Jiang X, Tang H, Chen T (2018) Epidemiology of gynecologic cancers in China. J Gynecol Oncol 29:https://doi.org/10.3802/jgo.2018.29.e7.

Huijgens AN, Mertens HJ (2013) Factors predicting recurrent endometrial cancer. Facts Views Vis Obgyn 5:179–186.

CAS  PubMed  PubMed Central  Google Scholar 

Siegel RL, Miller KD, Jemal A (2020) Cancer statistics, 2020. CA Cancer J Clin 70:7–30.https://doi.org/10.3322/caac.21590.

Article  PubMed  Google Scholar 

Proppe L, Alkatout I, Koch R et al (2022) Impact of lymphadenectomy on short- and long-term complications in patients with endometrial cancer. Arch Gynecol Obstet 306:811–819.https://doi.org/10.1007/s00404-022-06396-5.

Article  PubMed  PubMed Central  Google Scholar 

Fotopoulou C, El-Balat A, du Bois A et al (2015) Systematic pelvic and paraaortic lymphadenectomy in early high-risk or advanced endometrial cancer. Arch Gynecol Obstet 292:1321–1327.https://doi.org/10.1007/s00404-015-3746-6.

Article  CAS  PubMed  Google Scholar 

Berek JS, Matias-Guiu X, Creutzberg C et al (2023) FIGO staging of endometrial cancer: 2023. Int J Gynaecol Obstet 162:383–394.https://doi.org/10.1002/ijgo.14923.

Article  PubMed  Google Scholar 

Harris KL, Maurer KA, Jarboe E, Werner TL, Gaffney D (2020) LVSI positive and NX in early endometrial cancer: Surgical restaging (and no further treatment if N0), or adjuvant ERT? Gynecol Oncol 156:243–250.https://doi.org/10.1016/j.ygyno.2019.09.016.

Article  PubMed  Google Scholar 

Raffone A, Travaglino A, Raimondo D et al (2021) Prognostic value of myometrial invasion and TCGA groups of endometrial carcinoma. Gynecol Oncol 162:401–406.https://doi.org/10.1016/j.ygyno.2021.05.029.

Article  PubMed  Google Scholar 

Helpman L, Kupets R, Covens A et al (2014) Assessment of endometrial sampling as a predictor of final surgical pathology in endometrial cancer. Br J Cancer 110:609–615.https://doi.org/10.1038/bjc.2013.766.

Article  CAS  PubMed  Google Scholar 

Dimitraki M, Tsikouras P, Bouchlariotou S et al (2011) Clinical evaluation of women with PMB. Is it always necessary an endometrial biopsy to be performed? A review of the literature. Arch Gynecol Obstet 283:261–266.https://doi.org/10.1007/s00404-010-1601-3.

Article  PubMed  Google Scholar 

Yip SS, Aerts HJ (2016) Applications and limitations of radiomics. Phys Med Biol 61:R150-https://doi.org/10.1088/0031-9155/61/13/r150.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Lambin P, Rios-Velazquez E, Leijenaar R et al (2012) Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer 48:441–446.https://doi.org/10.1016/j.ejca.2011.11.036.

Article  PubMed  PubMed Central  Google Scholar 

Lambin P, Leijenaar RTH, Deist TM et al (2017) Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol 14:749–762.https://doi.org/10.1038/nrclinonc.2017.141.

Article  PubMed  Google Scholar 

Fang R, Lin N, Weng S, Liu K, Chen X, Cao D (2024) Multiparametric MRI radiomics improves preoperative diagnostic performance for local staging in patients with endometrial cancer. Abdominal Radiology 49:875–887.https://doi.org/10.1007/s00261-023-04149-9.

Article  PubMed  Google Scholar 

Yue X, He X, He S et al (2023) Multiparametric magnetic resonance imaging-based radiomics nomogram for predicting tumor grade in endometrial cancer. Frontiers in Oncology https://doi.org/10.3389/fonc.2023.1081134.

Article  PubMed  PubMed Central  Google Scholar 

Wang Y, Liu W, Lu Y et al (2024) Fully Automated Identification of Lymph Node Metastases and Lymphovascular Invasion in Endometrial Cancer From Multi-Parametric MRI by Deep Learning. Journal of Magnetic Resonance Imaging 60:2730–2742.https://doi.org/10.1002/jmri.29344.

Article  PubMed  Google Scholar 

Chen X, Wang Y, Shen M et al (2020) Deep learning for the determination of myometrial invasion depth and automatic lesion identification in endometrial cancer MR imaging: a preliminary study in a single institution. European Radiology 30:4985–4994.https://doi.org/10.1007/s00330-020-06870-1.

Article  PubMed  Google Scholar 

Mao W, Chen C, Gao H, Xiong L, Lin Y (2022) A deep learning-based automatic staging method for early endometrial cancer on MRI images. Front Physiol 13:974245.https://doi.org/10.3389/fphys.2022.974245.

Article  PubMed  PubMed Central  Google Scholar 

Miccò M, Gui B, Russo L et al (2022) Preoperative Tumor Texture Analysis on MRI for High-Risk Disease Prediction in Endometrial Cancer: A Hypothesis-Generating Study. Journal of Personalized Medicine https://doi.org/10.3390/jpm12111854.

Article  PubMed  PubMed Central  Google Scholar 

Yan BC, Ma FH, Li Y et al (2022) An MRI radiomics nomogram improves the accuracy in identifying eligible candidates for fertility-preserving treatment in endometrioid adenocarcinoma. Am J Cancer Res 12:1056–1068.

PubMed  PubMed Central  Google Scholar 

Bereby-Kahane M, Dautry R, Matzner-Lober E et al (2020) Prediction of tumor grade and lymphovascular space invasion in endometrial adenocarcinoma with MR imaging-based radiomic analysis. Diagnostic and Interventional Imaging 101:401–411.https://doi.org/10.1016/j.diii.2020.01.003.

Article  CAS  PubMed  Google Scholar 

Yamada I, Miyasaka N, Kobayashi D et al (2019) Endometrial Carcinoma: Texture Analysis of Apparent Diffusion Coefficient Maps and Its Correlation with Histopathologic Findings and Prognosis. Radiology: Imaging Cancer https://doi.org/10.1148/rycan.2019190054.

Article  PubMed  PubMed Central  Google Scholar 

Gates M, Gates A, Pieper D et al (2022) Reporting guideline for overviews of reviews of healthcare interventions: development of the PRIOR statement. Bmj 378:e070849.https://doi.org/10.1136/bmj-2022-070849.

Article  PubMed  PubMed Central  Google Scholar 

Whiting PF, Rutjes AW, Westwood ME et al (2011) QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 155:529–536.https://doi.org/10.7326/0003-4819-155-8-201110180-00009.

Article  PubMed  Google Scholar 

Moses LE, Shapiro D, Littenberg B (1993) Combining independent studies of a diagnostic test into a summary ROC curve: data-analytic approaches and some additional considerations. Stat Med 12:1293–1316.https://doi.org/10.1002/sim.4780121403.

Article  CAS  PubMed  Google Scholar 

Leeflang MM, Deeks JJ, Takwoingi Y, Macaskill P (2013) Cochrane diagnostic test accuracy reviews. Syst Rev https://doi.org/10.1186/2046-4053-2-82.

Article  PubMed  PubMed Central  Google Scholar 

Soliman PT, Oh JC, Schmeler KM et al (2005) Risk factors for young premenopausal women with endometrial cancer. Obstet Gynecol 105:575–580.https://doi.org/10.1097/01.AOG.0000154151.14516.f7.

Article  PubMed  Google Scholar 

Bo J, Jia H, Zhang Y et al (2022) Preoperative Prediction Value of Pelvic Lymph Node Metastasis of Endometrial Cancer: Combining of ADC Value and Radiomics Features of the Primary Lesion and Clinical Parameters. Journal of Oncology 2022:1–10.https://doi.org/10.1155/2022/3335048.

Article  Google Scholar 

Chen J, Gu H, Fan W et al (2021) MRI-Based Radiomic Model for Preoperative Risk stratification in Stage I Endometrial Cancer. Journal of Cancer 12:726–734.https://doi.org/10.7150/jca.50872.

Article  PubMed  PubMed Central  Google Scholar 

Fang R, Lin N, Weng S, Liu K, Chen X, Cao D (2024) Multiparametric MRI radiomics improves preoperative diagnostic performance for local staging in patients with endometrial cancer. Abdom Radiol (NY) 49:875–887.https://doi.org/10.1007/s00261-023-04149-9.

Article  PubMed  Google Scholar 

Han Y, Xu H, Ming Y et al (2020) Predicting myometrial invasion in endometrial cancer based on whole-uterine magnetic resonance radiomics. Journal of Cancer Research and Therapeutics https://doi.org/10.4103/jcrt.JCRT_1393_20.

Article