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Research progress of radiomics based on multi-parameter MRI in lymphatic space invasion of endometrial cancer
ZHAO Jifu  CAO Xinshan 

Cite this article as: ZHAO J F, CAO X S. Research progress of radiomics based on multi-parameter MRI in lymphatic space invasion of endometrial cancer[J]. Chin J Magn Reson Imaging, 2023, 14(6): 171-175. DOI:10.12015/issn.1674-8034.2023.06.031.


[Abstract] Among the numerous factors that affect the prognosis of endometrial cancer (EC), lymphatic vascular space invasion (LVSI) is an important independent risk factor, and current conventional imaging methods cannot accurately diagnose it before surgery. In recent years, the radioomics of multi-parameter magnetic resonance imaging (mpMRI) has shown great potential for diagnosing LVSI in EC, making it possible to accurately diagnose LVSI before surgery. This review summarizes and compares the latest research progress of mpMRI radiomics in EC LVSI, and innovatively proposed combining the radiomics of mpMRI with the tumor marker HE4 (human epididymis protein 4) to construct the radiomics model, aiming to improve the detection rate of LVSI and make more accurate judgments of patient progression, thereby assisting clinical treatment of patients with more precise treatment and improving their prognosis.
[Keywords] endometrial carcinoma；invasion of lymphatic vascular space；preoperative prediction；multi-parameter；magnetic resonance imaging；radiomics

ZHAO Jifu   CAO Xinshan*  

Department of Radiology, Affiliated Hospital of Binzhou Medical College, Binzhou 256603, China

Corresponding author: Cao XS, E-mail: byfycxs@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Science and Technology Development Plan Project of Shandong Province (No. 2010GSF10265).
Received  2022-12-25
Accepted  2023-04-28
DOI: 10.12015/issn.1674-8034.2023.06.031
Cite this article as: ZHAO J F, CAO X S. Research progress of radiomics based on multi-parameter MRI in lymphatic space invasion of endometrial cancer[J]. Chin J Magn Reson Imaging, 2023, 14(6): 171-175. DOI:10.12015/issn.1674-8034.2023.06.031.

[1]
BROOKS R A, FLEMING G F, LASTRA R R, et al. Current recommendations and recent progress in endometrial cancer[J]. CA Cancer J Clin, 2019, 69(4): 258-279. DOI: 10.3322/caac.21561.
[2]
MAKKER V, MACKAY H, RAY-COQUARD I, et al. Endometrial cancer[J/OL]. Nat Rev Dis Primers, 2021, 7(1): 88 [2022-11-16]. https://www.nature.com/articles/s41572-021-00324-8. DOI: 10.1038/s41572-021-00324-8.
[3]
WANG Z L, ZHANG S, MA Y F, et al. A nomogram prediction model for lymph node metastasis in endometrial cancer patients[J/OL]. BMC Cancer, 2021, 21(1): 748 [2022-11-16]. https://bmccancer.biomedcentral.com/articles/10.1186/s12885-021-08466-4. DOI: 10.1186/s12885-021-08466-4.
[4]
LEI H F, XU S X, MAO X D, et al. Systemic immune-inflammatory index as a predictor of lymph node metastasis in endometrial cancer[J]. J Inflamm Res, 2021, 14: 7131-7142. DOI: 10.2147/JIR.S345790.
[5]
WANG J Z, XU P, YANG X Y, et al. Association of myometrial invasion with lymphovascular space invasion, lymph node metastasis, recurrence, and overall survival in endometrial cancer: a meta-analysis of 79 studies with 68, 870 patients[J/OL]. Front Oncol, 2021, 11: 762329 [2022-11-16]. https://www.frontiersin.org/articles/10.3389/fonc.2021.762329/full. DOI: 10.3389/fonc.2021.762329.
[6]
COKMEZ H, YILMAZ A. Lower uterine segment involvement in lymphovascular space invasion and lymph node metastasis in endometrioid endometrial cancer[J]. Ginekol Pol, 2019, 90(6): 314-319. DOI: 10.5603/GP.2019.0057.
[7]
PENG Y J, LIU X W, TANG X, et al. Preoperative predicting lymphov-ascular space invasion in endometrial carcinoma by nomogram based on mpMRI radiomics[J]. Chin J Magn Reson Imaging, 2022, 13(7): 61-67. DOI: 10.12015/issn.1674-8034.2022.07.011.
[8]
JIN X Y, SHEN C J, YANG X D, et al. Association of tumor size with myometrial invasion, lymphovascular space invasion, lymph node metastasis, and recurrence in endometrial cancer: a meta-analysis of 40 studies with 53, 276 patients[J/OL]. Front Oncol, 2022, 12: 881850 [2022-11-18]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9201106/. DOI: 10.3389/fonc.2022.881850.
[9]
CHUNG J H, LEE S H, YI E, et al. Impact of resection margin length and tumor depth on the local recurrence after thoracoscopic pulmonary wedge resection of a single colorectal metastasis[J]. J Thorac Dis, 2019, 11(5): 1879-1887. DOI: 10.21037/jtd.2019.05.12.
[10]
MANDATO V D, TORRICELLI F, MASTROFILIPPO V, et al. Accuracy of preoperative endometrial biopsy and intraoperative frozen section in predicting the final pathological diagnosis of endometrial cancer[J]. Surg Oncol, 2020, 35: 229-235. DOI: 10.1016/j.suronc.2020.09.003.
[11]
LAMBIN P, RIOS-VELAZQUEZ E, LEIJENAAR R, et al. Radiomics: extracting more information from medical images using advanced feature analysis[J]. Eur J Cancer, 2012, 48(4): 441-446. DOI: 10.1016/j.ejca.2011.11.036.
[12]
KUMAR V, GU Y, BASU S, et al. Radiomics: the process and the challenges[J]. Magn Reson Imaging, 2012, 30(9): 1234-1248. DOI: 10.1016/j.mri.2012.06.010.
[13]
AERTS H J W L, VELAZQUEZ E R, LEIJENAAR R T H, et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach[J/OL]. Nat Commun, 2014, 5: 4006 [2022-11-18]. https://www.nature.com/articles/ncomms5006. DOI: 10.1038/ncomms5006.
[14]
BAO Y Z, CHENG Q, GE Y Q, et al. Differential diagnosis of renal cancer subtypes: a conditional inference tree model based on enhanced CT radiomic features[J]. Chin J Med Imaging, 2020, 28(7): 520-523. DOI: 10.3969/j.issn.1005-5185.2020.07.009.
[15]
MAYERHOEFER M E, MATERKA A, LANGS G, et al. Introduction to radiomics[J]. J Nucl Med, 2020, 61(4): 488-495. DOI: 10.2967/jnumed.118.222893.
[16]
BALAGURUNATHAN Y, GU Y H, WANG H, et al. Reproducibility and prognosis of quantitative features extracted from CT images[J]. Transl Oncol, 2014, 7(1): 72-87. DOI: 10.1593/tlo.13844.
[17]
CHEN-MAYER H H, FULD M K, HOPPEL B, et al. Standardizing CT lung density measure across scanner manufacturers[J]. Med Phys, 2017, 44(3): 974-985. DOI: 10.1002/mp.12087.
[18]
FASMER K E, HODNELAND E, DYBVIK J A, et al. Whole-volume tumor MRI radiomics for prognostic modeling in endometrial cancer[J]. J Magn Reson Imaging, 2021, 53(3): 928-937. DOI: 10.1002/jmri.27444.
[19]
KURATA Y, NISHIO M, KIDO A, et al. Automatic segmentation of the uterus on MRI using a convolutional neural network[J/OL]. Comput Biol Med, 2019, 114: 103438 [2022-10-06]. https://www.sciencedirect.com/science/article/abs/pii/S0010482519303154?via%3Dihub. DOI: 10.1016/j.compbiomed.2019.103438.
[20]
FU B Y, SHI B, CHEN Y L, et al. Combination analysis of ADC value with texture analysis based on T2WI and CE-T1WI for the preoperative prediction about grade, DMI, LVSI in endometrial carcinoma[J]. J Clin Radiol, 2022, 41(10): 1908-1915. DOI: 10.13437/j.cnki.jcr.2022.10.013.
[21]
LIU X F, YAN B C, LI Y, et al. Radiomics feature as a preoperative predictive of lymphovascular invasion in early-stage endometrial cancer: a multicenter study[J/OL]. Front Oncol, 2022, 12: 966529 [2022-10-06]. https://www.frontiersin.org/articles/10.3389/fonc.2022.966529/full. DOI: 10.3389/fonc.2022.966529.
[22]
WANG Y X, WU K H. Research progress of radiomics in endometrial cancer[J]. Chin J Med Imaging, 2022, 30(6): 630-634. DOI: 10.3969/j.issn.1005-5185.2022.06.021.
[23]
PARK S H, LIM H, BAE B K, et al. Robustness of magnetic resonance radiomic features to pixel size resampling and interpolation in patients with cervical cancer[J/OL]. Cancer Imaging, 2021, 21(1): 19 [2022-10-06]. https://cancerimagingjournal.biomedcentral.com/articles/10.1186/s40644-021-00388-5. DOI: 10.1186/s40644-021-00388-5.
[24]
RIZZO S, BOTTA F, RAIMONDI S, et al. Radiomics: the facts and the challenges of image analysis[J/OL]. Eur Radiol Exp, 2018, 2(1): 36 [2022-10-06]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6234198/. DOI: 10.1186/s41747-018-0068-z.
[25]
LONG L, SUN J Q, JIANG L L, et al. MRI-based traditional radiomics and computer-vision nomogram for predicting lymphovascular space invasion in endometrial carcinoma[J]. Diagn Interv Imaging, 2021, 102(7/8): 455-462. DOI: 10.1016/j.diii.2021.02.008.
[26]
ZHANG Y P, ZHANG B R, LIANG F, et al. Radiomics features on non-contrast-enhanced CT scan can precisely classify AVM-related hematomas from other spontaneous intraparenchymal hematoma types[J]. Eur Radiol, 2019, 29(4): 2157-2165. DOI: 10.1007/s00330-018-5747-x.
[27]
SONG Y F, SHANG H, MA Y M, et al. Can conventional DWI accurately assess the size of endometrial cancer?[J]. Abdom Radiol (NY), 2020, 45(4): 1132-1140. DOI: 10.1007/s00261-019-02220-y.
[28]
NOUGARET S, HORTA M, SALA E, et al. Endometrial cancer MRI staging: updated guidelines of the European society of urogenital radiology[J]. Eur Radiol, 2019, 29(2): 792-805. DOI: 10.1007/s00330-018-5515-y.
[29]
REYES-PÉREZ J A, VILLASEÑOR-NAVARRO Y, JIMÉNEZ DE LOS SANTOS M E, et al. The apparent diffusion coefficient (ADC) on 3-T MRI differentiates myometrial invasion depth and histological grade in patients with endometrial cancer[J]. Acta Radiol, 2020, 61(9): 1277-1286. DOI: 10.1177/0284185119898658.
[30]
WEI M Z, ZHAO Z H, HU H J, et al. MRI radiomics parameters in predicting p53 of cervical squamous cell carcinoma[J]. Chin J Med Imaging, 2019, 27(12): 934-937, 947. DOI: 10.3969/j.issn.1005-5185.2019.12.013.
[31]
XUE K, LI Z L, LI Z H, et al. Identify HER-2 over expression breast cancer based on radiomics of multi-parametric MRI[J]. Radiol Pract, 2020, 35(2): 186-189. DOI: 10.13609/j.cnki.1000-0313.2020.02.012.
[32]
CUI Y J, ZHENG T, YANG L S, et al. The predictive value of radiomics based nomogram model for lymphatic vascular space infiltration of endometrial carcinoma[J]. China Med Devices, 2021, 36(5): 85-90. DOI: 10.3969/j.issn.1674-1633.2021.05.020.
[33]
ZHANG K Y, ZHANG Y, FANG X, et al. Nomograms of combining apparent diffusion coefficient value and radiomics for preoperative risk evaluation in endometrial carcinoma[J/OL]. Front Oncol, 2021, 11: 705456 [2022-11-18]. https://www.frontiersin.org/articles/10.3389/fonc.2021.705456/full. DOI: 10.3389/fonc.2021.705456.
[34]
BEREBY-KAHANE M, DAUTRY R, MATZNER-LOBER E, et al. Prediction of tumor grade and lymphovascular space invasion in endometrial adenocarcinoma with MR imaging-based radiomic analysis[J]. Diagn Interv Imaging, 2020, 101(6): 401-411. DOI: 10.1016/j.diii.2020.01.003.
[35]
LAVAUD P, FEDIDA B, CANLORBE G, et al. Preoperative MR imaging for ESMO-ESGO-ESTRO classification of endometrial cancer[J]. Diagn Interv Imaging, 2018, 99(6): 387-396. DOI: 10.1016/j.diii.2018.01.010.
[36]
LUO Y, MEI D D, GONG J S, et al. Multiparametric MRI-based radiomics nomogram for predicting lymphovascular space invasion in endometrial carcinoma[J]. J Magn Reson Imaging, 2020, 52(4): 1257-1262. DOI: 10.1002/jmri.27142.
[37]
UENO Y, FORGHANI B, FORGHANI R, et al. Endometrial carcinoma: MR imaging-based texture model for preoperative risk stratification-a preliminary analysis[J]. Radiology, 2017, 284(3): 748-757. DOI: 10.1148/radiol.2017161950.
[38]
WANG C Y, SUN M Y. Research progress on histological classification and lymphatic vascular space infiltration of endometrial carcinoma by multi-modal MR imaging[J]. J Clin Radiol, 2020, 39(9): 1885-1889. DOI: 10.12117/jccmi.2019.02.013.
[39]
BAI Z Q, SHI J, DUAN X H, et al. Prediction of lymph vascular space invasion in cervical squamous cell carcinoma by using volumetric dynamic contrast-enhanced MRI[J]. Chin J Magn Reson Imaging, 2019, 10(2): 145-149. DOI: 10.12015/issn.1674-8034.2019.02.014.
[40]
ZHOU J Y, LI H, JIANG J X, et al. Value of radiomic model based on DCE-MRI parameter images in predicting vascular infiltration in endo-metrial carcinoma[J]. Radiol Pract, 2021, 36(12): 1533-1537. DOI: 10.13609/j.cnki.1000-0313.2021.12.014.
[41]
MAIS V, FAIS M L, PEIRETTI M, et al. HE4 tissue expression as A putative prognostic marker in low-risk/low-grade endometrioid endometrial cancer: a review[J]. Curr Oncol, 2022, 29(11): 8540-8555. DOI: 10.3390/curroncol29110673.
[42]
MOORE R G, MILLER C M, BROWN A K, et al. Utility of tumor marker HE4 to predict depth of myometrial invasion in endometrioid adenocarcinoma of the uterus[J]. Int J Gynecol Cancer, 2011, 21(7): 1185-1190. DOI: 10.1097/IGC.0b013e3182229ad8.
[43]
BEHROUZI R, BARR C E, CROSBIE E J. HE4 as a biomarker for endometrial cancer[J/OL]. Cancers (Basel), 2021, 13(19): 4764 [2022-11-18]. https://www.mdpi.com/2072-6694/13/19/4764. DOI: 10.3390/cancers13194764.
[44]
ESPIAU ROMERA A, CUESTA GUARDIOLA T, BENITO VIELBA M, et al. HE4 tumor marker as a predictive factor for lymphatic metastasis in endometrial cancer[J]. Int J Gynaecol Obstet, 2020, 149(3): 265-268. DOI: 10.1002/ijgo.13140.
[45]
DEGEZ M, CAILLON H, CHAUVIRÉ-DROUARD A, et al. HE4 in the diagnostic approach of endometrial cancer in patients with postmenopausal bleeding, the METRODEC protocol: protocol for a multicenter prospective study[J/OL]. Diagnostics (Basel), 2021, 11(7): 1274 [2022-11-18]. https://www.mdpi.com/2075-4418/11/7/1274. DOI: 10.3390/diagnostics11071274.
[46]
DEWAN R, DEWAN A, HARE S, et al. Diagnostic performance of serum human epididymis protein 4 in endometrial carcinoma: a pilot study[J]. J Clin Diagn Res, 2017, 11(7): XC01-XC05. DOI: 10.7860/JCDR/2017/28926.10285.
[47]
CYMBALUK-PŁOSKA A, GARGULIŃSKA P, BULSA M, et al. Can the determination of HE4 and CA125 markers affect the treatment of patients with endometrial cancer?[J/OL]. Diagnostics (Basel), 2021, 11(4): 626 [2022-11-18]. https://www.mdpi.com/2075-4418/11/4/626. DOI: 10.3390/diagnostics11040626.
[48]
DEGEZ M, CAILLON H, CHAUVIRÉ-DROUARD A, et al. Endometrial cancer: a systematic review of HE4, REM and REM-B[J]. Clin Chim Acta, 2021, 515: 27-36. DOI: 10.1016/j.cca.2020.12.029.
[49]
VAN TIMMEREN J E, CESTER D, TANADINI-LANG S, et al. Radiomics in medical imaging- "how-to" guide and critical reflection[J/OL]. Insights Imaging, 2020, 11(1): 91 [2022-11-18]. https://insightsimaging.springeropen.com/articles/10.1186/s13244-020-00887-2. DOI: 10.1186/s13244-020-00887-2.
[50]
CHETAN M R, GLEESON F V. Radiomics in predicting treatment response in non-small-cell lung cancer: current status, challenges and future perspectives[J]. Eur Radiol, 2021, 31(2): 1049-1058. DOI: 10.1007/s00330-020-07141-9.
[51]
LIU Z Y, WANG S, DONG D, et al. The applications of radiomics in precision diagnosis and treatment of oncology: opportunities and challenges[J]. Theranostics, 2019, 9(5): 1303-1322. DOI: 10.7150/thno.30309.

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