Share this content in WeChat
Application status and progress of magnetic resonance imaging in thyroid cancer
HUANG Ya'nan  ZU Hanyu  HAN Huiting  HUANG Junlin  WANG Yutang  JIANG Xingyue 

HUANG Y N, ZU H Y, HAN H T, et al. Application status and progress of magnetic resonance imaging in thyroid cancer[J]. Chin J Magn Reson Imaging, 2023, 14(8): 145-149. DOI:10.12015/issn.1674-8034.2023.08.025.

[Abstract] With the rapid development of magnetic resonance software and hardware technology and the development and application of thyroid surface coil, the image quality of thyroid magnetic resonance imaging is obviously improved, and it also plays an increasingly important role in the diagnosis and treatment of thyroid diseases. This paper reviewed the applications of magnetic resonance imaging in thyroid cancer and elaborated the application status and research progress of conventional magnetic resonance imaging and functional magnetic resonance imaging in thyroid cancer. In addition, we prospected the future development direction and application prospect of thyroid magnetic resonance imaging in this study. In order to provide important reference for the clinical treatment and surgical planning of thyroid cancer, and promote the clinical research and application of magnetic resonance imaging of thyroid cancer.
[Keywords] thyroid cancer;magnetic resonance imaging;functional magnetic resonance imaging;dynamic contrast-enhanced;diffusion weighted imaging;proton magnetic resonance spectroscopy

HUANG Ya'nan   ZU Hanyu   HAN Huiting   HUANG Junlin   WANG Yutang   JIANG Xingyue*  

Department of Radiology, Affiliated Hospital of Binzhou Medical College, Binzhou 256603, China

Corresponding author: Jiang XY, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS Natural Science Foundation of Shandong Province (No. ZR2018LH015).
Received  2023-03-24
Accepted  2023-07-21
DOI: 10.12015/issn.1674-8034.2023.08.025
HUANG Y N, ZU H Y, HAN H T, et al. Application status and progress of magnetic resonance imaging in thyroid cancer[J]. Chin J Magn Reson Imaging, 2023, 14(8): 145-149. DOI:10.12015/issn.1674-8034.2023.08.025.

TIAN W, SHI C L, WAN Z. Surgical treatment of thyroid cancer in China: progress in recent 10 years[J]. Chin J Pract Surg, 2022, 42(8): 841-844. DOI: 10.19538/j.cjps.issn1005-2208.2022.08.01.
Koch B L, Vattoth S, CHAPMAN P R. Diagnostic Imaging: Head and Neck-E-Book[M]. Canada: Elsevier Health Sciences, 2021:238-239.
WARREN FRUNZAC R, RICHARDS M. Computed tomography and magnetic resonance imaging of the thyroid and parathyroid glands[M]. Imaging in Endocrine Disorders, S. Karger AG, 2016: 16-23. DOI: 10.1159/000442274.
SUNG H, FERLAY J, SIEGEL R L, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71(3): 209-249. DOI: 10.3322/caac.21660.
MIHAILOVIĆ J, STEFANOVIĆ L, PRVULOVIC M. Magnetic resonance imaging in diagnostic algorithm of solitary cold thyroid nodules[J]. J BUON, 2006, 11(3): 341-346.
WU M N, LIANG L F, ZHANG M R, et al. Value of multi-parameter MRI in the diagnosis of thyroid benign and malignant nodules[J]. Chin J Radiol, 2021, 55(7): 710-715. DOI: 10.3760/cma.j.cn112149-20200822-01022.
XIE Y S, WU M N, HE P, et al. The imaging diagnosis and differential diagnosis of thyroid carcinoma and metastatic lymph nodes[J]. Chin J Radiol, 2022, 56(6): 715-718. DOI: 10.3760/cma.j.cn112149-20220322-00263.
SHIN C H, ROH J L, SONG D E, et al. Prognostic value of tumor size and minimal extrathyroidal extension in papillary thyroid carcinoma[J]. Am J Surg, 2020, 220(4): 925-931. DOI: 10.1016/j.amjsurg.2020.02.020.
WANG J C, TAKASHIMA S, MATSUSHITA T, et al. Esophageal invasion by thyroid carcinomas: prediction using magnetic resonance imaging[J]. J Comput Assist Tomogr, 2003, 27(1): 18-25. DOI: 10.1097/00004728-200301000-00004.
TAKASHIMA S, TAKAYAMA F, WANG J C, et al. Using MR imaging to predict invasion of the recurrent laryngeal nerve by thyroid carcinoma[J]. AJR Am J Roentgenol, 2003, 180(3): 837-842. DOI: 10.2214/ajr.180.3.1800837.
WEI R, ZHUANG Y Z, WANG L Y, et al. Histogram-based analysis of diffusion-weighted imaging for predicting aggressiveness in papillary thyroid carcinoma[J/OL]. BMC Med Imaging, 2022, 22(1): 188 [2023-03-23]. DOI: 10.1186/s12880-022-00920-4.
DAI Z D, WEI R, WANG H, et al. Multimodality MRI-based radiomics for aggressiveness prediction in papillary thyroid cancer[J/OL]. BMC Med Imaging, 2022, 22(1): 54 [2023-03-23]. DOI: 10.1186/s12880-022-00779-5.
XIE Y S, WANG S X, ZHANG M R, et al. The value of preoperative multi-parametric MR features using surface coil exclusive designed for thyroid gland in predicting the metastatic status of regional lymph nodes in thyroid cancer[J]. Chin J Magn Reson Imag, 2021, 12(4):17-22. DOI: 10.12015/issn.1674-8034.2021.04.004.
LIU L X, DONG Y. Application of artificial intelligence technology in diagnosing thyroid nodules and predicting lymph node metastasis[J]. J Interv Radiol, 2021, 30(4): 323-326. DOI: 10.3969/j.issn.1008-794X.2021.04.001.
MA W Q, CHEN K Y, YANG N, et al. Diagnostic value of machine learning based on multi-parameters of MRI radiomics to predict cervical lymph node status of papillary thyroid carcinoma[J]. Chin J Magn Reson Imag, 2022, 13(10): 108-113. DOI: 10.12015/issn.1674-8034.2022.10.016.
HU W J, ZHUANG Y Z, TANG L, et al. Preoperative cervical lymph node metastasis prediction in papillary thyroid carcinoma: a noninvasive clinical multimodal radiomics (CMR) nomogram analysis[J/OL]. J Oncol, 2023, 2023: 3270137 [2023-03-23]. DOI: 10.1155/2023/3270137.
TIAN J. Advances of the functional imaging in thyroid precision magnetic resonance imaging[J]. China Med Devices, 2022, 37(3): 159-162, 166. DOI: 10.3969/j.issn.1674-1633.2022.03.038.
GUPTA N, KAKAR A K, CHOWDHURY V, et al. Magnetic resonance spectroscopy as a diagnostic modality for carcinoma thyroid[J]. Eur J Radiol, 2007, 64(3): 414-418. DOI: 10.1016/j.ejrad.2007.03.006.
AGHAGHAZVINI L, PIROUZI P, SHARIFIAN H, et al. 3T magnetic resonance spectroscopy as a powerful diagnostic modality for assessment of thyroid nodules[J]. Arch Endocrinol Metab, 2018, 62(5): 501-505. DOI: 10.20945/2359-3997000000069.
TAO Q, LÜ Y F, XU H, et al. The role of quantitative and qualitative DCE-MRI in distinguishing benign and malignant of thyroids nodules[J]. Chin Comput Med Imag, 2022, 28(1): 38-43. DOI: 10.19627/j.cnki.cn31-1700/th.2022.01.002.
SAKAT M S, SADE R, KILIC K, et al. The use of dynamic contrast-enhanced perfusion MRI in differentiating benign and malignant thyroid nodules[J]. Indian J Otolaryngol Head Neck Surg, 2019, 71(Suppl 1): 706-711. DOI: 10.1007/s12070-018-1512-3.
SONG M H, YUE Y L, GUO J S, et al. Quantitative analyses of the correlation between dynamic contrast-enhanced MRI and intravoxel incoherent motion DWI in thyroid nodules[J/OL]. Am J Transl Res, 2020, 12(7): 3984-3992 [2023-03-23].
HE P, Huerman·Bahetibieke, ZHANG M R, et al. Semiquantitative and quantitative analyses of dynamic contrast-enhanced magnetic resonance imaging in the differentiation between malignant and benign thyroid nodules[J]. Chin J Magn Reson Imag, 2021, 12(7): 12-17. DOI: 10.12015/issn.1674-8034.2021.07.003.
ZHANG X R, BAI H L, LIU S M. Study on CT and MRI of thyroid adenoma and papillary thyroid carcinoma[J]. Chin J CT MRI, 2022, 20(5): 4-6. DOI: 10.3969/j.issn.1672-5131.2022.05.002.
ZHOU Y Y, WANG X, HU S D. The application of DCE GMRI in different iatingthyroidadenomaandpapillarythyroidcarcinoma[J]. J Pract Radiol, 2019, 35(5): 718-721. DOI: 10.3969/j.issn.1002-1671.2019.05.008.
WANG X, CHEN Y R, ZHANG G L, et al. Clinical value of diffusion-weighted magnetic resonance imaging in evaluating malignant grade of papillary thyroid carcinoma[J]. J Jiangsu Univ Med Ed, 2018, 28(1): 86-88. DOI: 10.13312/j.issn.1671-7783.y170212.
ZHU X, WANG Y C, ZHU Z F, et al. Clinical application value of ADC values in differentiating papillary in diagnosis of thyroid nodules[J]. J Med Imag, 2021, 31(6): 926-930.
REN S, LIU C H, BAI R J. Value of diffusion weighted imaging in diagnosis of nodular lesions of thyroid: a preliminary study[J]. Natl Med J China, 2010, 90(47): 3351-3354. DOI: 10.3760/cma.J.issn.03.
HU S D, ZHANG H, WANG X, et al. Can diffusion-weighted MR imaging be used as a tool to predict extrathyroidal extension in papillary thyroid carcinoma?[J]. Acad Radiol, 2021, 28(4): 467-474. DOI: 10.1016/j.acra.2020.03.005.
LU Y, CHEN Y R, HU S D, et al. Utility of different b-values diffusion-weighted MR imaging in differentiating malignant from benign thyroid nodules[J]. J Jiangsu Univ Med Ed, 2017, 27(3): 257-260. DOI: 10.13312/j.issn.1671-7783.y170082.
REN J, DI X, SHEN Z W, et al. Apparent diffusion coefficient histogram parameters obtained with different b values for differentiating benign and malignant thyroid nodules[J]. Chin J Med Imag Technol, 2022, 38(10): 1561-1566. DOI: 10.13929/j.issn.1003-3289.2022.10.026.
ZHU X, WANG J, WANG Y C, et al. Quantitative differentiation of malignant and benign thyroid nodules with multi-parameter diffusion-weighted imaging[J]. World J Clin Cases, 2022, 10(24): 8587-8598. DOI: 10.12998/wjcc.v10.i24.8587.
HUANG B F. Study of the diagnostic value of high resolution reduced field of view diffusion weighted imaging and dynamic contrast-enhancement imaging in prostate cancer by magnetic resonance imaging[D]. Luzhou: Southwest Medical University, 2020. DOI: 10.27215/d.cnki.glzyu.2020.000351.
PENG Y, LI Z, TANG H, et al. Comparison of reduced field-of-view diffusion-weighted imaging (DWI) and conventional DWI techniques in the assessment of rectal carcinoma at 3.0T: image quality and histological T staging[J]. J Magn Reson Imaging, 2018, 47(4): 967-975. DOI: 10.1002/jmri.25814.
BARON P, WIELEMA M, DIJKSTRA H, et al. Comparison of conventional and higher-resolution reduced-FOV diffusion-weighted imaging of breast tissue[J/OL]. Magma, 2022 [2023-03-23]. DOI: 10.1007/s10334-022-01055-x.
WANG Y F, REN Y, ZHU C F, et al. Optimising diffusion-weighted imaging of the thyroid gland using dedicated surface coil[J/OL]. Clin Radiol, 2022, 77(11): e791-e798 [2023-03-23]. DOI: 10.1016/j.crad.2022.07.011.
HE Z Z, ZHOU Q Q, YU Y S, et al. Evaluation of thyroid gland image quality by conventional and ZOOMit DWI[J]. Chin Comput Med Imag, 2020, 26(4): 324-328. DOI: 10.19627/j.cnki.cn31-1700/th.2020.04.006.
SONG M H, JIN Y F, GUO J S, et al. Application of whole-lesion intravoxel incoherent motion analysis using iZOOM DWI to differentiate malignant from benign thyroid nodules[J]. Acta Radiol, 2019, 60(9): 1127-1134. DOI: 10.1177/0284185118813599.
LIU B. The diagnostic performance of reduced field-of-view multi-b diffusion-weighted imaging in thyroid and parathyroid lesions[D]. Jinan: Shandong University, 2020. DOI: 10.27272/d.cnki.gshdu.2020.004738.
KUANG Y Y, YE K L, JIANG Z J, et al. Differential diagnosis of benign and malignant thyroid nodules with intravoxel incoherent motion diffusion-weighted imaging and diffusion-weighted imaging: Meta-analysis[J]. Chin J Med Imag Technol, 2021, 37(5): 674-679. DOI: 10.13929/j.issn.1003-3289.2021.05.009.
SONG M H, YUE Y L, JIN Y F, et al. 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[J/OL]. Cancer Imaging, 2020, 20(1): 9 [2023-03-23]. DOI: 10.1186/s40644-020-0289-2.
SU Y, GAO S J, CAO J B, et al. Each parameter value in differential diagnosis of benign and malignant thyroid nodules under IVIM theoretical aspects[J]. J China Clin Med Imag, 2017, 28(3): 176-179. DOI: 10.3969/j.issn.1008-1062.2017.03.007.
HU H, PENG J H, ZHOU L H, et al. The differential diagnostic value for benign and malignant thyroid nodules of intravoxel incoherent motion diffusion-weighted imaging: meta-analysis[J]. J Clin Radiol, 2020, 39(4): 664-668. DOI: 10.13437/j.cnki.jcr.2020.04.009.
TAN H, CHEN J, ZHAO Y L, et al. Feasibility of intravoxel incoherent motion for differentiating benign and malignant thyroid nodules[J]. Acad Radiol, 2019, 26(2): 147-153. DOI: 10.1016/j.acra.2018.05.011.
JIANG L L, CHEN J, HUANG H P, et al. Comparison of the differential diagnostic performance of intravoxel incoherent motion imaging and diffusion kurtosis imaging in malignant and benign thyroid nodules[J/OL]. Front Oncol, 2022, 12: 895972 [2023-03-23]. DOI: 10.3389/fonc.2022.895972.
IIMA M, REYNAUD O, TSURUGIZAWA T, et al. Characterization of glioma microcirculation and tissue features using intravoxel incoherent motion magnetic resonance imaging in a rat brain model[J]. Invest Radiol, 2014, 49(7): 485-490. DOI: 10.1097/RLI.0000000000000040.
LEMKE A, STIELTJES B, SCHAD L R, et al. Toward an optimal distribution of b values for intravoxel incoherent motion imaging[J]. Magn Reson Imaging, 2011, 29(6): 766-776. DOI: 10.1016/j.mri.2011.03.004.
ZHU X, WANG Y C, WANG J, et al. Magnetic resonance diffusion kurtosis imaging in differential diagnosis of thyroid nodules[J]. Zhejiang Med J, 2019, 41(24): 2600-2602, 2606, 15. DOI: 10.12056/j.issn.1006-2785.2019.41.24.2019-2670.

PREV Association and mechanism of asymptomatic carotid stenosis with cognitive impairment as suggested by multimodal MRI
NEXT Research progress of magnetic resonance imaging in diagnosis of thyroid nodules

Tel & Fax: +8610-67113815    E-mail: