Share：
Share this content in WeChat
X
[Chinese][PDF]99385
• Clinical Article •
Multiparametric magnetic resonance imaging to characterize pathological grading and stage of cervical squamous cell carcinoma
LIU Jiren  XU Yi  GUO Limei  SI Peng  GUO Juan 

Cite this article as: Liu JR, Xu Y, Guo LM, et al. Multiparametric magnetic resonance imaging to characterize pathological grading and stage of cervical squamous cell carcinoma[J]. Chin J Magn Reson Imaging, 2021, 12(12): 29-33. DOI:10.12015/issn.1674-8034.2021.12.006.


[Abstract] Objective To investigate the value of quantitative parameters derived from T1 mapping, diffusion weighted imaging (DWI) and dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in pathologically grading and staging of cervical squamous cell carcinoma (CSCC). Materials and Methods: A total of 65 patients with pathology confirmed CSCC were enrolled in this study, including 11 cases of well differentiated, 32 cases of moderately differentiated, 22 case of poorly differentiated, and 37 case of early-stage (FIGO ⅠB-ⅡA), 28 case of late-stage (FIGO ⅡB-Ⅳ). Patients underwent pretreatment T1 mapping, DWI and DCE-MRI scan and T1, ADC, Ktrans and Kep values of tumor tissues were obtained. One-way ANOVA was used to compare the differences of quantitative parameters among different pathological grades. The independent sample t test was used to assess the difference between the early- and late-stage group. ROC curves analysis was performed to determine the diagnostic efficacy of quantitative parameters.Results T1, ADC and Ktrans values were significant difference in different pathological grade of CSCC (P＜0.05). In term of distinguishing early-from late-stage, T1 value in the early-stage CSCC was higher, and Ktrans values was lower than the late-stage CSCC. The differences were significant (P＜0.05). The area under ROC curve (AUC) of T1, ADC and Ktrans values in the diagnosis of poorly differentiated CSCC were 0.83, 0.74 and 0.79, respectively. A combination of these quantitative parameters showed the highest diagnostic efficiency with an AUC of 0.91. The AUC of T1 and Ktrans values in the diagnosis of early stage CSCC was 0.67 and 0.65, respectively, and a combination of T1 and Ktrans achieved an AUC of 0.69.Conclusion T1 mapping, DWI and DCE-MRI quantitative parameters can be used as predictors to evaluate the pathological grade and staging of CSCC. The combination of multiple parameters can improve the diagnostic sensitivity of cervical squamous cell carcinoma, which has high clinical application value.
[Keywords] cervical squamous cell carcinoma；magnetic resonance imaging；longitudinal relaxation time；diffusion-weighted imaging；dynamic contrast enhanced imaging

LIU Jiren1   XU Yi2   GUO Limei2   SI Peng3   GUO Juan3*  

1 Department of Cancer Center, Third Hospital of Shanxi Medical University (Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences), Taiyuan 030032, China

2 Department of Radiology, Second Hospital of Shanxi Medical School, Taiyuan 030001, China

3 Department of Medical Imaging Center, Third Hospital of Shanxi Medical University (Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences), Taiyuan 030032, China

Guo J, E-mail: 13934110426@163.com

Conflicts of interest   None.

Received  2021-08-09
Accepted  2021-11-05
DOI: 10.12015/issn.1674-8034.2021.12.006
Cite this article as: Liu JR, Xu Y, Guo LM, et al. Multiparametric magnetic resonance imaging to characterize pathological grading and stage of cervical squamous cell carcinoma[J]. Chin J Magn Reson Imaging, 2021, 12(12): 29-33. DOI:10.12015/issn.1674-8034.2021.12.006.

[1]
Zhang S, McNamara M, Batur P. Cervical Cancer Screening: What's New? Updates for the Busy Clinician[J]. Am J Med, 2018, 131 (6): 702.e1-702.e5. DOI: 10.1016/j.amjmed.2018.01.020.
[2]
Cohen PA, Jhingran A, Oaknin A, et al. Cervical cancer[J]. Lancet, 2019, 393(10167): 169-182. DOI: 10.1016/s0140-6736(18)32470-x.
[3]
National Health Commission of The People's Republic of China. Chinese guidelines for diagnosis and treatment of cervical cancer 2018 (English version)[J]. Chin J Cancer Res, 2019, 31(2): 295-305. DOI: 10.21147/j.issn.1000-9604.2019.02.04.
[4]
Koh WJ, Abu-Rustum NR, Bean S, et al. Cervical Cancer, Version 3. 2019, NCCN Clinical Practice Guidelines in Oncology[J]. J Natl Compr Canc Netw, 2019, 17(1): 64-84. DOI: 10.6004/jnccn.2019.0001.
[5]
Cibula D, Pötter R, Planchamp F, et al. The European Society of Gynaecological Oncology/European Society for Radiotherapy and Oncology/European Society of Pathology guidelines for the management of patients with cervical cancer[J]. Radiother Oncol, 2018, 127(3): 404-416. DOI: 10.1016/j.radonc.2018.03.003.
[6]
Azuma Y, Chou SC, Lininger RA, et al. Hypoxia and differentiation in squamous cell carcinomas of the uterine cervix: pimonidazole and involucrin[J]. Clin Cancer Res, 2003, 9(13): 4944-52.
[7]
Okada S, Tsuda H, Ohmi K, et al. Immature glandular features in squamous cell carcinoma of the uterine cervix as an independent indicator of resistance to radiotherapy[J]. Int J Gynecol Cancer, 2002, 12(3): 277-285. DOI: 10.1046/j.1525-1438.2002.t01-1-01126.x.
[8]
Matsuo K, Mandelbaum RS, Machida H, et al. Association of tumor differentiation grade and survival of women with squamous cell carcinoma of the uterine cervix[J]. J Gynecol Oncol, 2018, 29(6) :e91. DOI: 10.3802/jgo.2018.29.e91.
[9]
Balcacer P, Shergill A, Litkouhi B. MRI of cervical cancer with a surgical perspective: staging, prognostic implications and pitfalls[J]. Abdom Radiol (NY), 2019, 44(7): 2557-2571. DOI: 10.1007/s00261-019-01984-7.
[10]
Vandecaveye V, Dresen R, De Keyzer F. Novel imaging techniques in gynaecological cancer[J]. Curr Opin Oncol, 2017, 29(5): 335-342. DOI: 10.1097/cco.0000000000000385.
[11]
Zhou Y, Liu J, Liu C, et al. Intravoxel incoherent motion diffusion weighted MRI of cervical cancer-Correlated with tumor differentiation and perfusion[J]. Magn Reson Imaging, 2016, 34(8): 1050-1056. DOI: 10.1016/j.mri.2016.04.009.
[12]
Lund KV, Simonsen TG, Hompland T, et al. Short-term pretreatment DCE-MRI in prediction of outcome in locally advanced cervical cancer[J]. Radiother Oncol, 2015, 115(3): 379-385. DOI: 10.1016/j.radonc.2015.05.001.
[13]
Winfield JM, Orton MR, Collins DJ, et al. Separation of type and grade in cervical tumours using non-mono-exponential models of diffusion-weighted MRI[J]. Eur Radiol, 2017, 27(2): 627-636. DOI: 10.1007/s00330-016-4417-0.
[14]
Lund KV, Simonsen TG, Kristensen GB, et al. DCE-MRI of locally-advanced carcinoma of the uterine cervix: Tofts analysis versus non-model-based analyses[J]. Radiat Oncol, 2020, 15(1): 79. DOI: 10.1186/s13014-020-01526-2.
[15]
Taylor AJ, Salerno M, Dharmakumar R, et al. T1 Mapping: Basic Techniques and Clinical Applications[J]. JACC Cardiovasc Imaging, 2016, 9(1): 67-81. DOI: 10.1016/j.jcmg.2015.11.005.
[16]
Panda A, OʼConnor G, Lo WC, et al. Targeted Biopsy Validation of Peripheral Zone Prostate Cancer Characterization With Magnetic Resonance Fingerprinting and Diffusion Mapping[J]. Invest Radiol, 2019, 54(8): 485-493. DOI: 10.1097/rli.0000000000000569.
[17]
Xie JP, Zhang WD, Zhu JY, et al. The clinical value of T1 and T2 values in predicting brain glioma grading and cell proliferation activity[J]. Chin J Magn Reson Imaging, 2021, 12(1): 15-20. DOI: 10.12015/issn.1674-8034.2021.01.004.
[18]
Saleh M, Virarkar M, Javadi S, et al. Cervical Cancer: 2018 Revised International Federation of Gynecology and Obstetrics Staging System and the Role of Imaging[J]. Am J Roentgenol, 2020, 214(5): 1182-1195. DOI: 10.2214/AJR.19.21819.
[19]
Reiter U, Reiter C, Kräuter C, et al. Cardiac magnetic resonance T1 mapping. Part 2: Diagnostic potential and applications[J]. Eur J Radiol, 2018, 109: 235-247. DOI: 10.1016/j.ejrad.2018.10.013.
[20]
Stanisz GJ, Odrobina EE, Pun J, et al. T1, T2 relaxation and magnetization transfer in tissue at 3T[J]. Magn Reson Med, 2005, 54 (3): 507-512. DOI: 10.1002/mrm.20605.
[21]
Panda A, Obmann VC, Lo WC, et al. MR Fingerprinting and ADC Mapping for Characterization of Lesions in the Transition Zone of the Prostate Gland[J]. Radiology, 2019, 292(3): 685-694. DOI: 10.1148/radiol.2019181705.
[22]
Liu L, Yin B, Shek K, et al. Role of quantitative analysis of T2 relaxation time in differentiating benign from malignant breast lesions[J]. J Int Med Res, 2018, 46(5): 1928-1935. DOI: 10.1177/0300060517721071.
[23]
Nöth U, Tichy J, Tritt S, et al. Quantitative T1 mapping indicates tumor infiltration beyond the enhancing part of glioblastomas[J]. NMR Biomed, 2020, 33(3): e4242. DOI: 10.1002/nbm.4242.
[24]
Adams LC, Jurmeister P, Ralla B, et al. Assessment of the extracellular volume fraction for the grading of clear cell renal cell carcinoma: first results and histopathological findings[J]. Eur Radiol, 2019, 29(11): 5832-5843. DOI: 10.1007/s00330-019-06087-x.
[25]
Peng ZP, Jiang MJ, Cai HS, et al. Gd-EOB-DTPA-enhanced magnetic resonance imaging combined with T1 mapping predicts the degree of differentiation in hepatocellular carcinoma[J]. BMC Cancer, 2016, 16: 625. DOI: 10.1186/s12885-016-2607-4.
[26]
Porcari AM, Negrão F, Tripodi GL, et al. Molecular Signatures of High-Grade Cervical Lesions[J]. Front Oncol, 2018, 8: 99. DOI: 10.3389/fonc.2018.00099.
[27]
Jakobsen I, Kaalhus O, Lyng H, et al. Detection of necrosis in human tumour xenografts by proton magnetic resonance imaging[J]. Br J Cancer, 1995, 71(3): 456-461. DOI: 10.1038/bjc.1995.93.
[28]
Zhang FF, Gao XM, Cheng JL, et al. Feasibility of Quantitative T1-mapping Reflecting Histological Features of Cervical Cancer: A Primary Study[J]. J Clin Radiol, 2020, 39(9): 1807-1811. DOI: 10.13437/j.cnki.jcr.2020.09.029.
[29]
Dappa E, Elger T, Hasenburg A, et al. The value of advanced MRI techniques in the assessment of cervical cancer: a review[J]. Insights Imaging, 2017, 8(5): 471-481. DOI: 10.1007/s13244-017-0567-0.
[30]
Baur ADJ, Hansen CM, Rogasch J, et al. Evaluation of T1 relaxation time in prostate cancer and benign prostate tissue using a Modified Look-Locker inversion recovery sequence[J]. Sci Rep, 2020, 10(1): 3121. DOI: 10.1038/s41598-020-59942-z.
[31]
Wang L, Gaddam S, Wang N, et al. Multiparametric Mapping Magnetic Resonance Imaging of Pancreatic Disease[J]. Front Physiol, 2020, 11: 8. DOI: 10.3389/fphys.2020.00008.

PREV Diagnostic value of ultra-high b-value DWI in peripheral prostate cancer
NEXT Application of different radiomics models based on MRI conventional T2WI in preoperative tri-classification of ovarian epithelial tumors
  


LINK


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