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Research progress of MRI radiomics in the evaluation of adverse pathological factors of early cervical cancer
CHEN Yuanyuan  XIN Zhonghong  MA Qinqin  LEI Junqiang 

CHEN Y Y, XIN Z H, MA Q Q, et al. Research progress of MRI radiomics in the evaluation of adverse pathological factors of early cervical cancer[J]. Chin J Magn Reson Imaging, 2023, 14(8): 187-191. DOI:10.12015/issn.1674-8034.2023.08.033.


[Abstract] Surgery is the recommended treatment for patients with cervical cancer (mainly in stage ⅠB1, ⅠB2 and ⅡA1). Postoperative patients with adverse pathological factors need adjuvant therapy, but the complications of multimode therapy can not be ignored. Early identification of risk factors is helpful for clinicians to formulate treatment plans and select appropriate patients for primary radical surgery to improve the quality of life and prognosis of patients. The potential of radiomics to guide personalized medicine is widely recognized tumor size, deep stromal invasion (DSI), lymphovascular space invasion (LVSI), lymph node metastases (LNM) and parametrial infiltration (PMI) those have all been a major subject of research in the radiomics field. By moving the diagnosis forward, it provides an important basis for the diagnosis and treatment of cervical cancer. However, the repeatability of imaging features, small data sets and time-consuming hinder its application in clinical decision-making. This article reviews the applications, limitations and prospects of MRI-based radiomics in cervical cancer, so as to provide new ideas for clinical practice and scientific research.
[Keywords] early-stage cervical cancer；risk factors；magnetic resonance imaging；radiomics；prognosis

CHEN Yuanyuan1   XIN Zhonghong2   MA Qinqin1   LEI Junqiang2*  

1 The First School of Clinical Medicine, Lanzhou University, Lanzhou 730000, China

2 Department of Radiology, the First Hospital of Lanzhou University, Lanzhou 730000, China

Corresponding author: Lei JQ, E-mail: leijq2011@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Natural Science Foundation of Gansu Province (No. 20JR10RA684).
Received  2023-01-29
Accepted  2023-06-28
DOI: 10.12015/issn.1674-8034.2023.08.033
CHEN Y Y, XIN Z H, MA Q Q, et al. Research progress of MRI radiomics in the evaluation of adverse pathological factors of early cervical cancer[J]. Chin J Magn Reson Imaging, 2023, 14(8): 187-191. DOI:10.12015/issn.1674-8034.2023.08.033.

[1]
ARBYN M, WEIDERPASS E, BRUNI L, et al. Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis[J/OL]. Lancet Glob Health, 2020, 8(2): e191-e203 [2023-01-20]. https://doi.org/10.1016/S2214-109X(19)30482-6. DOI: 10.1016/s2214-109x(19)30482-6.
[2]
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.
[3]
ZHANG J N, JIANG P, TU Y, et al. Significance of the number of intermediate-risk factors in cervical cancer patients treated with radical hysterectomy: a retrospective study of 976 patients[J]. J Invest Surg, 2022, 35(5): 1098-1105. DOI: 10.1080/08941939.2021.2013578.
[4]
KILIC F, CAKIR C, YUKSEL D, et al. Analysis of the prognostic factors determining the oncological outcomes in patients with high-risk early-stage cervical cancer[J]. J Obstet Gynaecol, 2022, 42(2): 281-288. DOI: 10.1080/01443615.2021.1882974.
[5]
PERRUCCI E, CERROTTA A, MACCHIA G, et al. Postoperative treatment of intermediate-risk early stage cervical cancer: results of a survey from the Gynecology Study Groupin the AIRO Gyn and MITO Groups[J/OL]. Crit Rev Oncol, 2022, 174: 103704 [2023-01-20]. https://doi.org/10.1016/j.critrevonc.2022.103704. DOI: 10.1016/j.critrevonc.2022.103704.
[6]
WAN T, TU H, LIU L L, et al. Perineural invasion should be regarded as an intermediate-risk factor for recurrence in surgically treated cervical cancer: a propensity score matching study[J]. Dis Markers, 2021, 2021: 1-8. DOI: 10.1155/2021/1375123.
[7]
PARK J Y, CHONG G O, PARK J Y, et al. Tumor budding in cervical cancer as a prognostic factor and its possible role as an additional intermediate-risk factor[J]. Gynecol Oncol, 2020, 159(1): 157-163. DOI: 10.1016/j.ygyno.2020.07.030.
[8]
LEVINSON K, BEAVIS A L, PURDY C, et al. Beyond Sedlis-a novel histology-specific nomogram for predicting cervical cancer recurrence risk: an NRG/GOG ancillary analysis[J]. Gynecol Oncol, 2021, 162(3): 532-538. DOI: 10.1016/j.ygyno.2021.06.017.
[9]
MA C C, ZHANG Y, LI R, et al. Risk of parametrial invasion in women with early stage cervical cancer: a meta-analysis[J]. Arch Gynecol Obstet, 2018, 297(3): 573-580. DOI: 10.1007/s00404-017-4597-0.
[10]
ZHU J, CAO L J, WEN H, et al. The clinical and prognostic implication of deep stromal invasion in cervical cancer patients undergoing radical hysterectomy[J]. J Cancer, 2020, 11(24): 7368-7377. DOI: 10.7150/jca.50752.
[11]
PARK J, KIM Y J, SONG M K, et al. Definitive chemoradiotherapy versus radical hysterectomy followed by tailored adjuvant therapy in women with early-stage cervical cancer presenting with pelvic lymph node metastasis on pretreatment evaluation: a propensity score matching analysis[J/OL]. Cancers, 2021, 13(15): 3703 [2023-01-19]. https://doi.org/10.3390/cancers13153703. DOI: 10.3390/cancers13153703.
[12]
LANDONI F, MANEO A, COLOMBO A, et al. Randomised study of radical surgery versus radiotherapy for stage Ib-IIa cervical cancer[J]. Lancet, 1997, 350(9077): 535-540. DOI: 10.1016/S0140-6736(97)02250-2.
[13]
MANGANARO L, NICOLINO G M, DOLCIAMI M, et al. Radiomics in cervical and endometrial cancer[J/OL]. Br J Radiol, 2021, 94(1125): 20201314 [2023-01-22]. https://doi.org/10.1259/bjr.20201314. DOI: 10.1259/bjr.20201314.
[14]
LIU H L, QIU Q T, CHANG C, et al. Research progress of radiomics in cervical cancer[J]. Chin J Cancer Prev Treat, 2023, 30(3): 181-186. DOI: 10.16073/j.cnki.cjcpt.2023.03.09.
[15]
NICOLET V, CARIGNAN L, BOURDON F, et al. MR imaging of cervical carcinoma: a practical staging approach[J]. Radiographics, 2000, 20(6): 1539-1549. DOI: 10.1148/radiographics.20.6.g00nv111539.
[16]
ZHANG W F, CHEN C L, LIU P, et al. Staging early cervical cancer in China: data from a multicenter collaborative[J/OL]. Int J Gynecol Cancer, 2019: ijgc-2019-000263 [2023-01-20]. https://doi.org/10.1136/ijgc-2019-000263. DOI: 10.1136/ijgc-2019-000263.
[17]
MITCHELL D G, SNYDER B, COAKLEY F, et al. Early invasive cervical cancer: tumor delineation by magnetic resonance imaging, computed tomography, and clinical examination, verified by pathologic results, in the ACRIN 6651/GOG 183 Intergroup Study[J]. J Clin Oncol, 2006, 24(36): 5687-5694. DOI: 10.1200/JCO.2006.07.4799.
[18]
XIAO M L, YAN B C, LI Y, et al. Diagnostic performance of MR imaging in evaluating prognostic factors in patients with cervical cancer: a meta-analysis[J]. Eur Radiol, 2020, 30(3): 1405-1418. DOI: 10.1007/s00330-019-06461-9.
[19]
ZHU H C, CAO K, LI X T, et al. MRI assessment of early cervical cancer invasion depth of stroma[J]. Chin J Med Imaging Technol, 2020, 36(4): 559-563. DOI: 10.13929/j.issn.1003-3289.2020.04.019.
[20]
WOO S, SUH C H, KIM S Y, et al. Magnetic resonance imaging for detection of parametrial invasion in cervical cancer: an updated systematic review and meta-analysis of the literature between 2012 and 2016[J]. Eur Radiol, 2018, 28(2): 530-541. DOI: 10.1007/s00330-017-4958-x.
[21]
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.
[22]
ZHANG W F, CHEN C L. The research progress in the diagnosis of parametrial infiltration with MRI in cervical cancer[J]. J Med Imaging, 2019, 29(4): 670-673. DOI: 10.3760/j.issn:1005-1201.2002.07.011.
[23]
ZHANG J, XUE H D, LI S, et al. Value of magnetic resonance imaging in parametrial invasion of cervical cancer[J]. Chin J Magn Reson Imaging, 2014, 5(4): 287-290. DOI: 10.3969/j.issn.1674-8034.2014.04.010.
[24]
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.
[25]
OLTHOF E P, VAN DER AA M A, ADAM J A, et al. The role of lymph nodes in cervical cancer: incidence and identification of lymph node metastases-a literature review[J]. Int J Clin Oncol, 2021, 26(9): 1600-1610. DOI: 10.1007/s10147-021-01980-2.
[26]
SALVO G, RAMIREZ P T, LEVENBACK C F, et al. Sensitivity and negative predictive value for sentinel lymph node biopsy in women with early-stage cervical cancer[J]. Gynecol Oncol, 2017, 145(1): 96-101. DOI: 10.1016/j.ygyno.2017.02.005.
[27]
BALAYA V, GUANI B, PACHE B, et al. Sentinel lymph node in cervical cancer: time to move forward[J/OL]. Chin Clin Oncol, 2021, 10(2): 18 [2023-01-19]. https://doi.org/10.21037/cco-21-5. DOI: 10.21037/cco-21-5.
[28]
PÁLSDÓTTIR K, FRIDSTEN S, BLOMQVIST L, et al. Interobserver agreement of transvaginal ultrasound and magnetic resonance imaging in local staging of cervical cancer[J]. Ultrasound Obstet Gynecol, 2021, 58(5): 773-779. DOI: 10.1002/uog.23662.
[29]
REN J, HE Y L, LI Y, et al. The value of model based on radiomics features of T2-weighted imaging and clinical feature in diagnosing the depth of stromal invasion of cervical squamous cell carcinoma[J]. Med J Peking Union Med Coll Hosp, 2021, 12(5): 705-712. DOI: 10.12290/xhyxzz.2021-0437.
[30]
REN J, LI Y, YANG J J, et al. MRI-based radiomics analysis improves preoperative diagnostic performance for the depth of stromal invasion in patients with early stage cervical cancer[J/OL]. Insights Imaging, 2022, 13(1): 17 [2023-01-22]. https://doi.org/10.1186/s13244-022-01156-0. DOI: 10.1186/s13244-022-01156-0.
[31]
DU W, WANG Y, LI D D, et al. Preoperative prediction of lymphovascular space invasion in cervical cancer with radiomics-based nomogram[J/OL]. Front Oncol, 2021, 11: 637794 [2023-01-20]. https://doi.org/10.3389/fonc.2021.637794. DOI: 10.3389/fonc.2021.637794.
[32]
YU H Q, ZHAI J, LIU C L, et al. Radiomics based on MRI for predicting cervical cancer lymph-vascular space invasion[J]. Chin J Med Imaging Technol, 2022, 38(3): 421-426. DOI: 10.13929/j.issn.1003-3289.2022.03.023.
[33]
HUANG G, CUI Y Q, WANG P, et al. Multi-parametric magnetic resonance imaging-based radiomics analysis of cervical cancer for preoperative prediction of lymphovascular space invasion[J/OL]. Front Oncol, 2021, 11: 663370 [2023-01-21]. https://doi.org/10.3389/fonc.2021.663370. DOI: 10.3389/fonc.2021.663370.
[34]
HUA W Q, XIAO T H, JIANG X R, et al. Lymph-vascular space invasion prediction in cervical cancer: exploring radiomics and deep learning multilevel features of tumor and peritumor tissue on multiparametric MRI[J/OL]. Biomed Signal Process Control, 2020, 58: 101869 [2023-01-21] https://doi.org/10.1016/j.bspc.2020.101869. DOI: 10.1016/j.bspc.2020.101869.
[35]
CUI L P, YU T, KAN Y Y, et al. Multi-parametric MRI-based peritumoral radiomics on prediction of lymph-vascular space invasion in early-stage cervical cancer[J]. Diagn Interv Radiol, 2022, 28(4): 312-321. DOI: 10.5152/dir.2022.20657.
[36]
ZHANG X, ZHANG Y, ZHANG G, et al. Deep learning with radiomics for disease diagnosis and treatment: challenges and potential[J/OL]. Front Oncol, 2022, 12: 773840 [2023-01-21]. https://doi.org/10.3389/fonc.2022.773840. DOI: 10.3389/fonc.2022.773840.
[37]
JIANG X R, LI J X, KAN Y Y, et al. MRI based radiomics approach with deep learning for prediction of vessel invasion in early-stage cervical cancer[J]. IEEE/ACM Trans Comput Biol Bioinform, 2021, 18(3): 995-1002. DOI: 10.1109/TCBB.2019.2963867.
[38]
WANG T, GAO T T, GUO H, et al. Preoperative prediction of parametrial invasion in early-stage cervical cancer with MRI-based radiomics nomogram[J]. Eur Radiol, 2020, 30(6): 3585-3593. DOI: 10.1007/s00330-019-06655-1.
[39]
LIU Q F, ZHANG Q Y, HUANG J, et al. Research on preoperative prediction of parametrial tissue invasion of cervical cancer based on T2WI combined ADC imaging[J]. China Med Devices, 2021, 36(12): 90-93, 107. DOI: 10.3969/j.issn.1674-1633.2021.12.022.
[40]
LI X X, LIN T T, LIU B, et al. Diagnosis of cervical cancer with parametrial invasion on whole-tumor dynamic contrast-enhanced magnetic resonance imaging combined with whole-lesion texture analysis based on T2-weighted images[J/OL]. Front Bioeng Biotechnol, 2020, 8: 590 [2023-01-21]. https://doi.org/10.3389/fbioe.2020.00590. DOI: 10.3389/fbioe.2020.00590.
[41]
CHAROENKWAN P, SHOOMBUATONG W, NANTASUPHA C, et al. iPMI: machine learning-aided identification of parametrial invasion in women with early-stage cervical cancer[J/OL]. Diagnostics, 2021, 11(8): 1454 [2023-01-24]. https://doi.org/10.3390/diagnostics11081454. DOI: 10.3390/diagnostics11081454.
[42]
LI L C, ZHANG J, ZHE X, et al. A meta-analysis of MRI-based radiomic features for predicting lymph node metastasis in patients with cervical cancer[J/OL]. Eur J Radiol, 2022, 151: 110243 [2023-01-21]. https://doi.org/10.1016/j.ejrad.2022. DOI: 10.1016/j.ejrad.2022.110243.
[43]
SONG J C, HU Q M, MA Z L, et al. Feasibility of T2WI-MRI-based radiomics nomogram for predicting normal-sized pelvic lymph node metastasis in cervical cancer patients[J]. Eur Radiol, 2021, 31(9): 6938-6948. DOI: 10.1007/s00330-021-07735-x.
[44]
ZHANG Y, ZHANG K Y, JIA H D, et al. Feasibility of predicting pelvic lymph node metastasis based on IVIM-DWI and texture parameters of the primary lesion and lymph nodes in patients with cervical cancer[J]. Acad Radiol, 2022, 29(7): 1048-1057. DOI: 10.1016/j.acra.2021.08.026.
[45]
XIA X M, LI D D, DU W, et al. Radiomics based on nomogram predict pelvic lymphnode metastasis in early-stage cervical cancer[J/OL]. Diagnostics, 2022, 12(10): 2446 [2023-01-20]. https://doi.org/10.3390/diagnostics12102446. DOI: 10.3390/diagnostics12102446.
[46]
SHI J X, DONG Y, JIANG W Y, et al. MRI-based peritumoral radiomics analysis for preoperative prediction of lymph node metastasis in early-stage cervical cancer: a multi-center study[J]. Magn Reson Imaging, 2022, 88: 1-8. DOI: 10.1016/j.mri.2021.12.008.
[47]
XIAO M L, WEI Y, ZHANG J, et al. MRI texture analysis for preoperative prediction of lymph node metastasis in patients with nonsquamous cell cervical carcinoma[J]. Acad Radiol, 2022, 29(11): 1661-1671. DOI: 10.1016/j.acra.2022.01.005.
[48]
ZHANG J J, WANG Y T, CAO D Y, et al. MRI-based three-dimensional reconstruction for staging cervical cancer and predicting high-risk patients[J/OL]. Ann Transl Med, 2021, 9(18): 1398 [2023-01-23]. https://doi.org/10.21037/atm-21-2246. DOI: 10.21037/atm-21-2246.
[49]
YI Q Q, ZHOU Z, LUO Y, et al. Construction of prediction model of intermediate risk factors for early cervical cancer based on preoperative MRI radiomics and clinical features[J]. Chin J Magn Reson Imaging, 2022, 13(4): 124-127, 136. DOI: 10.12015/issn.1674-8034.2022.04.024.
[50]
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.

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