Share：
Share this content in WeChat
X
[Chinese][PDF]2743
• Review •
Research progress of magnetic resonance diffusion kurtosis imaging in cervical cancer
ZHOU Siyu  FENG Feng 

Cite this article as: ZHOU S Y, FENG F. Research progress of magnetic resonance diffusion kurtosis imaging in cervical cancer[J]. Chin J Magn Reson Imaging, 2023, 14(10): 189-194. DOI:10.12015/issn.1674-8034.2023.10.034.


[Abstract] Cervical cancer is one of the most common malignant tumors of the reproductive system in women, which seriously threatens women's life and health. Determining the histological subtype and stage grade of cervical cancer is of great significance for formulating a reasonable treatment plan. In recent years, diffusion kurtosis imaging (DKI) has attracted widespread attention as a non-invasive imaging technique. DKI can reflect more realistic microdynamics and microstructure of water molecules. DKI has played an important role in the staging, grading and treatment evaluation of cervical cancer. This article will review the basic principles of DKI, the research status of DKI in cervical cancer, and the application of DKI image-based radiomics in cervical cancer, in order to provide important references for the clinical diagnosis, individualized treatment plan formulation and treatment evaluation of cervical cancer.
[Keywords] cervical cancer；diffusion kurtosis imaging；magnetic resonance imaging；diagnosis；staging and grading；efficacy evaluation

ZHOU Siyu   FENG Feng*  

Department of Radiology, Cancer Hospital of Nantong University, Nantong 226000, China

Corresponding author: FENG F, E-mail: drfengfeng@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS 2021 Nantong Municipal Social and People's Livelihood Science and Technology Project (No. MS22021047).
Received  2023-07-03
Accepted  2023-09-28
DOI: 10.12015/issn.1674-8034.2023.10.034
Cite this article as: ZHOU S Y, FENG F. Research progress of magnetic resonance diffusion kurtosis imaging in cervical cancer[J]. Chin J Magn Reson Imaging, 2023, 14(10): 189-194. DOI:10.12015/issn.1674-8034.2023.10.034.

[1]
CIBULA D, RASPOLLINI M R, PLANCHAMP F, et al. ESGO/ESTRO/ESP Guidelines for the management of patients with cervical cancer-Update 2023[J]. Int J Gynecol Cancer, 2023, 33(5): 649-666. DOI: 10.1136/ijgc-2023-004429.
[2]
BECKMANN M W, STUEBS F A, VORDERMARK D, et al. The diagnosis, treatment, and aftercare of cervical carcinoma[J]. Dtsch Arztebl Int, 2021, 118(47): 806-812. DOI: 10.3238/arztebl.m2021.0352.
[3]
SMITS A, STEINS M, VAN KOEVERDEN S, et al. Can MRI be used as a sole diagnostic modality in determining clinical stage in cervical cancer?[J/OL]. Oncologist, 2023, 28(1): e19-e25 [2023-04-30]. https://pubmed.ncbi.nlm.nih.gov/36250801. DOI: 10.1093/oncolo/oyac210.
[4]
ZHANG R, BAI Y, WEI W, et al. Basic principles of intravoxel incoherent motion and diffusional kurtosis imaging and their applications in central nervous system diseases[J]. Chin J Magn Reson Imag, 2020, 11(9): 804-808. DOI: 10.12015/issn.1674-8034.2020.09.019.
[5]
JENSEN J H, HELPERN J A, RAMANI A, et al. Diffusional kurtosis imaging: the quantification of non-gaussian water diffusion by means of magnetic resonance imaging[J]. Magn Reson Med, 2005, 53(6): 1432-1440. DOI: 10.1002/mrm.20508.
[6]
QI Y F, HE Y L, LIN C Y, et al. Diffusion-weighted imaging of cervical cancer: feasibility of ultra-high b-value at 3T[J/OL]. Eur J Radiol, 2020, 124: 108779 [2023-9-13]. https://pubmed.ncbi.nlm.nih.gov/31935594. DOI: 10.1016/j.ejrad.2019.108779.
[7]
SUN X R, WANG X C, ZHANG H, et al. Research progress of diffusion magnetic resonance imaging in mild cognitive impairment[J]. Chin J Magn Reson Imag, 2021, 12(1): 70-72, 84. DOI: 10.12015/issn.1674-8034.2021.01.015.
[8]
MENG N, WANG X J, SUN J, et al. Application of the amide proton transfer-weighted imaging and diffusion kurtosis imaging in the study of cervical cancer[J]. Eur Radiol, 2020, 30(10): 5758-5767. DOI: 10.1007/s00330-020-06884-9.
[9]
GRANATA V, FUSCO R, BELLI A, et al. Diffusion weighted imaging and diffusion kurtosis imaging in abdominal oncological setting: why and when[J/OL]. Infect Agent Cancer, 2022, 17(1): 25 [2023-04-30]. https://pubmed.ncbi.nlm.nih.gov/23882093. DOI: 10.1186/s13027-022-00441-3.
[10]
WANG M D, PERUCHO J A U, CHAN Q, et al. Diffusion kurtosis imaging in the assessment of cervical carcinoma[J/OL]. Acad Radiol, 2020, 27(5): e94-e101 [2023-04-30]. https://pubmed.ncbi.nlm.nih.gov/31324577. DOI: 10.1016/j.acra.2019.06.022.
[11]
YAMADA I, OSHIMA N, WAKANA K, et al. Uterine cervical carcinoma: evaluation using non-gaussian diffusion kurtosis imaging and its correlation with histopathological findings[J]. J Comput Assist Tomogr, 2021, 45(1): 29-36. DOI: 10.1097/rct.0000000000001042.
[12]
ZHENG X, SHEN F M, ZHENG D C, et al. The application of magnetic resonance diffusion kurtosis imaging in efficacy evaluation of early radiotherapy of cervical carcinoma[J]. Chin J Magn Reson Imag, 2023, 14(2): 68-72, 82. DOI: 10.12015/issn.1674-8034.2023.02.012.
[13]
WANG K, PAN T, ZHOU X, et al. The application of non-Gaussion DWI model in body diseases[J]. Chin J Magn Reson Imag, 2016, 7(1): 71-76. DOI: 10.12015/issn.1674-8034.2016.01.014.
[14]
CHEN J, CAO L, GU H M. The value of DKI-MRI in evaluating pathological types and differentiation degree of cervical cancer[J]. Radiol Pract, 2021, 36(5): 628-632. DOI: 10.13609/j.cnki.1000-0313.2021.05.011.
[15]
LE BIHAN D. Apparent diffusion coefficient and beyond: what diffusion MR imaging can tell us about tissue structure[J]. Radiology, 2013, 268(2): 318-322. DOI: 10.1148/radiol.13130420.
[16]
LE BIHAN D, BRETON E, LALLEMAND D, et al. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders[J]. Radiology, 1986, 161(2): 401-407. DOI: 10.1148/radiology.161.2.3763909.
[17]
GRANATA V, FUSCO R, RISI C, et al. Diffusion-weighted MRI and diffusion kurtosis imaging to detect RAS mutation in colorectal liver metastasis[J/OL]. Cancers, 2020, 12(9): 2420 [2023-04-30]. https://pubmed.ncbi.nlm.nih.gov/32858990. DOI: 10.3390/cancers12092420.
[18]
WANG Q, XIAO X, LIANG Y, et al. Diagnostic performance of diffusion MRI for differentiating benign and malignant nonfatty musculoskeletal soft tissue tumors: a systematic review and meta-analysis[J]. J Cancer, 2021, 12(24): 7399-7412. DOI: 10.7150/jca.62131.
[19]
LIANG P, YUAN G J, LI S C, et al. Non-invasive evaluation of the pathological and functional characteristics of chronic kidney disease by diffusion kurtosis imaging and intravoxel incoherent motion imaging: comparison with conventional DWI[J/OL]. Br J Radiol, 2023, 96(1141): 20220644 [2023-04-30]. https://pubmed.ncbi.nlm.nih.gov/36400040. DOI: 10.1259/bjr.20220644.
[20]
WANG L L, ZHAO X M, HUANG G, et al. Diagnostic value of by use of magnetic resonance DKI, DWI and DCE imaging in cervical naopiastic lesions[J]. J Med Imag, 2022, 32(3): 484-488. DOI: 1006-9011(2022)03-0484-05.
[21]
LI J, XUE X, ZHANG Y, et al. The differences in immune features and genomic profiling between squamous cell carcinoma and adenocarcinoma - A multi-center study in Chinese patients with uterine cervical cancer[J]. Gynecol Oncol, 2023, 175: 133-141. DOI: 10.1016/j.ygyno.2023.05.071.
[22]
MENG N, WANG J, ZHANG M, et al. Comparative analysis of diffusion kurtosis imaging and intravoxel incoherent motion for evaluating histological classification and grading of cervical squamous cell carcinoma and cervical adenocarcinoma[J]. Chin J Med Imag Technol, 2019, 35(1): 108-112. DOI: 10.13929/j.1003-3289.201803016.
[23]
WU C Y, MA C, YUAN J, et al. Exploration of potential therapeutic and prognostic value of CXC chemokines in cervical squamous cell carcinoma and endocervical adenocarcinoma based on bioinformatics analysis[J]. Math Biosci Eng, 2021, 18(6): 8201-8222. DOI: 10.3934/mbe.2021407.
[24]
MENG X, TIAN S F, MA C J, et al. APTw combined with mDixon-Quant imaging to distinguish the differentiation degree of cervical squamous carcinoma[J/OL]. Front Oncol, 2023, 13: 1105867 [2023-04-30]. https://pubmed.ncbi.nlm.nih.gov/36761975. DOI: 10.3389/fonc.2023.1105867.
[25]
MATSUO K, MANDELBAUM R S, MACHIDA H, et al. Association of tumor differentiation grade and survival of women with squamous cell carcinoma of the uterine cervix[J/OL]. J Gynecol Oncol, 2018, 29(6): e91 [2023-04-30]. https://pubmed.ncbi.nlm.nih.gov/30207099. DOI: 10.3802/jgo.2018.29.e91.
[26]
HONG S B, CHENG J J, DI W. Advances and applications of MRI in staging assessment of cervical cancer[J]. J Int Obstet Gynecol, 2021, 48(6): 634-638. DOI: 10.12280/gjfckx.20210165.
[27]
HOU M Y, SONG K, REN J P, et al. Comparative analysis of the value of amide proton transfer-weighted imaging and diffusion kurtosis imaging in evaluating the histological grade of cervical squamous carcinoma[J/OL]. BMC Cancer, 2022, 22(1): 87 [2023-04-30]. https://pubmed.ncbi.nlm.nih.gov/35057777. DOI: 10.1186/s12885-022-09205-z.
[28]
THELISSEN A A B, JÜRGENLIEMK-SCHULZ I M, VAN DER LEIJ F, et al. Upstaging by para-aortic lymph node dissection in patients with locally advanced cervical cancer: a systematic review and meta-analysis[J]. Gynecol Oncol, 2022, 164(3): 667-674. DOI: 10.1016/j.ygyno.2021.12.026.
[29]
LIU J, LI S J, LIU J J, et al. The value of DKI in evaluating pathological features and clinical staging of cervical cancer[J]. J China Clin Med Imag, 2023, 34(2): 136-140. DOI: 10.12117/jccmi.2023.02.014.
[30]
WANG P Y, THAPA D, WU G Y, et al. A study on diffusion and kurtosis features of cervical cancer based on non-Gaussian diffusion weighted model[J]. Magn Reson Imag, 2018, 47: 60-66. DOI: 10.1016/j.mri.2017.10.016.
[31]
ANANIA V, COLLIER Q, VERAART J, et al. Improved diffusion parameter estimation by incorporating T2 relaxation properties into the DKI-FWE model[J/OL]. NeuroImage, 2022, 256: 119219 [2023-09-23]. https://pubmed.ncbi.nlm.nih.gov/35447354. DOI: 10.1016/j.neuroimage.2022.119219.
[32]
RAMIREZ P T, MILAM M R. Laparoscopic extraperitoneal paraaortic lymphadenectomy in patients with locally advanced cervical cancer[J]. Gynecol Oncol, 2007, 104(2suppl 1): 9-12. DOI: 10.1016/j.ygyno.2006.10.032.
[33]
WEI J H, LIU Y, WANG M, et al. The application value of CT and MRI in preoperative assessment of lymph node metastasis of cervical cancer[J]. Chin J Clin Obstet Gynecol, 2022, 23(6): 583-586. DOI: 10.13390/j.issn.1672-1861.2022.06.006.
[34]
QIN H Y, YANG G X, XU Y, et al. Research progress on the screening value of HPV E6E7, cervical liquid-based cytology and colposcopy biopsy in cervical cancer[J]. Chin J Clin Obstet Gynecol, 2022, 23(3): 332-334. DOI: 10.13390/j.issn.1672-1861.2022.03.043.
[35]
HUANG Q H, WANG Y C, MENG X Y, et al. Amide proton transfer-weighted imaging combined with ZOOMit diffusion kurtosis imaging in predicting lymph node metastasis of cervical cancer[J/OL]. Bioengineering, 2023, 10(3): 331 [2023-04-23]. https://pubmed.ncbi.nlm.nih.gov/36978722. DOI: 10.3390/bioengineering10030331.
[36]
CUI Y Q, HUANG G, WANG L L, et al. Clinical-radiomic analysis of multi-parametric magnetic resonance imaging predicts lymphovascular space invasion and outcomes in cervical cancer[J]. Chin J Magn Reson Imag, 2023, 14(2): 73-82. DOI: 10.12015/issn.1674-8034.2023.02.013.
[37]
WANG W, FAN X F, YANG J, et al. Preliminary MRI study of extracellular volume fraction for identification of lymphovascular space invasion of cervical cancer[J]. J Magn Reson Imaging, 2023, 57(2): 587-597. DOI: 10.1002/jmri.28423.
[38]
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 [2023-04-30]. https://pubmed.ncbi.nlm.nih.gov/35460974. DOI: 10.1016/j.ctarc.2022.100559.
[39]
SIEGEL R L, MILLER K D, WAGLE N S, et al. Cancer statistics, 2023[J]. CA Cancer J Clin, 2023, 73(1): 17-48. DOI: 10.3322/caac.21763.
[40]
ZHANG Y, ZHANG K Y, JIA H D, et al. IVIM-DWI and MRI-based radiomics in cervical cancer: prediction of concurrent chemoradiotherapy sensitivity in combination with clinical prognostic factors[J]. Magn Reson Imaging, 2022, 91: 37-44. DOI: 10.1016/j.mri.2022.05.005.
[41]
LI Y, REN J, YANG J J, et al. MRI-derived radiomics analysis improves the noninvasive pretreatment identification of multimodality therapy candidates with early-stage cervical cancer[J]. Eur Radiol, 2022, 32(6): 3985-3995. DOI: 10.1007/s00330-021-08463-y.
[42]
CUSUMANO D, RUSSO L, GUI B, et al. Evaluation of early regression index as response predictor in cervical cancer: a retrospective study on T2 and DWI MR images[J]. Radiother Oncol, 2022, 174: 30-36. DOI: 10.1016/j.radonc.2022.07.001.
[43]
LI J, GAO X M, CHENG J L. Relationship of diffusion kurtosis imaging parameters with the pathologic type and prognosis of rectal tumors[J]. Chin J Oncol, 2022, 44(11): 1208-1213. DOI: 10.3760/cma.j.cn112152-20201019-00913.
[44]
HU S, PENG Y, WANG Q S, et al. T2*-weighted imaging and diffusion kurtosis imaging (DKI) of rectal cancer: correlation with clinical histopathologic prognostic factors[J]. Abdom Radiol (NY), 2022, 47(2): 517-529. DOI: 10.1007/s00261-021-03369-1.
[45]
WANG W W, ZHANG X D, ZHU L M, et al. Prediction of prognostic factors and genotypes in patients with breast cancer using multiple mathematical models of MR diffusion imaging[J/OL]. Front Oncol, 2022, 12: 825264 [2023-04-30]. https://pubmed.ncbi.nlm.nih.gov/35174093. DOI: 10.3389/fonc.2022.825264.
[46]
LIU C L, XING Y, WEI D M, et al. Diffusion kurtosis imaging as a prognostic marker in osteosarcoma patients with preoperative chemotherapy[J/OL]. Biomed Res Int, 2020, 2020: 3268138 [2023-04-30]. https://pubmed.ncbi.nlm.nih.gov/33029501. DOI: 10.1155/2020/3268138.
[47]
GILLIES R J, KINAHAN P E, HRICAK H. Radiomics: images are more than pictures, they are data[J]. Radiology, 2016, 278(2): 563-577. DOI: 10.1148/radiol.2015151169.
[48]
LI Y Y, TAN Y. Research progress in radiomics on prognosis prediction of lower-grade gliomas[J]. Chin J Magn Reson Imag, 2022, 13(11): 129-132, 148. DOI: 10.12015/issn.1674-8034.2022.11.025.
[49]
JIA Y S, WU H. Research advances in radiogenomics[J]. Chin J Magn Reson Imag, 2022, 13(3): 166-170. DOI: 10.12015/issn.1674-8034.2022.03.040.
[50]
ZHANG Q, YU X D, OUYANG H, et al. Whole-tumor texture model based on diffusion kurtosis imaging for assessing cervical cancer: a preliminary study[J]. Eur Radiol, 2021, 31(8): 5576-5585. DOI: 10.1007/s00330-020-07612-z.
[51]
TIAN S F, LIU A L, GUO Y, et al. Application of radiomics methods based on DKI sequence MK map for differentiating squamous cell carcinoma from cervix adenocarcinoma[J]. Chin J Med Imag, 2021, 29(7): 716-720. DOI: 10.3969/j.issn.1005-5185.2021.07.015.
[52]
WANG M D, PERUCHO J A U, VARDHANABHUTI V, et al. Radiomic features of T2-weighted imaging and diffusion kurtosis imaging in differentiating clinicopathological characteristics of cervical carcinoma[J]. Acad Radiol, 2022, 29(8): 1133-1140. DOI: 10.1016/j.acra.2021.08.018.
[53]
HE B, CHEN W B, WU Y J, et al. Prognostic value of diffusion kurtosis imaging histogram based nomogram model for cervical cancer[J]. Chin J Radiat Oncol, 2023, 32(7): 606-611. DOI: 10.3760/cma.j.cn113030-20230116-00012.

PREV Progress of MRI in evaluation of pelvic lymph node metastasis from cervical cancer
NEXT Progress in the application of artificial intelligence in transpathology
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn