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Research progress of functional magnetic resonance imaging and artificial intelligence in evaluating the staging of nasopharyngeal carcinoma
MO Zhiying  ZHOU Wenjuan  YANG Weizhen 

Cite this article as: MO Z Y, ZHOU W J, YANG W Z. Research progress of functional magnetic resonance imaging and artificial intelligence in evaluating the staging of nasopharyngeal carcinoma[J]. Chin J Magn Reson Imaging, 2024, 15(6): 202-206. DOI:10.12015/issn.1674-8034.2024.06.032.


[Abstract] Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumors of the head and neck, and accurate staging is helpful to guide the implementation of individualized treatment plan. At present, NPC staging mainly depends on magnetic resonance imaging (MRI), while conventional MRI can only be staged according to the morphological changes of tumor, which is highly subjective. Dynamic contrast-enhanced MRI, diffusion-weighted imaging, intravoxel incoherent motion imaging, diffusion kurtosis imaging and other MRI functional imaging technologies make the staging evaluation of NPC more objective through quantitative measurement, but at present, these technologies and their parameter values have not yet formed a unified standard for the staging evaluation of NPC. Artificial intelligence excavates more information from images and has a good application prospect in the future. We reviewed the value of these techniques in evaluating NPC staging in this paper, in order to provide a reliable basis for clinical diagnosis and treatment, and provide a reference direction for future research.
[Keywords] nasopharyngeal carcinoma;stage;magnetic resonance imaging;functional magnetic resonance imaging;artificial intelligence

MO Zhiying   ZHOU Wenjuan   YANG Weizhen*  

Department of Radiology, Wuzhou People's Hospital of Guangxi, Wuzhou 543000, China

Corresponding author: YANG W Z, E-mail: 13977480280@163.com

Conflicts of interest   None.

Received  2024-01-26
Accepted  2024-05-13
DOI: 10.12015/issn.1674-8034.2024.06.032
Cite this article as: MO Z Y, ZHOU W J, YANG W Z. Research progress of functional magnetic resonance imaging and artificial intelligence in evaluating the staging of nasopharyngeal carcinoma[J]. Chin J Magn Reson Imaging, 2024, 15(6): 202-206. DOI:10.12015/issn.1674-8034.2024.06.032.

[1]
HUANG H G, YAO Y Y, DENG X Y, et al. Immunotherapy for nasopharyngeal carcinoma: current status and prospects (Review)[J/OL]. Int J Oncol, 2023, 63(2): 97 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/37417358/. DOI: 10.3892/ijo.2023.5545.
[2]
ZHANG Y, CHEN L, HU G Q, et al. Final overall survival analysis of gemcitabine and cisplatin induction chemotherapy in nasopharyngeal carcinoma: a multicenter, randomized phase Ⅲ trial[J]. J Clin Oncol, 2022, 40(22): 2420-2425. DOI: 10.1200/JCO.22.00327.
[3]
CHEN Y P, CHAN A T C, LE Q T, et al. Nasopharyngeal carcinoma[J]. Lancet, 2019, 394(10192): 64-80. DOI: 10.1016/S0140-6736(19)30956-0.
[4]
LEE A W M, NG W T, CHAN J Y W, et al. Management of locally recurrent nasopharyngeal carcinoma[J/OL]. Cancer Treat Rev, 2019, 79: 101890 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/31470314/. DOI: 10.1016/j.ctrv.2019.101890.
[5]
KING A D. MR imaging of nasopharyngeal carcinoma[J]. Magn Reson Imaging Clin N Am, 2022, 30(1): 19-33. DOI: 10.1016/j.mric.2021.06.015.
[6]
YANG H F, WANG K, LIANG Z, et al. Prognostic role of pre-treatment serum albumin in patients with nasopharyngeal carcinoma: a meta-analysis and systematic review[J]. Clin Otolaryngol, 2020, 45(2): 167-176. DOI: 10.1111/coa.13454.
[7]
ZHANG L, DONG D, LI H L, et al. Development and validation of a magnetic resonance imaging-based model for the prediction of distant metastasis before initial treatment of nasopharyngeal carcinoma: a retrospective cohort study[J/OL]. EBioMedicine, 2019, 40: 327-335 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/30642750/. DOI: 10.1016/j.ebiom.2019.01.013.
[8]
ZHAO D W, FANG X M, ZHOU S H, et al. Application of diffusion kurtosis imaging in evaluating acute xerostomia in nasopharyngeal carcinoma treated with induction chemotherapy plus concurrent chemoradiotherapy[J/OL]. Front Oncol, 2022, 12: 870315 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/35664750/. DOI: 10.3389/fonc.2022.870315.
[9]
WU W Q, XIA J, LI B, et al. Feasibility evaluation of intravoxel incoherent motion diffusion-weighted imaging in the diagnosis of skull-base invasion in nasopharyngeal carcinoma[J]. J Cancer, 2023, 14(2): 290-298. DOI: 10.7150/jca.80679.
[10]
GUO Y H, DAI G M, XIONG X L, et al. Intravoxel incoherent motion radiomics nomogram for predicting tumor treatment responses in nasopharyngeal carcinoma[J/OL]. Transl Oncol, 2023, 31: 101648 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/36905870/. DOI: 10.1016/j.tranon.2023.101648.
[11]
TABNAK P, HAJIESMAILPOOR Z. Differentiating nasopharyngeal carcinoma from lymphoma in the head and neck region using the apparent diffusion coefficient (ADC) value: a systematic review and meta-analysis[J/OL]. Pol J Radiol, 2023, 88: e472-e482 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/38020498/. DOI: 10.5114/pjr.2023.132172.
[12]
WANG Z P, FANG M J, ZHANG J, et al. Radiomics and deep learning in nasopharyngeal carcinoma: a review[J/OL]. IEEE Rev Biomed Eng, 2024, 17: 118-135 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/37097799/. DOI: 10.1109/RBME.2023.3269776.
[13]
FOTOUHI M, SAMADI KHOSHE MEHR F, DELAZAR S, et al. Assessment of LI-RADS efficacy in classification of hepatocellular carcinoma and benign liver nodules using DCE-MRI features and machine learning[J/OL]. Eur J Radiol Open, 2023, 11: 100535 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/37964787/. DOI: 10.1016/j.ejro.2023.100535.
[14]
HUANG W Y, ZHANG Q H, WU G, et al. DCE-MRI quantitative transport mapping for noninvasively detecting hypoxia inducible factor-1α, epidermal growth factor receptor overexpression, and Ki-67 in nasopharyngeal carcinoma patients[J/OL]. Radiother Oncol, 2021, 164: 146-154 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/34592360/. DOI: 10.1016/j.radonc.2021.09.016.
[15]
LI H, ZHAO S, FAN H Y, et al. The effect of histogram analysis of DCE-MRI parameters on differentiating renal tumors[J/OL]. Clin Lab, 2023, 69(11) [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/37948477/. DOI: 10.7754/Clin.Lab.2023.221126.
[16]
LIU X, WANG X, CHEN Q M, et al. The early diagnostic value of DCE-MRI quantitative parameters combined with DWI for na-sopharyngeal carcinoma[J]. Pract J Clin Med, 2019, 16(2): 206-209. DOI: 10.3969/j.issn.1672-6170.2019.02.064.
[17]
SUN J Y, GAO W X, NI J, et al. Explore the diagnostic value of dynamic contrast-enhanced magnetic resonance ima-ging in clinical staging of nasopharyngeal carcinoma[J]. J Mod Oncol, 2020, 28(24): 4339-4342. DOI: 10.3969/j.issn.1672-4992.2020.24.028.
[18]
HUANG B S, WONG C S, WHITCHER B, et al. Dynamic contrast-enhanced magnetic resonance imaging for characterising nasopharyngeal carcinoma: comparison of semiquantitative and quantitative parameters and correlation with tumour stage[J]. Eur Radiol, 2013, 23(6): 1495-1502. DOI: 10.1007/s00330-012-2740-7.
[19]
NI L P, LIU Y. To compare the value of clinical stage of nasopharyngeal carcinoma diagnosed by DCE-MRI and DWI[J]. J Clin Radiol, 2016, 35(4): 518-522. DOI: 10.13437/j.cnki.jcr.2016.04.007.
[20]
YAO W W, ZHANG H, DING B, et al. Rectal cancer: 3D dynamic contrast-enhanced MRI; correlation with microvascular density and clinicopathological features[J]. Radiol Med, 2011, 116(3): 366-374. DOI: 10.1007/s11547-011-0628-2.
[21]
BAI C, TANG F, ZHANG Z, et al. Application value of dynamic contrast-enhanced magnetic resonance imaging in staging of nasopharyngeal carcinoma[J]. Prog Mod Biomed, 2019, 19(17): 3342-3346. DOI: 10.13241/j.cnki.pmb.2019.17.030.
[22]
YANG C L, WU W L, JIN F, et al. A prospective clinical study with long-term follow-up of the correlation between dynamic contrast-enhanced magnetic resonance parameters and prognosis in patients with locally advanced nasopharyngeal carcinoma[J]. Chin J Radiol Med Prot, 2020, 40(6): 446-453. DOI: 10.3760/cma.j.issn.0254-5098.2020.06.006.
[23]
ZHANG Q, QIAN L T, DONG J N, et al. To investigate the value of IVIM-DWI and DCE-MRI quantitative parameters in early response prediction of nasopharyngeal carcinoma[J]. J Clin Radiol, 2019, 38(3): 426-430. DOI: 10.13437/j.cnki.jcr.2019.03.015.
[24]
LIU Q, JIA X, GENG Z J, et al. Application of DCE-MRI parameters combined with conventional MRI plain scan in clinical staging evaluation of nasopharyngeal carcinoma in the elderly[J]. Chin J Gerontol, 2022, 42(9): 2116-2119. DOI: 10.3969/j.issn.1005-9202.2022.09.022.
[25]
ZHENG D C, CHEN Y B, CHEN Y, et al. Dynamic contrast-enhanced MRI of nasopharyngeal carcinoma: a preliminary study of the correlations between quantitative parameters and clinical stage[J]. J Magn Reson Imaging, 2014, 39(4): 940-948. DOI: 10.1002/jmri.24249.
[26]
SRIYOOK A, LERTBUTSAYANUKUL C, JITTAPIROMSAK N. Value of dynamic contrast-enhanced magnetic resonance imaging for determining the plasma Epstein-Barr virus status and staging of nasopharyngeal carcinoma[J/OL]. Clin Imaging, 2021, 72: 1-7 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/33190027/. DOI: 10.1016/j.clinimag.2020.10.047.
[27]
SUN J Q, SHAN F F, MENG Z H, et al. Permeability quantitative parameters of MRI quantitative dynamic contrast enhanced and perfusion parameters of T1WI perfusion imaging in the different clinical staging of nasopharyngeal carcinoma[J]. Jiangxi Med J, 2020, 55(7): 801-803, 809. DOI: 10.3969/j.issn.1006-2238.2020.07.002.
[28]
KANG S K, ZHANG A, PANDHARIPANDE P V, et al. DWI for renal mass characterization: systematic review and meta-analysis of diagnostic test performance[J]. AJR Am J Roentgenol, 2015, 205(2): 317-324. DOI: 10.2214/AJR.14.13930.
[29]
RUI Y F, ZHOU N, YANG Y, et al. The values of diffusion-weighted imaging and clinical staging in the prognostic evaluation of nasopharyngeal carcinoma[J]. Chin J Otorhinolaryngol Skull Base Surg, 2022, 28(5): 39-44. DOI: 10.11798/j.issn.1007-1520.202221379.
[30]
HUANG T, JIANG P P, FAN L Z, et al. Value of multi b-value DWI of 3.0T MR in differential diagnosis of benign and malignant cervical lymph nodes in patients with nasopharyngeal carcinoma[J]. J Med Imag, 2020, 30(3): 367-370, 374.
[31]
YU H M, ZHAI Z H, MA D Y, et al. The value of multi b-values diffusion-weighted of using 3.0T MR imaging for nodal staging in nasopharyngeal carcinoma[J]. Radiol Pract, 2015, 30(7): 728-731. DOI: 10.13609/j.cnki.1000-0313.2015.07.005.
[32]
LIAO L P, LIU T, WEI B. Prediction of short-term treatment outcome of nasopharyngeal carcinoma based on voxel incoherent motion imaging and arterial spin labeling quantitative parameters[J/OL]. Eur J Radiol Open, 2022, 10: 100466 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/36590328/. DOI: 10.1016/j.ejro.2022.100466.
[33]
WU M Y, ZHANG J L. MR perfusion imaging for kidney disease[J]. Magn Reson Imaging Clin N Am, 2024, 32(1): 161-170. DOI: 10.1016/j.mric.2023.09.004.
[34]
WANG H X, YAN R F, LI Z, et al. Quantitative dynamic contrast-enhanced parameters and intravoxel incoherent motion facilitate the prediction of TP53 status and risk stratification of early-stage endometrial carcinoma[J]. Radiol Oncol, 2023, 57(2): 257-269. DOI: 10.2478/raon-2023-0023.
[35]
LIAO L P, LIAO H, LUO N B, et al. Investigating the diffusion and perfusion characteristics of intravoxel incoherent motion diffusion-weighted imaging and arterial spin labeling in different stages of nasopharyngeal carcinoma[J]. Radiol Pract, 2022, 37(1): 29-34. DOI: 10.13609/j.cnki.1000-0313.2022.01.006.
[36]
HUANG W Y, LONG L L, ZHAO Y, et al. Preliminary study with reduced field-of-view IVIM-DWI MRI technique in the staging of nasopharyngeal carcinoma[J]. Radiol Pract, 2016, 31(7): 604-608. DOI: 10.13609/j.cnki.1000-0313.2016.07.007.
[37]
LAI V, LI X, LEE V H, et al. Nasopharyngeal carcinoma: comparison of diffusion and perfusion characteristics between different tumour stages using intravoxel incoherent motion MR imaging[J]. Eur Radiol, 2014, 24(1): 176-183. DOI: 10.1007/s00330-013-2995-7.
[38]
ZHAO M J, ZHAO L H, YANG H, et al. Apparent diffusion coefficient for the prediction of tumor response to neoadjuvant chemo-radiotherapy in locally advanced rectal cancer[J/OL]. Radiat Oncol, 2021, 16(1): 17 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/33472660/. DOI: 10.1186/s13014-020-01738-6.
[39]
MALEK M, RAHMANI M, POURASHRAF M, et al. Prediction of lymphovascular space invasion in cervical carcinoma using diffusion kurtosis imaging[J/OL]. Cancer Treat Res Commun, 2022, 31: 100559 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/35460974/. DOI: 10.1016/j.ctarc.2022.100559.
[40]
HONDA M, LE BIHAN D, KATAOKA M, et al. Diffusion kurtosis imaging as a biomarker of breast cancer[J/OL]. BJR Open, 2023, 5(1): 20220038 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/37035767/. DOI: 10.1259/bjro.20220038.
[41]
CHENG Q C, REN A L, XU X H, et al. Application of DKI and IVIM imaging in evaluating histologic grades and clinical stages of clear cell renal cell carcinoma[J/OL]. Front Oncol, 2023, 13: 1203922 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/37954085/. DOI: 10.3389/fonc.2023.1203922.
[42]
CHEN Y B, REN W, ZHENG D C, et al. Diffusion kurtosis imaging predicts neoadjuvant chemotherapy responses within 4 days in advanced nasopharyngeal carcinoma patients[J]. J Magn Reson Imaging, 2015, 42(5): 1354-1361. DOI: 10.1002/jmri.24910.
[43]
XU X Q, MA G, WANG Y J, et al. Histogram analysis of diffusion kurtosis imaging of nasopharyngeal carcinoma: correlation between quantitative parameters and clinical stage[J]. Oncotarget, 2017, 8(29): 47230-47238. DOI: 10.18632/oncotarget.17591.
[44]
WU Y N, HUANG L N. The relationship between MRI diffusion kurtosis imaging and NPC clinical stage[J]. J Pract Med, 2023, 39(13): 1704-1708. DOI: 10.3969/j.issn.1006-5725.2023.13.019.
[45]
SATAKE H, ISHIGAKI S, ITO R, et al. Radiomics in breast MRI: current progress toward clinical application in the era of artificial intelligence[J]. Radiol Med, 2022, 127(1): 39-56. DOI: 10.1007/s11547-021-01423-y.
[46]
HUANG X Q, SHU J, YAN Y L, et al. Feasibility of magnetic resonance imaging-based radiomics features for preoperative prediction of extrahepatic cholangiocarcinoma stage[J/OL]. Eur J Cancer, 2021, 155: 227-235 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/34391055/. DOI: 10.1016/j.ejca.2021.06.053.
[47]
CONTI A, DUGGENTO A, INDOVINA I, et al. Radiomics in breast cancer classification and prediction[J/OL]. Semin Cancer Biol, 2021, 72: 238-250 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/32371013/. DOI: 10.1016/j.semcancer.2020.04.002.
[48]
YANG T H, ZHANG Y, LI S Y, et al. Ability of 18F-FDG PET/CT radiomic features to differentiate EGFR mutation status in patients with lung adenocarcinoma[J]. Chin J Nucl Med Mol Imag, 2021, 41(2): 65-70. DOI: 10.3760/cma.j.cn321828-20191108-00255.
[49]
ZHONG L Z, FANG X L, DONG D, et al. A deep learning MR-based radiomic nomogram may predict survival for nasopharyngeal carcinoma patients with stage T3N1M0[J/OL]. Radiother Oncol, 2020, 151: 1-9 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/32634460/. DOI: 10.1016/j.radonc.2020.06.050.
[50]
ZHONG L Z, DONG D, FANG X L, et al. A deep learning-based radiomic nomogram for prognosis and treatment decision in advanced nasopharyngeal carcinoma: a multicentre study[J/OL]. EBioMedicine, 2021, 70: 103522 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/34391094/. DOI: 10.1016/j.ebiom.2021.103522.
[51]
ZHANG L, WU X J, LIU J, et al. MRI-based deep-learning model for distant metastasis-free survival in locoregionally advanced nasopharyngeal carcinoma[J]. J Magn Reson Imaging, 2021, 53(1): 167-178. DOI: 10.1002/jmri.27308.
[52]
ZHANG B, TIAN J, DONG D, et al. Radiomics features of multiparametric MRI as novel prognostic factors in advanced nasopharyngeal carcinoma[J]. Clin Cancer Res, 2017, 23(15): 4259-4269. DOI: 10.1158/1078-0432.CCR-16-2910.
[53]
LI Q J, YU Q, GONG B B, et al. The Effect of Magnetic Resonance Imaging Based Radiomics Models in Discriminating stage Ⅰ-Ⅱ and Ⅲ-Ⅳa Nasopharyngeal Carcinoma[J/OL]. Diagnostics, 2023, 13(2): 300 [2024-01-25]. https://pubmed.ncbi.nlm.nih.gov/36673110/. DOI: 10.3390/diagnostics13020300.
[54]
YANG Q, GUO Y, OU X M, et al. Automatic T staging using weakly supervised deep learning for nasopharyngeal carcinoma on MR images[J]. J Magn Reson Imaging, 2020, 52(4): 1074-1082. DOI: 10.1002/jmri.27202.

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