Share：
Share this content in WeChat
X
[Chinese][PDF]3962
• Clinical Article •
The application of magnetic resonance diffusion kurtosis imaging in efficacy evaluation of early radiotherapy of cervical carcinoma
ZHENG Xiang  SHEN Fangmin  ZHENG Dechun  CHEN Wenjuan 

Cite this article as: 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 Imaging, 2023, 14(2): 68-72, 82. DOI:10.12015/issn.1674-8034.2023.02.012.


[Abstract] Objective To investigate the application value of MR diffusion kurtosis imaging (DKI) in evaluating the early efficacy of radiotherapy for cervical cancer.Materials and Methods The study included 21 patients with age of (57.24±10.35) years old. All patients were pathologically confirmed as cervical cancer, including 19 cases of cervical squamous cell carcinoma, one case of adenocarcinoma and one case of adenosquamous carcinoma. All patients underwent conventional MRI and DKI scanning with 3.0 T MR machine before radiotherapy, 10 fractions of radiotherapy and the same day after radiotherapy. The efficacy of radiotherapy was evaluated at 10 fractions according to the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST version 1.1). Among them, complete remission (CR) and partial remission (PR) were response groups. Stable disease (SD) and progressive disease (PD) were the non-response groups. The changes of each parameter of DKI at different stages of radiotherapy were analyzed and compared between the two groups and the receiver operating characteristic (ROC) curve of each parameter of DKI was drawn.Results Compared with the values before radiotherapy, the mean diffusivity (MD) values of lesions after radiotherapy were increased (P＜0.001), and the mean kurtosis (MK) values were decreased (P=0.019) after radiotherapy. In addition, the response group had a significantly higher MD value than the non-response group before radiotherapy (P=0.016), but there was no significant difference after radiotherapy (P＞0.05). The response group had a significantly lower MK level than the non-response group before and after radiotherapy (P＜0.05). Before radiotherapy the area under the curve (AUC) of MD and MK for predicting the early efficacy of radiotherapy was 0.817 and 0.822 respectively, while the AUC of the combination of MD and MK was 0.923, and there was no significant difference in the AUC of the three methods (Z=1.264, P=0.206). However, the Youden index of combined diagnosis was higher, that is, the sensitivity (87.5%) and specificity (92.3%) were higher.Conclusions DKI has the ability to predict the early efficacy of radiotherapy for cervical carcinoma, and the combination of MD and MK has a better predictive ability than single application.
[Keywords] cervical cancer；magnetic resonance imaging；diffusion kurtosis imaging；mean diffusivity；mean kurtosis；radiation therapy；efficacy evaluation

ZHENG Xiang1*   SHEN Fangmin1   ZHENG Dechun1   CHEN Wenjuan2  

1 Department of Radiologic Diagnosis, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou 350014, China

2 Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou 350014, China

*Correspondence to: Zheng X, E-mail: skipskip@sina.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Natural Science Foundation of Fujian Province (No. 2021J01426); Foundation of Fujian Cancer Hospital (No. 2021YN13).
Received  2022-10-08
Accepted  2023-02-01
DOI: 10.12015/issn.1674-8034.2023.02.012
Cite this article as: 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 Imaging, 2023, 14(2): 68-72, 82. DOI:10.12015/issn.1674-8034.2023.02.012.

[1]
XIA C F, DONG X S, LI H, et al. Cancer statistics in China and United States, 2022: profiles, trends, and determinants[J]. Chin Med J (Engl), 2022, 135(5): 584-590. DOI: 10.1097/CM9.0000000000002108.
[2]
YANG E, HUANG S Y, RAN X T, et al. The 5-year overall survival of cervical cancer in stage IIIC-r was little different to stage Ⅰ and Ⅱ: a retrospective analysis from a single center[J/OL]. BMC Cancer, 2021, 21(1): 203 [2022-10-05]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7912513. DOI: 10.1186/s12885-021-07890-w.
[3]
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 [2022-10-05]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185934. DOI: 10.1186/s13027-022-00441-3.
[4]
TAHA H T, CHAD J A, CHEN J J. DKI enhances the sensitivity and interpretability of age-related DTI patterns in the white matter of UK biobank participants[J]. Neurobiol Aging, 2022, 115: 39-49. DOI: 10.1016/j.neurobiolaging.2022.03.008.
[5]
GOGHARI V M, KUSI M, SHAKEEL M K, et al. Diffusion kurtosis imaging of white matter in bipolar disorder[J/OL]. Psychiatry Res Neuroimaging, 2021, 317: 111341 [2022-9-05]. https://www.sciencedirect.com/science/article/abs/pii/S0925492721000937. DOI: 10.1016/j.pscychresns.2021.111341.
[6]
DENG X Y, DUAN Z Q, FANG S B, et al. Advances in the application and research of magnetic resonance diffusion kurtosis imaging in the musculoskeletal system[J/OL]. J Magn Reson Imaging, 2022 [2022-10-07]. https://pubmed.ncbi.nlm.nih.gov/36200754. DOI: 10.1002/jmri.28463.
[7]
GUO J, DONG C, WU Z J, et al. Diffusion kurtosis imaging assessment of the response to radiotherapy in a VX2 bone tumor model: an animal study[J]. Acta Radiol, 2022, 63(2): 182-191. DOI: 10.1177/0284185121989519.
[8]
XIE S H, LANG R, LI B, et al. Evaluation of diffuse glioma grade and proliferation activity by different diffusion-weighted-imaging models including diffusion kurtosis imaging (DKI) and mean apparent propagator (MAP) MRI[J]. Neuroradiology, 2023, 65(1): 55-64. DOI: 10.1007/s00234-022-03000-0.
[9]
PENG Q, TANG W, HUANG Y, et al. Diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma[J]. Chin Med J (Engl), 2020, 133(20): 2403-2409. DOI: 10.1097/CM9.0000000000001074.
[10]
LO Y C, LI T J T, LIN T C, et al. Microstructural evidence of neuroinflammation for psychological symptoms and pain in patients with fibromyalgia[J]. J Rheumatol, 2022, 49(8): 942-947. DOI: 10.3899/jrheum.211170.
[11]
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 [2022-10-05]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8780242. DOI: 10.1186/s12885-022-09205-z.
[12]
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 [2022-10-05]. https://pubmed.ncbi.nlm.nih.gov/31324577. DOI: 10.1016/j.acra.2019.06.022.
[13]
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.
[14]
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 [2022-10-05]. https://pubmed.ncbi.nlm.nih.gov/35460974. DOI: 10.1016/j.ctarc.2022.100559.
[15]
CAO K, WANG S, ZHAO B, et al. MR diffusion kurtosis imaging versus standard diffusion imaging: changes with radiation in uterine cervical carcinoma xenografts[J]. Chin J Magn Reson Imaging, 2017, 8(9): 685-690. DOI: 10.12015/issn.1674-8034.2017.09.008.
[16]
BHATLA N, AOKI D, SHARMA D N, et al. Cancer of the cervix uteri: 2021 update[J]. Int J Gynaecol Obstet, 2021, 155(Suppl 1): 28-44. DOI: 10.1002/ijgo.13865.
[17]
XU W N, YU L J, YANG Z G, et al. Comparison of PERCIST1.0 and RECIST1.1 for the evaluation of concurrent chemoradiotherapy response in advanced cervical cancer[J]. J China Clin Med Imaging, 2017, 28(10): 747-751. DOI: 10.3969/j.issn.1008-1062.2017.10.013.
[18]
PENG Q H, LV W G. Interpretation of NCCN guidelines for cervical cancer, version 1.2022[J]. J Pract Oncol, 2022, 37(3): 205-214. DOI: 10.13267/j.cnki.syzlzz.2022.034.
[19]
BU X H, ZHANG J, TIAN F Z, et al. Value of diffusion-weighted magnetic resonance imaging combined with miR-18a level in predicting radiosensitivity of cervical cancer[J]. Med Sci Monit, 2018, 24: 7271-7278. DOI: 10.12659/MSM.910990.
[20]
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.
[21]
ZHENG X, CHEN Y B, XIAO Y P, et al. Early diagnosis of radio-insensitive human nasopharyngeal carcinoma xenograft models by diffusion kurtosis imaging[J]. Magn Reson Imaging, 2019, 55: 128-132. DOI: 10.1016/j.mri.2018.08.001.
[22]
WANG J, HAN Y L, LI Y, et al. Targeting tumor physical microenvironment for improved radiotherapy[J/OL]. Small Methods, 2022, 6(11): e2200570 [2022-10-05]. https://onlinelibrary.wiley.com/doi/10.1002/smtd.202200570. DOI: 10.1002/smtd.202200570.
[23]
TANG C, LU G X, XU J M, et al. Diffusion kurtosis imaging and MRI-detected extramural venous invasion in rectal cancer: correlation with clinicopathological prognostic factors[J/OL]. Abdom Radiol (NY), 2022 [2023-01-06]. https://link.springer.com/article/10.1007/s00261-022-03782-0. DOI: 10.1007/s00261-022-03782-0.
[24]
CAO J F, LUO X, ZHOU Z M, et al. Comparison of diffusion-weighted imaging mono-exponential mode with diffusion kurtosis imaging for predicting pathological grades of clear cell renal cell carcinoma[J/OL]. Eur J Radiol, 2020, 130: 109195 [2022-10-05]. https://www.ejradiology.com/article/S0720-048X(20)30384-3. DOI: 10.1016/j.ejrad.2020.109195.
[25]
ZHANG A D, SU X H, WANG Y F, et al. Predicting the effects of radiotherapy based on diffusion kurtosis imaging in a xenograft mouse model of esophageal carcinoma[J/OL]. Exp Ther Med, 2021, 21(4): 327 [2023-01-01]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7903468.
[26]
WANG W W, LV S Q, XUN J, et al. Comparison of diffusion kurtosis imaging and dynamic contrast enhanced MRI in prediction of prognostic factors and molecular subtypes in patients with breast cancer[J/OL]. Eur J Radiol, 2022, 154: 110392 [2022-10-05]. https://www.ejradiology.com/article/S0720-048X(22)00242-X. DOI: 10.1016/j.ejrad.2022.110392.
[27]
CAO L K, CHEN J, DUAN T, et al. Diffusion kurtosis imaging (DKI) of hepatocellular carcinoma: correlation with microvascular invasion and histologic grade[J]. Quant Imaging Med Surg, 2019, 9(4): 590-602. DOI: 10.21037/qims.2019.02.14.
[28]
YUAN S J, QIAO T K, QIANG J W. Diffusion-weighted imaging and diffusion kurtosis imaging for early evaluation of the response to docetaxel in rat epithelial ovarian cancer[J/OL]. J Transl Med, 2018, 16(1): 340 [2022-09-05]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6282389. DOI: 10.1186/s12967-018-1714-1.
[29]
KUMARI S, ADVANI D, SHARMA S, et al. Combinatorial therapy in tumor microenvironment: where do we stand?[J/OL]. Biochim Biophys Acta Rev Cancer, 2021, 1876(2): 188585 [2022-9-05]. https://www.sciencedirect.com/science/article/abs/pii/S0304419X21000822. DOI: 10.1016/j.bbcan.2021.188585.
[30]
ZHENG D C, ZHANG X X, LIN H, et al. Diffusion kurtosis imaging in early assessment on response of neoadjuvant chemotherapy for metastatic neck lymph nodes from nasopharyngeal carcinoma[J]. Chin J Med Imaging Technol, 2020, 36(2): 220-224. DOI: 10.13929/j.issn.1003-3289.2020.02.012.
[31]
YU J, XU Q, SONG J C, et al. The value of diffusion kurtosis magnetic resonance imaging for assessing treatment response of neoadjuvant chemoradiotherapy in locally advanced rectal cancer[J]. Eur Radiol, 2017, 27(5): 1848-1857. DOI: 10.1007/s00330-016-4529-6.
[32]
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.
[33]
LI X W, YANG L, WANG Q M, et al. Soft tissue sarcomas: IVIM and DKI correlate with the expression of HIF-1α on direct comparison of MRI and pathological slices[J]. Eur Radiol, 2021, 31(7): 4669-4679. DOI: 10.1007/s00330-020-07526-w.
[34]
TANG C L, QIN Y J, HU Q L, et al. Diagnostic value of multi-model high-resolution diffusion-weighted MR imaging in breast lesions: based on simultaneous multi-slice readout-segmented echo-planar imaging[J/OL]. Eur J Radiol, 2022, 154: 110439 [2022-10-05]. https://www.ejradiology.com/article/S0720-048X(22)00289-3. DOI: 10.1016/j.ejrad.2022.110439.
[35]
LI Q, CAO B H, TAN Q X, et al. Prediction of muscle invasion of bladder cancer: a comparison between DKI and conventional DWI[J/OL]. Eur J Radiol, 2021, 136: 109522 [2022-9-05]. https://linkinghub.elsevier.com/retrieve/pii/S0720-048X(21)00002-4. DOI: 10.1016/j.ejrad.2021.109522.
[36]
GUO J, SUN W K, DONG C, et al. Intravoxel incoherent motion imaging combined with diffusion kurtosis imaging to assess the response to radiotherapy in a rabbit VX2 malignant bone tumor model[J/OL]. Cancer Imaging, 2022, 22(1): 47 [2022-10-05]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9446876. DOI: 10.1186/s40644-022-00488-w.

PREV The value of ADC map and T2WI radiomics analysis of the primary tumor for prediction of bone metastases in prostate cancer
NEXT Clinical-radiomic analysis of multi-parametric magnetic resonance imaging predicts lymphovascular space invasion and outcomes in cervical cancer
  


LINK


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