  2019-11-06       Impact factor: 4.241

8.  MRI Texture Analysis Reflects Histopathology Parameters in Thyroid Cancer - A First Preliminary Study.

Authors:  Hans-Jonas Meyer; Stefan Schob; Anne Kathrin Höhn; Alexey Surov
Journal:  Transl Oncol       Date:  2017-10-06       Impact factor: 4.243

9.  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

10.  Radiomics Nomogram for Identifying Sub-1 cm Benign and Malignant Thyroid Lesions.

Authors:  Xinxin Wu; Jingjing Li; Yakui Mou; Yao Yao; Jingjing Cui; Ning Mao; Xicheng Song
Journal:  Front Oncol       Date:  2021-06-07       Impact factor: 6.244

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